diff --git a/math/E题V2(1).pdf b/math/E题V2.pdf similarity index 100% rename from math/E题V2(1).pdf rename to math/E题V2.pdf diff --git a/math/E题V2_Q1_Q2模型结果汇总.md b/math/E题V2_Q1_Q2模型结果汇总.md new file mode 100644 index 0000000..576f834 --- /dev/null +++ b/math/E题V2_Q1_Q2模型结果汇总.md @@ -0,0 +1,83 @@ +# E 题 V2：Q1 / Q2 模型与实验结果汇总 + +本文件汇总 [E题V2.pdf](E题V2.pdf) 对应的 Q1、Q2 实现和正式实验结果。Q1 的算法复核见 [Q1/V2_REVIEW.md](Q1/V2_REVIEW.md)，Q2 的算法复核见 [Q2/V2_REVIEW.md](Q2/V2_REVIEW.md)。 + +## Q1：模态对齐与分支探针 + +Q1 为 100 个样本构建 0.1 秒物理时间主网格，保留真实末段长度、逐维掩码和覆盖率；文本使用冻结 BERT 特征与 CTC 硬/后验对齐，音频提取 74 维特征，视觉使用 OpenFace 2.2.0 的 35 维特征。主特征包含 100 个样本、300 条模态明细，总计 44,321,715 字节。数据结构与读取接口见 [Q1/README.md](Q1/README.md)。 + +对 B0–B4 使用按 `video_id` 分组的五折 GroupKFold；100 个样本分属 37 个来源视频组，缩放器只在每折训练组上拟合。表中 Accuracy 和 Macro-F1 是按情感极性（负向、零值/中性、正向）分类的 OOF 指标，不是对齐边界准确率。 + +| 分支 | OOF Accuracy | OOF Macro-F1 | OOF MAE | OOF RMSE | OOF Pearson | +|---|---:|---:|---:|---:|---:| +| B0 | 0.5900 | 0.3373 | 0.5345 | 0.7325 | 0.4255 | +| B1 | 0.5700 | 0.3084 | 0.5342 | 0.7444 | 0.3981 | +| B2 | 0.5500 | 0.2769 | 0.5308 | 0.7342 | 0.4232 | +| B3 | 0.5700 | 0.3084 | 0.5202 | 0.7371 | 0.4114 | +| B4 | 0.6000 | 0.3882 | 0.5393 | 0.7628 | 0.3413 | + +B4 的 Accuracy 与 Macro-F1 最高；B3 的 MAE 最低。分类与回归没有由同一分支同时取得最好结果。没有人工词边界真值，因此不报告边界误差或 CTC 后验经验校准率。完整折外预测、分折指标、Bootstrap 差值与运行参数见 [Q1/results/model_comparison_v2](Q1/results/model_comparison_v2/)。 + +## Q2：缺失鲁棒情感模型 + +Q2 使用附件二官方划分：训练集 3,395 条 / 1,528 个来源视频组，验证集 728 条 / 239 组，测试集 727 条 / 381 组；三份官方集合的来源视频组两两不重叠。结构化共享/私有状态空间补全器为 8 维共享状态加每模态 4 维私有状态；训练遮蔽率为 0、0.1、0.3、0.5、0.7，并比较 C0–C7 结构和三个单因素诊断。测试集仅用于最终一次评估。 + +### 验证集模型对照 + +下表为 `ablation_validation.csv` 中的 728 条验证样本结果。所有指标按原文件保留并四舍五入到 4 位小数；C0 是 Logistic/Ridge 基线，后续为结构消融及单因素诊断。 + +| 模型 | Accuracy | Macro-F1 | MAE | RMSE | Pearson | +|---|---:|---:|---:|---:|---:| +| C0 | 0.5920 | 0.5559 | 0.7334 | 0.9372 | 0.5192 | +| C1 | 0.6071 | 0.5512 | 0.6780 | 0.9222 | 0.5780 | +| C2 | 0.5975 | 0.4764 | 0.7159 | 0.9473 | 0.5797 | +| C3 | 0.6085 | 0.4974 | 0.7171 | 0.9520 | 0.5966 | +| C4 | 0.6085 | 0.5551 | 0.6918 | 0.9516 | 0.5685 | +| C5（最终选定） | 0.6154 | 0.5446 | 0.6624 | 0.8933 | 0.6174 | +| C6 | 0.6264 | 0.5801 | 0.6457 | 0.8814 | 0.6157 | +| C6 无距离/跨度惩罚 | 0.6044 | 0.5145 | 0.6795 | 0.9098 | 0.6046 | +| C6 无辅助重构 | 0.6003 | 0.5178 | 0.6957 | 0.9327 | 0.5887 | +| C6 点遮蔽 | 0.6030 | 0.5513 | 0.6945 | 0.9554 | 0.5647 | +| C7 仅蒸馏 | 0.5907 | 0.5244 | 0.6743 | 0.8981 | 0.6013 | +| C7 仅组风险 | 0.6085 | 0.5117 | 0.6860 | 0.9253 | 0.5912 | + +C6 在这组验证点指标中取得较高的 Accuracy、Macro-F1、MAE 和 RMSE；正式选择仍按论文实验流程中的验证选择损失执行，最终选择 C5。`ablation_validation.csv` 中 C5 的消融指标与正式导出的 `validation_metrics.json` 有小幅差异，下面正式验证结果按 JSON 原值报告；没有将两份文件的数值混合。 + +### C5 正式验证与测试结果 + +| 指标 | 官方验证集 | 官方测试集 | +|---|---:|---:| +| Accuracy | 0.6168 | 0.6740 | +| Macro-F1 | 0.5472 | 0.5861 | +| MAE | 0.6615 | 0.6980 | +| RMSE | 0.8930 | 0.9674 | +| Pearson | 0.6176 | 0.6300 | +| Brier | 0.4918 | 0.4409 | +| 分类 NLL | 0.8373 | 0.7614 | +| ECE（15 桶） | 0.0597 | 0.0499 | +| 90% 预测区间覆盖率 | 0.8929 | 0.8968 | +| 90% 预测区间平均宽度 | 2.3819 | 2.4824 | + +测试集类别支持数为负向 207、中性 158、正向 362；相应召回率为 0.7440、0.2089、0.8370。温度校准参数为 1.2127。测试集指标、预测、组 Bootstrap 区间及门控诊断见 [Q2/results](Q2/results/)。 + +### 连续缺失控制 + +验证集共执行 42 个固定缺失情景。C5 的归一化 AURC-MAE 及相对 C0 的差值如下；差值置信区间由来源视频组配对 Bootstrap 得到。 + +| 遮蔽模式 | C5 AURC-MAE | 相对 C0 差值 | 95% Bootstrap 区间 | +|---|---:|---:|---:| +| 单模态 | 0.6696 | -0.0758 | [-0.1118, -0.0389] | +| 同步 | 0.6890 | -0.0758 | [-0.1105, -0.0417] | +| 部分重叠 | 0.6883 | -0.0774 | [-0.1146, -0.0429] | +| 异步 | 0.6880 | -0.0894 | [-0.1261, -0.0554] | + +附件三有 30 条无标签样本，仅导出预测和审计，不计算 Accuracy 或 F1。`aligned_50.pkl` 没有逐行质量分数，因此按算法回退规则对可见行取 `q*=1, J_Q=0`；无人工边界或附件三标签的项目不报告虚构的监督指标。 + +## 主要结果文件 + +- Q1 五折模型对照：`Q1/results/model_comparison_v2/comparison_summary.csv`、`fold_metrics.csv`、`oof_predictions.csv`、`group_bootstrap_deltas.csv`。 +- Q1 特征文件与样本清单：`Q1/features_v2/`。 +- Q1 随机样本词到原始音频/视频位置图：`Q1/results/alignment_query_random_seed20260925.png`；重绘脚本为 `Q1/visualize_alignment.py`。 +- Q2 验证消融与正式指标：`Q2/results/ablation_validation.csv`、`validation_metrics.json`、`test_metrics.json`。 +- Q2 缺失控制与组区间：`Q2/results/controlled_missingness.csv`、`controlled_group_bootstrap.csv`、`group_bootstrap_ci.csv`。 +- Q2 附件三输出：`Q2/results/attachment3_predictions.csv`、`attachment3_audit.csv`。 diff --git a/math/Q1/README.md b/math/Q1/README.md index bfaada9..8888f1a 100644 --- a/math/Q1/README.md +++ b/math/Q1/README.md @@ -1,44 +1,40 @@ -# 问题一模型对比 +# Q1：模态对齐与特征分支 -本目录实现问题一 PDF 第 4.8.3 节的 B0–B4 单因素对照。代码从附件一的 100 条原始视频和标签表开始，先生成统一的文本、语音、视觉特征，再在 0.1 秒主时间网格上进行五折 `video_id` 留组评估。 +本目录按《E题V2》第四章构建 Q1 对齐特征。规格核对与限制见 [`V2_REVIEW.md`](V2_REVIEW.md)，可供后续训练读取的主特征包位于 `features_v2/`。 -## 运行 +## V2 特征包 -在仓库根目录执行： +- 100 个样本、300 条模态明细；主物理时间视图为 0.1 秒，并保留真实末段长度。 +- 文本采用冻结 BERT 词级特征；音频 74 维；视觉采用 OpenFace 2.2.0 的 35 维输出。 +- 原生词、音频窗、视频帧与源索引均保留；另提供逐词 CTC 后验、50 段相位视图、多尺度视图、B4 语音视图和物理时间查询矩阵。 +- 每个时间视图包含均值、方差、计数、逐维物理覆盖率、掩码和独立质量摘要。质量加权只影响特征汇聚，不改变物理覆盖率。 +- B4 Wav2Vec2 视图通过接口从本机 `cache/native/` 按需读取；不复制进主包。 +- 特征文件共 44,321,715 字节（约 42.27 MiB）。`feature_manifest.json` 记录配置哈希、源运行信息及精确字节数。 -```bash -cd math/Q1 -uv sync -uv run python compare_models.py +## 读取接口 + +```python +from q1_io import load_sample, get_view, csr_from_sample + +sample = load_sample("video_id/clip_id") +primary = get_view(sample, "audio", "sec") +multiscale = get_view(sample, "audio", "multi", context_s=0.3) +posterior_text = get_view(sample, "text", "posterior") +word_to_audio = csr_from_sample(sample, "query_word_audio_H_time") +b4_speech = get_view(sample, "speech", "sec") ``` -默认使用 CUDA（如果可用），需要可访问 Hugging Face 下载 BERT 与 Wav2Vec2 权重；MediaPipe Face Landmarker 权重会保存在 `math/Q1/cache/`。可用 `--device cpu` 指定 CPU。缓存保存在 `math/Q1/cache/native/`，中断后重跑会继续使用已完成样本。只有传入 `--force-extract` 才会重算全部原始特征。 +`get_view` 支持 `sec`、`word`、`phase50`、`multi` 和文本专用 `posterior`。多尺度视图从原生行按窗口重新聚合；`speech` 视图依赖本机原生缓存。清单文件为 `features_v2/manifest_q1.jsonl`、`sample_summary.csv` 和 `modality_summary.csv`。 -## 对照定义 +## 重建和五折探针 -- **B0**：冻结 BERT 词向量、冻结 CTC Viterbi 词边界、物理时间区间投影；训练折均值/标准差缩放。 -- **B1**：B0 加训练折中位数/MAD 稳健缩放，并对面部旋转使用 SO(3) 均值、对视线代理使用单位向量均值。 -- **B2**：B1 只替换文本时间投影，使用 CTC 固定转写状态图的前向–后向词占据后验。音频/视频的 PTS 不变。 -- **B3**：B1 加音频 log-F0/能量和面部 jaw-open/嘴部开合率的一、二阶时间增广路径签名。缺测处会断开路径。 -- **B4**：B1 加冻结 Wav2Vec2-base-960h 最后四层的时间投影表示。 +在仓库根目录运行： -每个模型以相同的五段时间池化探针评价极性和强度。分类器为固定 C=0.05 的逻辑回归，回归器为固定 alpha=25 的 Ridge；参数不按留出折调节。归一化器只使用训练折观测值。95% 差值区间以 `video_id` 为单位做 2,000 次配对 Bootstrap。 +```bash +uv run --project math/Q1 python math/Q1/build_v2.py +uv run --project math/Q1 python math/Q1/compare_v2.py +``` -文本维度为 768（BERT 最后四层、词内子词平均）；语音为 74 维（40 log-Mel、13 MFCC、13 ΔMFCC、8 韵律/谱量）；视觉为 35 维（17 个 MediaPipe blendshape 代理、6 维头姿、6 维近似视线、6 维面部比例几何）。MediaPipe blendshape 分数不等于 OpenFace AU 强度，视线为基于虹膜偏移的代理量；本次实现记录了实际所用索引与定义，没有将代理量称为 OpenFace 特征。 +特征重建依赖 `cache/native/`、`source_cache_manifest.json`、附件一视频及本机模型资源。`build_v2.py` 复用 `compare_models.py` 中的标签读取、缓存解析和数据结构；V2 对照入口是 `compare_v2.py`。B0–B4 五折 `video_id` 分组探针写入 `results/model_comparison_v2/`，每折缩放器只在训练视频组拟合；报告包含 Accuracy、Macro-F1、MAE、RMSE 和 Pearson。无人工词边界真值时，不报告边界误差或 CTC 后验校准率。 -硬边界质量由 CTC 发射分数得到，但不视为校准概率。聚合时按样本内有效词的中位分数归一化，并截断到 [0.25, 4]，仅作为相对质量权重。物理覆盖率仍以实际区间交叠计算。B2 的文本后验占据率是期望词活动质量，不能与物理覆盖率互换。 - -没有人工词边界标注，因此结果不报告边界误差、IoU/MATE 或后验经验校准率。情感探针分数只检查当前特征视图保留标签信息的程度，不是对齐正确性的真值。 - -## 结果文件 - -完整结果在 [`results/model_comparison/`](results/model_comparison/)： - -- `report.md`：实验设置、主要结果和限制。 -- `comparison_summary.csv`、`fold_metrics.csv`：总体和分折指标。 -- `group_bootstrap_deltas.csv`：相对 B1 的视频组配对 Bootstrap 区间。 -- `oof_predictions.csv`：100 条留组预测。 -- `sample_alignment_summary.csv`、`modality_summary.csv`：100 行样本汇总与 300 行模态明细。 -- `word_alignment_posterior.csv`：逐词硬边界、未校准对齐分数、实际相对质量权重与模型内部边界区间。 -- `split_assignments.csv`、`run_manifest.json`：折号、文件哈希、模型 revision、运行环境和参数。 -- `comparison.png`：OOF 指标图。 +词到原生音频窗和视频帧的 `H_time` 查询矩阵示例可用 `visualize_alignment.py` 重绘；默认展示样本 `-iRBcNs9oI8/8`，也可通过 `--sample-id` 指定样本。图与样本清单写入 `results/`。 diff --git a/math/Q1/V2_REVIEW.md b/math/Q1/V2_REVIEW.md new file mode 100644 index 0000000..228dee2 --- /dev/null +++ b/math/Q1/V2_REVIEW.md @@ -0,0 +1,46 @@ +# Q1 对《E题V2》第四章的复核 + +本复核只涉及 `math/Q1`。主特征包从本机 Q1 原生缓存构建；OpenFace 特征来自锁定的 OpenFace 2.2.0 运行包。没有读取 `deep_learning/`。标签只用于 B0–B4 五折信息探针，不参与特征抽取、CTC 对齐或质量计算。 + +## 规格核对 + +| PDF 要求 | 当前实现 | 结论 | +|---|---|---| +| 冻结 BERT 词级特征与长文本分窗 | BERT-base-uncased 冻结；每词对最后四层取均值，保存字符跨度和 WordPiece 映射；窗口 510 子词、步长 384 | 已实现 | +| 固定转写的单调 CTC 对齐 | 同一状态图保存 Viterbi 硬路径和 forward–backward 占据后验；词边界后验分位数随特征保留 | 已实现；没有人工边界真值时不报告边界准确率或后验经验校准率 | +| 74 维音频、逐分量有效性与真实范围 | 40 log-Mel、13 MFCC、13 局部线性 ΔMFCC、8 韵律/谱量；16 kHz、400 样本窗、160 步长、FFT 512；保存实际音频采样范围 | 已实现；F0 和有声概率取 `librosa.pyin`，HNR 在检测 F0 处由自相关另算并以 dB 保存 | +| 35 维 OpenFace 面部特征 | OpenFace 2.2.0 导出 17 个 AU 强度、Pose6、Gaze6、Geometry6；置信度门槛 0.8；保留原始 PTS 和帧索引 | 已实现；几何量依据 68 点标记计算 | +| 0.1 秒物理时间主网格、真实末段与分量掩码 | 原生区间交叠投影；每维保存均值、方差、计数、物理覆盖率和掩码；B0 均值可以按质量加权，覆盖率独立按真实交叠计算 | 已实现 | +| 几何一致的 B1 视觉汇聚 | 头部旋转使用 SO(3) 加权均值，视线使用单位向量均值；其他分量按物理区间汇聚 | 已实现，可由 `geometry_aware=True` 读取 | +| 相对进度、多尺度、B4 和词查询接口 | 提供 50 段相位视图、0.1/0.3/0.7 秒多尺度视图、按需 B4 Wav2Vec2 视图和词到原生音频/视频行的 CSR `H_time` | 已实现；B4 复用本机原生缓存以控制包体积 | +| B0–B4 单因素对照 | 五折 `video_id` GroupKFold；所有缩放器在每折训练组拟合；输出 OOF Accuracy、Macro-F1、MAE、RMSE、Pearson 与视频组 Bootstrap 差值 | 已完成，V2 结果见 `results/model_comparison_v2/` | + +## 记录的限制 + +1. `librosa.pyin` 的 `voiced_flag` 与 `voiced_prob` 分开保存；HNR 单独由 pYIN 检出的 F0 位置自相关周期性计算。pYIN 在 80 Hz 下界、25 ms 窗口会提示周期数不足，因此该范围内的 F0 需谨慎解释。字段语义未用周期强度冒称概率。 +2. CTC 边界后验未做经验校准。没有人工词边界标注，故不能声称边界精度、IoU/MATE 或校准率；后验宽度只作为模型内部不确定性摘要。 +3. `q1_io.get_view(sample, "speech", "sec")` 从本机 B4 原生缓存读取 Wav2Vec2 特征，不复制到主包。换机器若没有该缓存，需按清单重建 B4 特征。 +4. B6 内容相似度探针关闭。主包保留的是物理时间查询矩阵，避免把内容相似误作时间对齐证据。 + +## 当前 V2 五折探针 + +100 条样本按 37 个来源 `video_id` 分组。表中 Accuracy 是 100 条折外预测的正确率；Macro-F1 是 Negative、Neutral、Positive 三类 F1 的等权平均。两者都是情感信息探针，不是对齐边界准确率。 + +| 分支 | OOF Accuracy | OOF Macro-F1 | OOF MAE | OOF RMSE | OOF Pearson | +|---|---:|---:|---:|---:|---:| +| B0 | 0.5900 | 0.3373 | 0.5345 | 0.7325 | 0.4255 | +| B1 | 0.5700 | 0.3084 | 0.5342 | 0.7444 | 0.3981 | +| B2 | 0.5500 | 0.2769 | 0.5308 | 0.7342 | 0.4232 | +| B3 | 0.5700 | 0.3084 | 0.5202 | 0.7371 | 0.4114 | +| B4 | 0.6000 | 0.3882 | 0.5393 | 0.7628 | 0.3413 | + +Macro-F1 最高的是 B4，MAE 最低的是 B3；没有单一分支同时在分类与回归上占优。`comparison_summary.csv` 同时包含总体 OOF Accuracy 和逐折 Accuracy 均值/标准差。逐样本硬对齐词数和未定位词数见 `features_v2/sample_summary.csv`。 + +## 特征包审计 + +- 100 个 NPZ 样本、100 行样本汇总、300 行模态明细；总文件字节数 44,321,715（约 42.27 MiB）。 +- `feature_manifest.json` 记录实际配置哈希、输入缓存来源、模型版本、包体积和各分支状态；每个样本均有对应配置哈希。 +- 无穷/NaN 检查、OpenFace 样本提取、真实音频末帧范围、视觉原生帧索引与五折分组结果均已核对。 +- 缺失边界用数值 `-1` 与 JSON `null` 表示；无证据的边界不被伪造成零秒。 + +完整 OOF 指标、折号、预测、Bootstrap 区间和运行参数保存在 `results/model_comparison_v2/`。构建特征时读取的原生缓存来源信息单独保存在 `source_cache_manifest.json`。 diff --git a/math/Q1/build_v2.py b/math/Q1/build_v2.py new file mode 100644 index 0000000..d11e014 --- /dev/null +++ b/math/Q1/build_v2.py @@ -0,0 +1,404 @@ +from __future__ import annotations + +import csv +import hashlib +import json +import subprocess +import sys +from dataclasses import replace +from pathlib import Path +from typing import Any + +import numpy as np +from scipy import sparse + +ROOT = Path(__file__).resolve().parents[2] +Q1 = Path(__file__).resolve().parent +sys.path.insert(0, str(Q1)) +import compare_models as cm # noqa: E402 + +CACHE = Q1 / "cache" / "native" +RUN = Q1 / "source_cache_manifest.json" +LABELS = cm.LABEL_FILE +OUT = Q1 / "features_v2" +MODALITIES = ("text", "audio", "vision") +CONFIG = { + "schema": "q1-v2-source-first-2026-09", + "source_cache_schema": "q1-b0b4-v4-openface", + "common_step_s": 0.1, + "multi_context_windows_s": [0.1, 0.3, 0.7], + "relative_progress_bins": 50, + "text_encoder": "google-bert/bert-base-uncased; frozen last-four-layer mean per whitespace word; window=510, stride=384", + "alignment": "fixed-transcript CTC monotone state graph; hard Viterbi path plus stored forward-backward occupancy; scores uncalibrated", + "audio": "74-D: 40 log-Mel + 13 MFCC + 13 two-sided local-linear delta MFCC + [log-energy, log-F0, librosa.pyin voiced probability, spectral centroid, bandwidth, flux, zero-crossing rate, HNR dB]; 16 kHz, 400-sample window, 160-sample hop, FFT 512; HNR autocorrelation uses n=1024 at detected F0; preserve per-field validity; librosa.pyin warns cycle support is short at fmin=80 Hz for a 25 ms frame", + "vision": "OpenFace 2.2.0 native-frame output: 17 AU intensities, Pose6, Gaze6, Geometry6; confidence threshold 0.8; actual frame PTS and indices retained", + "quality": "B0 uses raw CTC word-path score in [0,1]; unavailable quality falls back to q*=1 and is flagged; audio/vision retain explicit unknown or detector-confidence states", + "content_probe": "disabled; physical time/query maps remain separate from content similarity", + "time": "left-closed/right-open seconds relative to video stream origin; source indices retained", + "branch_states": {"sec": "primary B0 view and materialized", "B1_vision_geometry": "geometry-aware 0.1 s view materialized", "word": "materialized", "phase50": "materialized", "multi": "derived from native rows on demand by q1_io", "posterior": "native CTC posterior stored; sec projection available through q1_io", "dynamics": "materialized if continuous support is sufficient", "b4_speech": "source-cache-backed on demand through q1_io to stay within the 50 MiB feature-package cap", "query_word": "physical H_time matrices materialized", "content_probe": "disabled"}, +} + + +def digest(path: Path) -> str: + h = hashlib.sha256() + with path.open("rb") as f: + for block in iter(lambda: f.read(1024 * 1024), b""): + h.update(block) + return h.hexdigest() + + +def finite_boundary_summary(rows: list[dict[str, float]], offset: float, end_s: float) -> tuple[np.ndarray, str]: + values=[] + json_rows=[] + for row in rows: + vals=[row.get("start_p05_s",np.nan)+offset,row.get("start_p95_s",np.nan)+offset,row.get("end_p05_s",np.nan)+offset,row.get("end_p95_s",np.nan)+offset] + vals=[float(np.clip(v,0.0,end_s)) if np.isfinite(v) else np.nan for v in vals] + values.append([v if np.isfinite(v) else -1.0 for v in vals]) + absolute_fields={"start_mean_s","end_mean_s","start_p05_s","start_p95_s","end_p05_s","end_p95_s"} + json_rows.append({k:(float(np.clip(v+offset,0.0,end_s)) if np.isfinite(v) and k in absolute_fields else (float(v) if np.isfinite(v) else None)) for k,v in row.items()}) + return np.asarray(values,np.float32),json.dumps(json_rows,ensure_ascii=False) + + +def audio_sample_count_from_quality(sample: cm.Sample) -> int: + """The final partial 25 ms frame records its exact decoded sample fraction.""" + valid=np.flatnonzero(np.asarray(sample.audio_quality)>0) + if not len(valid): + return 0 + index=int(valid[-1]) + fraction=float(np.clip(sample.audio_quality[index],0.0,1.0)) + return index*cm.FRAME_STEP+int(round(fraction*cm.FRAME_LENGTH)) + + +def effective_text_quality(raw: np.ndarray, valid: np.ndarray) -> tuple[np.ndarray, np.ndarray]: + """Use bounded raw CTC scores; q*=1 means no extra discount when unavailable.""" + raw = np.asarray(raw, np.float32) + available = np.asarray(valid, bool) & (raw > 0) & np.isfinite(raw) + effective = np.ones(len(raw), np.float32) + effective[available] = np.clip(raw[available], 0.0, 1.0) + return effective, available + + +def intervals_from_times(times: np.ndarray, duration: float, step: float, gap_factor: float = 1.5) -> np.ndarray: + times = np.asarray(times, dtype=np.float64) + if not len(times): + return np.empty((0, 2), np.float32) + starts = np.empty(len(times), dtype=np.float64) + ends = np.empty(len(times), dtype=np.float64) + breaks = np.diff(times) > gap_factor * step + for i, t in enumerate(times): + starts[i] = (times[i - 1] + t) / 2 if i and not breaks[i - 1] else max(0.0, t - step / 2) + ends[i] = (t + times[i + 1]) / 2 if i + 1 < len(times) and not breaks[i] else min(duration, t + step / 2) + if starts[0] <= step: + starts[0] = 0.0 + if ends[-1] >= duration - step: + ends[-1] = duration + starts = np.clip(starts, 0.0, duration) + ends = np.clip(ends, 0.0, duration) + return np.column_stack((starts, np.maximum(starts, ends))).astype(np.float32) + + +def probe_media(path: Path) -> dict[str, Any]: + command = ["ffprobe", "-v", "error", "-show_entries", "format=start_time,duration:stream=codec_type,start_time,time_base,sample_rate,avg_frame_rate", "-of", "json", str(path)] + try: + obj = json.loads(subprocess.run(command, check=True, capture_output=True, text=True).stdout) + streams = obj.get("streams", []) + fmt = obj.get("format", {}) + vs = next((s for s in streams if s.get("codec_type") == "video"), {}) + aus = next((s for s in streams if s.get("codec_type") == "audio"), {}) + v0 = float(vs.get("start_time", fmt.get("start_time", 0)) or 0) + a0 = float(aus.get("start_time", fmt.get("start_time", 0)) or 0) + return {"format_start_s": float(fmt.get("start_time", 0) or 0), "format_duration_s": float(fmt.get("duration", 0) or 0), "video_start_s": v0, "audio_start_s": a0, "audio_offset_from_video_s": a0 - v0, "video_time_base": vs.get("time_base"), "audio_time_base": aus.get("time_base"), "audio_sample_rate": aus.get("sample_rate"), "avg_frame_rate": vs.get("avg_frame_rate"), "status": "ok"} + except Exception as exc: + return {"format_start_s": 0.0, "format_duration_s": 0.0, "video_start_s": 0.0, "audio_start_s": 0.0, "audio_offset_from_video_s": 0.0, "status": f"ffprobe_error:{type(exc).__name__}"} + + +def aggregate(values: np.ndarray, observed: np.ndarray, source_intervals: np.ndarray, quality: np.ndarray, edges: np.ndarray, quality_available: np.ndarray | None = None) -> dict[str, np.ndarray]: + values = np.asarray(values, np.float64) + observed = np.asarray(observed, bool) + source_intervals = np.asarray(source_intervals, np.float64) + quality = np.maximum(0.0, np.asarray(quality, np.float64)) + quality_available = np.zeros(len(values), dtype=bool) if quality_available is None else np.asarray(quality_available, dtype=bool) + n, d = len(edges) - 1, values.shape[1] + mean = np.zeros((n, d), np.float32) + var = np.zeros((n, d), np.float32) + count = np.zeros((n, d), np.uint8) + coverage = np.zeros((n, d), np.float32) + qbar = np.ones((n, d), np.float32) + qavail = np.zeros((n, d), np.float32) + mask = np.zeros((n, d), bool) + for i, (left, right) in enumerate(zip(edges[:-1], edges[1:])): + if right <= left or not len(source_intervals): + continue + overlap = np.maximum(0.0, np.minimum(source_intervals[:, 1], right) - np.maximum(source_intervals[:, 0], left)) + phys = overlap[:, None] * observed + w = phys * quality[:, None] + wsum = w.sum(axis=0) + good = wsum > 0 + if good.any(): + sx = (values * w).sum(axis=0) + sx2 = (np.square(values) * w).sum(axis=0) + mean[i, good] = (sx[good] / wsum[good]).astype(np.float32) + var[i, good] = np.maximum(0.0, sx2[good] / wsum[good] - mean[i, good].astype(np.float64) ** 2).astype(np.float32) + mask[i, good] = True + coverage[i] = np.minimum(1.0, phys.sum(axis=0) / (right - left)).astype(np.float32) + count[i] = np.minimum(255, ((overlap[:, None] > 0) & observed).sum(axis=0)).astype(np.uint8) + base = phys.sum(axis=0) + valid = base > 0 + qbar[i, valid] = ((phys * quality[:, None]).sum(axis=0)[valid] / base[valid]).astype(np.float32) + qavail[i, valid] = ((phys * quality_available[:, None]).sum(axis=0)[valid] / base[valid]).astype(np.float32) + # Audio HNR/prosodic rows can have genuinely large within-window variance; + # retain variance in float32 rather than silently overflowing float16. + return {"x": mean.astype(np.float16), "var": var.astype(np.float32), "count": count, "coverage_u8": np.rint(coverage * 255).astype(np.uint8), "mask": mask, "qbar": qbar.astype(np.float16), "quality_available_fraction": qavail.astype(np.float16)} + + +def sparse_overlap(source_intervals: np.ndarray, target_intervals: np.ndarray, quality: np.ndarray | None = None) -> sparse.csr_matrix: + rows, cols, vals = [], [], [] + q = np.ones(len(source_intervals), np.float32) if quality is None else np.asarray(quality, np.float32) + for i, (left, right) in enumerate(target_intervals): + overlap = np.maximum(0.0, np.minimum(source_intervals[:, 1], right) - np.maximum(source_intervals[:, 0], left)) * q + js = np.flatnonzero(overlap > 0) + rows.extend([i] * len(js)); cols.extend(js.tolist()); vals.extend(overlap[js].tolist()) + return sparse.csr_matrix((np.asarray(vals, np.float32), (rows, cols)), shape=(len(target_intervals), len(source_intervals))) + + +def sparse_word_map(word_intervals: np.ndarray, source_intervals: np.ndarray, chi: np.ndarray) -> sparse.csr_matrix: + rows, cols, vals = [], [], [] + for k, (left, right) in enumerate(word_intervals): + if right <= left: + continue + overlap = np.maximum(0.0, np.minimum(source_intervals[:, 1], right) - np.maximum(source_intervals[:, 0], left)) * chi + js = np.flatnonzero(overlap > 0) + total = float(overlap[js].sum()) + if total > 0: + rows.extend([k] * len(js)); cols.extend(js.tolist()); vals.extend((overlap[js] / total).tolist()) + return sparse.csr_matrix((np.asarray(vals, np.float32), (rows, cols)), shape=(len(word_intervals), len(source_intervals))) + + +def pack_csr(arrays: dict[str, Any], prefix: str, matrix: sparse.csr_matrix) -> None: + arrays[prefix + "_data"] = matrix.data.astype(np.float16) + arrays[prefix + "_indices"] = matrix.indices.astype(np.int32) + arrays[prefix + "_indptr"] = matrix.indptr.astype(np.int32) + arrays[prefix + "_shape"] = np.asarray(matrix.shape, np.int32) + + +def text_provenance(record: dict[str, Any], words: list[str], tokenizer: Any) -> tuple[np.ndarray, np.ndarray, np.ndarray]: + text = record["text"] + spans = np.full((len(words), 2), -1, np.int32) + subword = np.zeros((len(words), 2), np.int32) + all_ids: list[int] = [] + cursor = 0 + for i, word in enumerate(words): + start = text.find(word, cursor) + if start >= 0: + spans[i] = (start, start + len(word)); cursor = start + len(word) + ids = tokenizer(word, add_special_tokens=False)["input_ids"] if tokenizer is not None else [] + subword[i] = (len(all_ids), len(all_ids) + len(ids)) + all_ids.extend(int(v) for v in ids) + return spans, subword, np.asarray(all_ids, np.int32) + + +def make_dynamics(sample: cm.Sample, audio_intervals: np.ndarray, vision_intervals: np.ndarray, edges: np.ndarray) -> tuple[np.ndarray, np.ndarray, np.ndarray]: + # Time-augmented level-2 log-signature on continuous 0.7 s contexts; this is auxiliary only. + names = [("audio", 67, 66), ("vision", 10, 31)] + output = np.zeros((len(edges)-1, 2, 6), np.float32) + valid = np.zeros((len(edges)-1, 2), bool) + bounds = np.zeros((len(edges)-1, 2, 2), np.float32) + for t,(l,r) in enumerate(zip(edges[:-1],edges[1:])): + center=(l+r)/2 + a=max(0.0,center-0.35); b=min(sample.duration_s,center+0.35) + bounds[t,:,:]=[a,b] + for branch,(mod,j,k) in enumerate(names): + if mod=="audio": + times=sample.audio_times; x=sample.audio_features.astype(np.float32); mask=sample.audio_observed + ints=audio_intervals; required=mask[:,[j,k]].all(axis=1) + else: + times=sample.vision_times; x=sample.vision_features.astype(np.float32); mask=sample.vision_observed + ints=vision_intervals; required=mask[:,[j,k]].all(axis=1) + ix=np.flatnonzero((ints[:,0]>=a-1e-7)&(ints[:,1]<=b+1e-7)&required) + if len(ix)<3: continue + # Break the path at missing or unusually long source gaps. + expected=0.01 if mod=="audio" else max(float(np.median(np.diff(times))),1e-6) + if np.any(np.diff(times[ix])>1.5*expected): continue + vals=np.column_stack(((times[ix]-a)/max(b-a,1e-6),x[ix,j],x[ix,k])).astype(np.float64) + dz=np.diff(vals,axis=0) + first=dz.sum(axis=0) + area=np.zeros(3,np.float64); pairs=((0,1),(0,2),(1,2)) + for p,(u,v) in enumerate(pairs): + area[p]=0.5*sum(dz[a0,u]*dz[b0,v]-dz[a0,v]*dz[b0,u] for a0 in range(len(dz)) for b0 in range(a0+1,len(dz))) + output[t,branch]=np.concatenate((first,area)).astype(np.float32) + valid[t,branch]=True + return output.astype(np.float16),valid,bounds + + +def geometry_aware_vision(sample: cm.Sample, intervals: np.ndarray, bounds: np.ndarray, base: dict[str, np.ndarray]) -> tuple[np.ndarray, np.ndarray]: + """B1 SO(3) mean for head pose and unit-vector means for gaze channels.""" + values = base["x"].astype(np.float32).copy() + masks = base["mask"].astype(bool).copy() + raw = sample.vision_features.astype(np.float32) + observed = sample.vision_observed + for target_index, (left, right) in enumerate(bounds): + overlap = np.maximum(0.0, np.minimum(intervals[:, 1], right) - np.maximum(intervals[:, 0], left)) + weighted_overlap=overlap*sample.vision_quality + pose_rows = (weighted_overlap > 0) & observed[:, 17:20].all(axis=1) + if pose_rows.any(): + mean_rot = cm._so3_weighted_mean(raw[pose_rows, 17:20], weighted_overlap[pose_rows]) + if mean_rot is not None: + values[target_index, 17:20] = mean_rot + masks[target_index, 17:20] = True + for start in (23, 26): + rows = (weighted_overlap > 0) & observed[:, start:start + 3].all(axis=1) + if not rows.any(): + continue + mean = np.average(raw[rows, start:start + 3], axis=0, weights=weighted_overlap[rows]) + norm = float(np.linalg.norm(mean)) + if norm > 1e-6: + values[target_index, start:start + 3] = mean / norm + masks[target_index, start:start + 3] = True + else: + values[target_index, start:start + 3] = 0.0 + masks[target_index, start:start + 3] = False + return values.astype(np.float16), masks + + +def main() -> None: + if not CACHE.is_dir() or not RUN.is_file(): + raise FileNotFoundError("Existing Q1 native cache and run manifest are required") + OUT.mkdir(parents=True, exist_ok=True) + run = json.loads(RUN.read_text(encoding="utf-8")) + records = cm._read_labels(LABELS) + if len(records) != 100: + raise ValueError(f"expected 100 attachment-1 rows, got {len(records)}") + tokenizer = None + try: + tokenizer = cm.AutoTokenizer.from_pretrained(cm.TEXT_MODEL_ID, use_fast=True, local_files_only=True) + except Exception: + pass + config_text = json.dumps(CONFIG, ensure_ascii=False, sort_keys=True, separators=(",", ":")) + config_hash = hashlib.sha256(config_text.encode("utf-8")).hexdigest() + grid_rows: list[dict[str, Any]] = [] + sample_rows: list[dict[str, Any]] = [] + manifest_lines: list[dict[str, Any]] = [] + for record in records: + sid=record["sample_id"] + source_hash=run["inputs"]["video_sha256_by_sample"][sid] + cache=CACHE/f"{cm._safe_name(record['video_id'])}__{cm._safe_name(record['clip_id'])}.npz" + sample=cm._load_cache(cache,record,source_hash,"q1-b0b4-v4-openface") + video_path=cm.DATA_DIR/record["video_id"]/f"{record['clip_id']}.mp4" + media=probe_media(video_path) + audio_offset=float(media.get("audio_offset_from_video_s",0.0)) + sample_count=audio_sample_count_from_quality(sample) + audio_end_s=float(np.clip(audio_offset+sample_count/cm.SAMPLE_RATE,0.0,sample.duration_s)) + audio_times=sample.audio_times.astype(np.float32)+audio_offset + ctc_times=sample.ctc_times.astype(np.float32)+audio_offset + hard=sample.hard_intervals.astype(np.float32).copy()+np.float32(audio_offset) + hard=np.clip(hard,0.0,audio_end_s) + hard_valid=sample.hard_valid & (hard[:,1]>hard[:,0]) + text_intervals=np.where(hard_valid[:,None],hard,0.0) + audio_starts=np.arange(len(audio_times),dtype=np.int64)*cm.FRAME_STEP + audio_ranges=np.column_stack((audio_starts,np.minimum(audio_starts+cm.FRAME_LENGTH,sample_count))).astype(np.int32) + audio_intervals=intervals_from_times(audio_times,audio_end_s,cm.FRAME_STEP/cm.SAMPLE_RATE) + audio_intervals=np.clip(audio_intervals,0.0,sample.duration_s) + video_step=float(np.median(np.diff(sample.vision_times))) if len(sample.vision_times)>1 else 1.0/30.0 + vision_intervals=intervals_from_times(sample.vision_times,sample.duration_s,video_step) + frame_indices=sample.vision_frame_indices.astype(np.int32) + words=sample.text_words + char_spans,subword_spans,subword_ids=text_provenance(record,words,tokenizer) + duration=sample.duration_s + sec_edges=cm._grid_edges(duration) + sec_bounds=np.column_stack((sec_edges[:-1],sec_edges[1:])).astype(np.float32) + phase_edges=np.linspace(0.0,duration,51,dtype=np.float64) + phase_bounds=np.column_stack((phase_edges[:-1],phase_edges[1:])).astype(np.float32) + word_bounds=text_intervals.copy() + # Keep the media timestamps in the video-origin timebase for dynamics too. + sample.audio_times = audio_times + text_quality, text_quality_available = effective_text_quality(sample.hard_quality, hard_valid) + source={ + "text":(sample.text_features.astype(np.float32),np.broadcast_to(sample.text_valid[:,None],sample.text_features.shape).copy(),text_intervals,text_quality,text_quality_available), + "audio":(sample.audio_features.astype(np.float32),sample.audio_observed,audio_intervals,sample.audio_quality,sample.audio_quality_available), + "vision":(sample.vision_features.astype(np.float32),sample.vision_observed,vision_intervals,sample.vision_quality,sample.vision_quality_available), + } + sec={name:aggregate(source[name][0],source[name][1],source[name][2],source[name][3],sec_edges,source[name][4]) for name in MODALITIES} + phase={name:aggregate(source[name][0],source[name][1],source[name][2],source[name][3],phase_edges,source[name][4]) for name in MODALITIES} + vision_b1_x,vision_b1_mask=geometry_aware_vision(sample,vision_intervals,sec_bounds,sec["vision"]) + + # Word-level physical correspondence and query matrices. + word_views={} + for name in MODALITIES: + result={k:[] for k in ("x","var","count","coverage_u8","mask","qbar","quality_available_fraction")} + for aa,bb in word_bounds: + v=aggregate(source[name][0],source[name][1],source[name][2],source[name][3],np.asarray([aa,bb],np.float64),source[name][4]) + for k in result: result[k].append(v[k][0]) + word_views[name]={k:np.asarray(v) for k,v in result.items()} + # Sparse target-to-native overlap maps for the primary physical view. + maps={name:sparse_overlap(source[name][2],sec_bounds) for name in MODALITIES} + # Query channels are fixed for display only: acoustic log-energy and OpenFace AU12. + h_audio=sparse_word_map(word_bounds,audio_intervals,sample.audio_observed[:,66].astype(np.float32)) + h_vision=sparse_word_map(word_bounds,vision_intervals,sample.vision_observed[:,10].astype(np.float32)) + dyn,dyn_valid,dyn_bounds=make_dynamics(sample,audio_intervals,vision_intervals,sec_edges) + delta_centers=np.arange(len(audio_times),dtype=np.int64) + delta_left=np.maximum(0,delta_centers-2)*cm.FRAME_STEP + delta_right=np.minimum(sample_count,np.minimum(len(audio_times)-1,delta_centers+2)*cm.FRAME_STEP+cm.FRAME_LENGTH) + delta_ranges=np.column_stack((delta_left,delta_right)).astype(np.int32) + boundary_p05_p95,boundary_summary_json=finite_boundary_summary(sample.boundary_summary,audio_offset,audio_end_s) + cache_file=OUT/f"{cm._safe_name(record['video_id'])}__{cm._safe_name(record['clip_id'])}.npz" + payload:dict[str,Any]={ + "meta_json":np.asarray(json.dumps({"sample_id":sid,"video_id":record["video_id"],"clip_id":record["clip_id"],"duration_s":duration,"sentiment":sample.sentiment,"polarity":sample.polarity,"annotation":record["annotation"],"source_video_sha256":source_hash,"media":media,"config_hash":config_hash,"vision_backend":"OpenFace 2.2.0 FeatureExtraction","quality_available":{"text":bool(text_quality_available.any()),"audio":bool(sample.audio_quality_available.any()),"vision":bool(sample.vision_quality_available.any())}},ensure_ascii=False)), + "native_text_words":np.asarray(words,dtype=str),"native_text_features":sample.text_features.astype(np.float16),"native_text_observed":sample.text_valid.astype(bool),"native_text_intervals":text_intervals.astype(np.float32),"native_text_hard_quality_uncalibrated":sample.hard_quality.astype(np.float16),"native_text_quality_effective":text_quality.astype(np.float16),"native_text_quality_available":text_quality_available,"native_text_boundary_p05_p95":boundary_p05_p95,"native_text_char_spans":char_spans,"native_text_subword_spans":subword_spans,"native_text_subword_ids":subword_ids, + "native_audio_times":audio_times,"native_audio_features":sample.audio_features.astype(np.float16),"native_audio_mask":sample.audio_observed.astype(bool),"native_audio_quality":sample.audio_quality.astype(np.float16),"native_audio_quality_available":sample.audio_quality_available.astype(bool),"native_audio_source_range_samples":audio_ranges,"native_audio_delta_calc_range_samples":delta_ranges,"native_audio_intervals":audio_intervals, + "native_vision_times":sample.vision_times.astype(np.float32),"native_vision_features":sample.vision_features.astype(np.float16),"native_vision_mask":sample.vision_observed.astype(bool),"native_vision_quality":sample.vision_quality.astype(np.float16),"native_vision_quality_available":sample.vision_quality_available.astype(bool),"native_vision_frame_index":frame_indices,"native_vision_intervals":vision_intervals, + "native_ctc_times":ctc_times,"native_ctc_occupancy":sample.ctc_occupancy.astype(np.float16),"native_ctc_boundary_summary_json":np.asarray(boundary_summary_json), + "views_sec_time_bounds_s":sec_bounds,"views_phase50_time_bounds_s":phase_bounds,"views_word_time_bounds_s":word_bounds, + "views_sec_vision_b1_x":vision_b1_x,"views_sec_vision_b1_mask":vision_b1_mask, + "views_dynamics_x":dyn,"views_dynamics_mask":dyn_valid,"views_dynamics_time_bounds_s":dyn_bounds, + } + for name in MODALITIES: + for k,v in sec[name].items(): payload[f"views_sec_{name}_{k}"]=v + for k,v in phase[name].items(): payload[f"views_phase50_{name}_{k}"]=v + for k,v in word_views[name].items(): payload[f"views_word_{name}_{k}"]=v + pack_csr(payload,f"alignment_map_{name}",maps[name]) + pack_csr(payload,"query_word_audio_H_time",h_audio) + pack_csr(payload,"query_word_vision_H_time",h_vision) + np.savez_compressed(cache_file,**payload) + feature_hash=digest(cache_file) + observed_summary={} + for name in MODALITIES: + vals,mask,ints,q,q_available=source[name] + support=np.zeros(mask.shape[1],np.float64) + for r,(a,b) in enumerate(ints): + support += max(0.0,float(b-a))*mask[r]*(q[r]>0) + coverage=np.clip(support/max(duration,1e-9),0,1) + observed_summary[name]={"observed_duration_mean_s":float(np.mean(coverage)*duration),"mean_coverage":float(np.mean(coverage)),"row_count":int(len(vals)),"dimension":int(vals.shape[1]),"quality_available":bool(q_available.any()),"quality_available_fraction":float(q_available.mean()) if len(q_available) else 0.0} + gran={"text":"word-level, variable duration; fixed-transcript CTC source interval","audio":"native 10 ms feature step; 25 ms windows; context ranges retained separately","vision":"native OpenFace frame timestamps and frame indices"}[name] + unobserved_rows=int((~mask.any(axis=1)).sum()) if len(mask) else 0 + if name=="text": + missing_reason=f"{int((~hard_valid).sum())} word intervals are not reliable under the fixed-transcript CTC path" if (~hard_valid).any() else "none" + elif name=="audio": + undefined_pitch=int((~mask[:,67]).sum()) if mask.shape[1]>67 else 0 + missing_reason=f"F0/HNR naturally undefined or unavailable in {undefined_pitch} rows; support masks retained" + else: + missing_reason=f"OpenFace confidence/success gate rejected {unobserved_rows} native frames" if unobserved_rows else "none" + grid_rows.append({"sample_id":sid,"video_id":record["video_id"],"clip_id":record["clip_id"],"modality":name,"source_duration_s":duration,"observed_duration_s":observed_summary[name]["observed_duration_mean_s"],"native_length":len(vals),"native_dim":vals.shape[1],"aligned_length":len(sec_bounds),"aligned_dim":vals.shape[1],"alignment_type":"fixed 0.1 s physical grid; direct native interval projection","granularity":gran,"mean_coverage":observed_summary[name]["mean_coverage"],"missing_reason":missing_reason,"quality_available":observed_summary[name]["quality_available"],"quality_available_fraction":observed_summary[name]["quality_available_fraction"],"quality_path":f"{cache_file.name}::native_{name}_*quality*","query_map_path":f"{cache_file.name}::query_word_{name}_H_time" if name in ("audio","vision") else "not_applicable","probe_status":"content probe disabled" if name in ("audio","vision") else "not_applicable","feature_path":str(cache_file.relative_to(Q1)),"source_hash":source_hash,"status":"success" if mask.any() else "failed_or_unavailable","config_hash":config_hash}) + sample_status="success" if all(source[m][1].any() for m in MODALITIES) else "partial" + sample_rows.append({"sample_id":sid,"video_id":record["video_id"],"clip_id":record["clip_id"],"source_duration_s":duration,"source_video_sha256":source_hash,"feature_path":str(cache_file.relative_to(Q1)),"feature_sha256":feature_hash,"sec_length":len(sec_bounds),"word_count":len(words),"hard_aligned_word_count":int(hard_valid.sum()),"unlocated_word_count":int((~hard_valid).sum()),"status":sample_status,"config_hash":config_hash}) + manifest_lines.append({"sample_id":sid,"video_id":record["video_id"],"clip_id":record["clip_id"],"feature_path":str(cache_file.relative_to(Q1)),"source_video_sha256":source_hash,"feature_sha256":feature_hash,"duration_s":duration,"status":sample_rows[-1]["status"],"config_hash":config_hash}) + print(f"{sid}: {len(words)} words, {len(sec_bounds)} sec steps, {cache_file.stat().st_size/1024:.1f} KiB") + + def write_csv(path:Path,rows:list[dict[str,Any]])->None: + with path.open("w",encoding="utf-8-sig",newline="") as f: + w=csv.DictWriter(f,fieldnames=list(rows[0]));w.writeheader();w.writerows(rows) + write_csv(OUT/"sample_summary.csv",sample_rows) + write_csv(OUT/"modality_summary.csv",grid_rows) + (OUT/"manifest_q1.jsonl").write_text("\n".join(json.dumps(x,ensure_ascii=False) for x in manifest_lines)+"\n",encoding="utf-8") + configuration={"config":CONFIG,"config_hash":config_hash,"source_run_manifest":RUN.relative_to(Q1).as_posix(),"source_cache_schema":"q1-b0b4-v4-openface","source_label_sha256":digest(LABELS),"python":run.get("python"),"packages":run.get("packages",{}),"models":run.get("models",{}),"samples":len(records),"modalities":300,"total_bytes":sum(p.stat().st_size for p in OUT.iterdir() if p.is_file())} + (OUT/"feature_manifest.json").write_text(json.dumps(configuration,ensure_ascii=False,indent=2),encoding="utf-8") + median_sample=sorted(sample_rows,key=lambda x:x["source_duration_s"])[len(sample_rows)//2] + with np.load(Q1/median_sample["feature_path"],allow_pickle=False) as d: + k=int(min(5,len(d["native_text_words"])-1)); sid=median_sample["sample_id"] + card={"sample_id":sid,"source_video_sha256":median_sample["source_video_sha256"],"duration_s":median_sample["source_duration_s"],"word":str(d["native_text_words"][k]),"word_char_span":d["native_text_char_spans"][k].tolist(),"hard_interval_s":d["native_text_intervals"][k].tolist(),"boundary_interval_90_s":d["native_text_boundary_p05_p95"][k].tolist(),"audio_source_rows":sparse.csr_matrix((d["query_word_audio_H_time_data"].astype(np.float32),d["query_word_audio_H_time_indices"],d["query_word_audio_H_time_indptr"]),shape=tuple(d["query_word_audio_H_time_shape"])).getrow(k).indices.tolist(),"vision_source_rows":sparse.csr_matrix((d["query_word_vision_H_time_data"].astype(np.float32),d["query_word_vision_H_time_indices"],d["query_word_vision_H_time_indptr"]),shape=tuple(d["query_word_vision_H_time_shape"])).getrow(k).indices.tolist(),"manual_boundary_audit":"not available; no empirical boundary error or calibration claimed","vision_backend":"OpenFace 2.2.0"} + (OUT/"typical_alignment_card.json").write_text(json.dumps(card,ensure_ascii=False,indent=2),encoding="utf-8") + configuration["total_bytes"]=sum(p.stat().st_size for p in OUT.rglob("*") if p.is_file()) + (OUT/"feature_manifest.json").write_text(json.dumps(configuration,ensure_ascii=False,indent=2),encoding="utf-8") + print(f"Wrote {len(sample_rows)} samples and {len(grid_rows)} modality rows; total {configuration['total_bytes']/1024**2:.2f} MiB") + +if __name__=="__main__": + main() diff --git a/math/Q1/compare_models.py b/math/Q1/compare_models.py index f813c0e..b04aeda 100644 --- a/math/Q1/compare_models.py +++ b/math/Q1/compare_models.py @@ -6,22 +6,23 @@ import hashlib import importlib.metadata import json import math +import os import platform import re +import shutil import subprocess import sys import time -import urllib.request from dataclasses import dataclass from pathlib import Path from typing import Any, Iterable import cv2 +import librosa import matplotlib matplotlib.use("Agg") import matplotlib.pyplot as plt -import mediapipe as mp import numpy as np import torch from openpyxl import load_workbook @@ -39,7 +40,8 @@ DATA_DIR = ROOT / "E题数据" / "附件1-数据集原始多模态样本" / "MOS LABEL_FILE = DATA_DIR / "label-100.xlsx" OUTPUT_DIR = MATH_DIR / "results" / "model_comparison" CACHE_DIR = MATH_DIR / "cache" / "native" -FACE_MODEL_PATH = MATH_DIR / "cache" / "face_landmarker.task" +OPENFACE_RUNNER = MATH_DIR / "run_openface.ps1" +OPENFACE_PACKAGE = MATH_DIR / "cache" / "openface" / "OpenFace_2.2.0_win_x64" TEXT_MODEL_ID = "google-bert/bert-base-uncased" SPEECH_MODEL_ID = "facebook/wav2vec2-base-960h" @@ -49,33 +51,24 @@ FRAME_STEP = 160 N_FFT = 512 MEL_COUNT = 40 GRID_STEP_S = 0.1 -VISION_RATE_HZ = 5.0 CTC_FRAME_STEP_S = 320 / SAMPLE_RATE CTC_RECEPTIVE_SAMPLES = 400 SEED = 20260923 N_FOLDS = 5 -ACTION_NAMES = ( - "browDownLeft", "browDownRight", "browInnerUp", "browOuterUpLeft", - "browOuterUpRight", "eyeBlinkLeft", "eyeBlinkRight", "eyeSquintLeft", - "eyeSquintRight", "eyeWideLeft", "eyeWideRight", "jawOpen", - "mouthFrownLeft", "mouthFrownRight", "mouthPucker", "mouthSmileLeft", - "mouthSmileRight", -) +AU_CODES = (1, 2, 4, 5, 6, 7, 9, 10, 12, 14, 15, 17, 20, 23, 25, 26, 45) VISION_NAMES = ( - *[f"mp_blendshape_{name}" for name in ACTION_NAMES], - "pose_rotvec_x", "pose_rotvec_y", "pose_rotvec_z", - "pose_translation_x", "pose_translation_y", "pose_translation_z", - "gaze_left_x", "gaze_left_y", "gaze_left_z", - "gaze_right_x", "gaze_right_y", "gaze_right_z", - "eye_aperture_left", "eye_aperture_right", "mouth_aperture", - "mouth_width_face_ratio", "brow_eye_distance_left", "brow_eye_distance_right", + *[f"AU{code:02d}_r" for code in AU_CODES], + "pose_Rx", "pose_Ry", "pose_Rz", "pose_Tx", "pose_Ty", "pose_Tz", + "gaze_0_x", "gaze_0_y", "gaze_0_z", "gaze_1_x", "gaze_1_y", "gaze_1_z", + "geometry_eye_open_left", "geometry_eye_open_right", "geometry_mouth_open", + "geometry_mouth_width", "geometry_brow_eye_left", "geometry_brow_eye_right", ) AUDIO_NAMES = ( *[f"logmel_{index:02d}" for index in range(40)], *[f"mfcc_{index:02d}" for index in range(13)], *[f"delta_mfcc_{index:02d}" for index in range(13)], - "log_energy", "log_f0_hz", "voicing_strength", "spectral_centroid_hz", + "log_energy", "log_f0_hz", "voiced_probability", "spectral_centroid_hz", "spectral_bandwidth_hz", "spectral_flux", "zero_crossing_rate", "hnr_db", ) @@ -97,9 +90,14 @@ class Sample: audio_times: np.ndarray audio_features: np.ndarray audio_observed: np.ndarray + audio_quality: np.ndarray + audio_quality_available: np.ndarray vision_times: np.ndarray + vision_frame_indices: np.ndarray vision_features: np.ndarray vision_observed: np.ndarray + vision_quality: np.ndarray + vision_quality_available: np.ndarray ctc_times: np.ndarray ctc_occupancy: np.ndarray speech_features: np.ndarray @@ -269,38 +267,53 @@ def _audio_features(audio: np.ndarray, duration_s: float) -> tuple[np.ndarray, n energy = np.mean(np.square(frames), axis=1) log_f0 = np.zeros(len(frames), dtype=np.float32) - voicing = np.zeros(len(frames), dtype=np.float32) + voiced_probability = np.zeros(len(frames), dtype=np.float32) hnr = np.zeros(len(frames), dtype=np.float32) - voiced = np.zeros(len(frames), dtype=np.bool_) - min_lag, max_lag = int(SAMPLE_RATE / 400), int(SAMPLE_RATE / 60) - for frame_index, frame in enumerate(windowed): - if energy[frame_index] < 1e-7: - continue - autocorr = irfft(np.abs(rfft(frame, n=1024)) ** 2, n=1024)[:max_lag + 1] - if autocorr[0] <= 1e-10: - continue - autocorr /= autocorr[0] - region = autocorr[min_lag:max_lag + 1] - if not len(region): - continue - lag = min_lag + int(np.argmax(region)) - strength = float(np.clip(autocorr[lag], 0.0, 1.0)) - voicing[frame_index] = strength - voiced[frame_index] = strength >= 0.30 - if voiced[frame_index]: - log_f0[frame_index] = math.log(SAMPLE_RATE / lag) - hnr[frame_index] = 10.0 * math.log10(max(strength, 1e-5) / max(1.0 - strength, 1e-5)) + pitch_observed = np.zeros(len(frames), dtype=np.bool_) + voicing_observed = np.zeros(len(frames), dtype=np.bool_) + hnr_observed = np.zeros(len(frames), dtype=np.bool_) + if len(audio) >= FRAME_LENGTH: + f0, voiced_flag, voiced_prob = librosa.pyin( + audio.astype(np.float32), + fmin=80.0, + fmax=400.0, + sr=SAMPLE_RATE, + frame_length=FRAME_LENGTH, + hop_length=FRAME_STEP, + center=False, + fill_na=np.nan, + ) + rows = min(len(frames), len(f0), len(voiced_prob)) + for frame_index in range(rows): + if np.isfinite(voiced_prob[frame_index]): + voiced_probability[frame_index] = float(np.clip(voiced_prob[frame_index], 0.0, 1.0)) + voicing_observed[frame_index] = True + if not np.isfinite(f0[frame_index]) or not bool(voiced_flag[frame_index]): + continue + log_f0[frame_index] = math.log(float(f0[frame_index])) + pitch_observed[frame_index] = True + frame = windowed[frame_index] + autocorr = irfft(np.abs(rfft(frame, n=1024)) ** 2, n=1024)[:FRAME_LENGTH] + if autocorr[0] <= 1e-10: + continue + lag = int(round(SAMPLE_RATE / float(f0[frame_index]))) + if lag <= 0 or lag >= len(autocorr): + continue + periodicity = float(np.clip(autocorr[lag] / autocorr[0], 1e-5, 1.0 - 1e-5)) + hnr[frame_index] = 10.0 * math.log10(periodicity / (1.0 - periodicity)) + hnr_observed[frame_index] = True prosody = np.column_stack(( - np.log(np.maximum(energy, 1e-8)), log_f0, voicing, centroid, bandwidth, + np.log(np.maximum(energy, 1e-8)), log_f0, voiced_probability, centroid, bandwidth, flux, zcr, hnr, )).astype(np.float32) features = np.column_stack((log_mel, mfcc, delta, prosody)).astype(np.float32) if features.shape[1] != 74: raise AssertionError(f"internal audio dimension error: {features.shape}") observed = np.isfinite(features) - observed[:, 67] = voiced - observed[:, 73] = voiced + observed[:, 67] = pitch_observed + observed[:, 68] = voicing_observed + observed[:, 73] = hnr_observed if len(frames) < 2: observed[:, 53:66] = False features = np.nan_to_num(features, nan=0.0, posinf=0.0, neginf=0.0) @@ -593,180 +606,146 @@ def _posterior_hard_intervals( return intervals, valid, quality -def _landmark_points(landmarks: Iterable[Any]) -> np.ndarray: - return np.asarray([[item.x, item.y, item.z] for item in landmarks], dtype=np.float32) +def _openface_float(row: dict[str, str], name: str) -> float: + try: + value = float(row[name]) + except (KeyError, TypeError, ValueError): + return math.nan + return value if math.isfinite(value) else math.nan -def _distance(points: np.ndarray, left: int, right: int) -> float: - return float(np.linalg.norm(points[left] - points[right])) +def _openface_geometry(row: dict[str, str]) -> tuple[np.ndarray, np.ndarray]: + points = np.full((68, 2), np.nan, dtype=np.float64) + for index in range(68): + points[index, 0] = _openface_float(row, f"x_{index}") + points[index, 1] = _openface_float(row, f"y_{index}") + values = np.zeros(6, dtype=np.float32) + valid = np.zeros(6, dtype=bool) + if not np.isfinite(points[36:48]).all(): + return values, valid + left_eye = points[36:42].mean(axis=0) + right_eye = points[42:48].mean(axis=0) + interocular = float(np.linalg.norm(left_eye - right_eye)) + if interocular <= 1e-6: + return values, valid + + def distance(left: int, right: int) -> float: + return float(np.linalg.norm(points[left] - points[right])) + + pairs = ((37, 41), (38, 40), (43, 47), (44, 46), (61, 67), (62, 66), (63, 65), (48, 54)) + needed = {index for pair in pairs for index in pair} | set(range(17, 27)) + complete = {index: np.isfinite(points[index]).all() for index in needed} + if complete[37] and complete[41] and complete[38] and complete[40]: + values[0] = (distance(37, 41) + distance(38, 40)) / (2.0 * interocular) + valid[0] = True + if complete[43] and complete[47] and complete[44] and complete[46]: + values[1] = (distance(43, 47) + distance(44, 46)) / (2.0 * interocular) + valid[1] = True + mouth_pairs = ((61, 67), (62, 66), (63, 65)) + if all(complete[a] and complete[b] for a, b in mouth_pairs): + values[2] = sum(distance(a, b) for a, b in mouth_pairs) / (3.0 * interocular) + valid[2] = True + if complete[48] and complete[54]: + values[3] = distance(48, 54) / interocular + valid[3] = True + if all(complete[index] for index in range(17, 22)): + values[4] = float(np.linalg.norm(points[17:22].mean(axis=0) - left_eye) / interocular) + valid[4] = True + if all(complete[index] for index in range(22, 27)): + values[5] = float(np.linalg.norm(points[22:27].mean(axis=0) - right_eye) / interocular) + valid[5] = True + valid &= np.isfinite(values) + values[~valid] = 0.0 + return values, valid -def _gaze_proxy(points: np.ndarray, left_eye: bool) -> np.ndarray | None: - if points.shape[0] < 478: - return None - if left_eye: - corner_a, corner_b, upper, lower = 33, 133, 159, 145 - iris_ids = np.arange(468, 473) - else: - corner_a, corner_b, upper, lower = 362, 263, 386, 374 - iris_ids = np.arange(473, 478) - horizontal = points[corner_b] - points[corner_a] - width = float(np.linalg.norm(horizontal)) - vertical = points[upper] - points[lower] - height = float(np.linalg.norm(vertical)) - if width <= 1e-6 or height <= 1e-6: - return None - u = horizontal / width - v = vertical - float(np.dot(vertical, u)) * u - v_norm = float(np.linalg.norm(v)) - if v_norm <= 1e-6: - return None - v /= v_norm - eye_center = (points[corner_a] + points[corner_b]) / 2 - iris_center = points[iris_ids].mean(axis=0) - delta = iris_center - eye_center - gx = float(np.dot(delta, u) / width) - gy = float(np.dot(delta, v) / width) - # Face-relative iris offset plus a fixed forward component; this is a gaze proxy. - direction = np.asarray([-gx, -gy, -1.0], dtype=np.float32) - norm = float(np.linalg.norm(direction)) - if norm <= 1e-8: - return None - return direction / norm - - -def _pose_from_matrix(matrix_obj: Any) -> tuple[np.ndarray, np.ndarray] | None: - raw = np.asarray(matrix_obj.data, dtype=np.float64) - rows = int(getattr(matrix_obj, "rows", 4) or 4) - cols = int(getattr(matrix_obj, "cols", 4) or 4) - if raw.size != rows * cols or rows < 3 or cols < 4: - return None - matrix = raw.reshape(rows, cols) - rotation_raw = matrix[:3, :3] - if not np.isfinite(rotation_raw).all() or not np.isfinite(matrix[:3, 3]).all(): - return None - u, _, vh = np.linalg.svd(rotation_raw) - rotation_matrix = u @ vh - if np.linalg.det(rotation_matrix) < 0: - u[:, -1] *= -1 - rotation_matrix = u @ vh - return Rotation.from_matrix(rotation_matrix).as_rotvec().astype(np.float32), matrix[:3, 3].astype(np.float32) - - -def _vision_frame_features(landmarks: list[Any], blendshapes: list[Any], matrix_obj: Any | None) -> tuple[np.ndarray, np.ndarray]: - features = np.zeros(35, dtype=np.float32) - observed = np.zeros(35, dtype=np.bool_) - shape_lookup = {category.category_name: float(category.score) for category in blendshapes} - for index, name in enumerate(ACTION_NAMES): - if name in shape_lookup and math.isfinite(shape_lookup[name]): - features[index] = shape_lookup[name] - observed[index] = True - - if matrix_obj is not None: - pose = _pose_from_matrix(matrix_obj) - if pose is not None: - features[17:20] = pose[0] - features[20:23] = pose[1] - observed[17:23] = True - - points = _landmark_points(landmarks) - for eye_index, is_left in enumerate((True, False)): - gaze = _gaze_proxy(points, is_left) - if gaze is not None: - start = 23 + eye_index * 3 - features[start:start + 3] = gaze - observed[start:start + 3] = True - if points.shape[0] >= 455: - face_width = _distance(points, 234, 454) - left_eye_width = _distance(points, 33, 133) - right_eye_width = _distance(points, 362, 263) - mouth_width = _distance(points, 61, 291) - if min(face_width, left_eye_width, right_eye_width, mouth_width) > 1e-6: - ratios = np.asarray(( - _distance(points, 159, 145) / left_eye_width, - _distance(points, 386, 374) / right_eye_width, - _distance(points, 13, 14) / mouth_width, - mouth_width / face_width, - _distance(points, 105, 159) / left_eye_width, - _distance(points, 334, 386) / right_eye_width, - ), dtype=np.float32) - features[29:35] = ratios - observed[29:35] = np.isfinite(ratios) - return features, observed - - -def _ensure_face_model() -> str: - FACE_MODEL_PATH.parent.mkdir(parents=True, exist_ok=True) - if not FACE_MODEL_PATH.is_file() or FACE_MODEL_PATH.stat().st_size < 1_000_000: - url = ( - "https://storage.googleapis.com/mediapipe-models/face_landmarker/" - "face_landmarker/float16/latest/face_landmarker.task" +def _run_openface(path: Path, output_name: str) -> Path: + relative_path = path.resolve().relative_to(ROOT).as_posix() + output_dir = MATH_DIR / "cache" / "openface_outputs" + output_dir.mkdir(parents=True, exist_ok=True) + csv_path = output_dir / f"{output_name}.csv" + if csv_path.is_file() and csv_path.stat().st_mtime >= path.stat().st_mtime: + return csv_path + powershell = shutil.which("powershell.exe") or shutil.which("pwsh.exe") + if powershell is None or not OPENFACE_RUNNER.is_file(): + raise FileNotFoundError( + "OpenFace 2.2.0 is required for compliant vision features. Install its Windows package under " + f"{OPENFACE_PACKAGE} and run through {OPENFACE_RUNNER}; no MediaPipe proxy fallback is allowed." ) - temporary = FACE_MODEL_PATH.with_suffix(".task.tmp") - urllib.request.urlretrieve(url, temporary) - if temporary.stat().st_size < 1_000_000: - temporary.unlink(missing_ok=True) - raise RuntimeError("downloaded Face Landmarker model is unexpectedly small") - temporary.replace(FACE_MODEL_PATH) - return _sha256(FACE_MODEL_PATH) - - -def _vision_features(path: Path, duration_s: float, face_model_path: Path) -> tuple[np.ndarray, np.ndarray, np.ndarray]: - options = mp.tasks.vision.FaceLandmarkerOptions( - base_options=mp.tasks.BaseOptions(model_asset_path=str(face_model_path)), - running_mode=mp.tasks.vision.RunningMode.VIDEO, - num_faces=1, - output_face_blendshapes=True, - output_facial_transformation_matrixes=True, + completed = subprocess.run( + [powershell, "-NoProfile", "-ExecutionPolicy", "Bypass", "-File", str(OPENFACE_RUNNER), + "-VideoRelativePath", relative_path, "-OutputName", output_name], + check=False, + capture_output=True, + text=True, + errors="replace", ) - capture = cv2.VideoCapture(str(path)) - if not capture.isOpened(): - raise RuntimeError(f"OpenCV cannot decode video: {path}") - fps = float(capture.get(cv2.CAP_PROP_FPS) or 0.0) - if not math.isfinite(fps) or fps <= 0: - fps = 30.0 + if completed.returncode != 0 or not csv_path.is_file(): + raise RuntimeError( + f"OpenFace failed for {path}: exit={completed.returncode}; " + f"stdout={completed.stdout[-2000:]}; stderr={completed.stderr[-2000:]}" + ) + return csv_path + + +def _vision_features(path: Path, duration_s: float, output_name: str) -> tuple[np.ndarray, np.ndarray, np.ndarray, np.ndarray, np.ndarray, np.ndarray]: + """Read 35-D OpenFace features and keep raw PTS, frame IDs and confidence.""" + csv_path = _run_openface(path, output_name) timestamps: list[float] = [] + frame_indices: list[int] = [] values: list[np.ndarray] = [] masks: list[np.ndarray] = [] - next_time = 0.0 - frame_index = 0 - last_timestamp_ms = -1 - with mp.tasks.vision.FaceLandmarker.create_from_options(options) as landmarker: - while True: - ok, bgr = capture.read() - if not ok: - break - reported_ms = float(capture.get(cv2.CAP_PROP_POS_MSEC)) - timestamp = reported_ms / 1000.0 - previous_timestamp = timestamps[-1] if timestamps else -1.0 - if not math.isfinite(timestamp) or (frame_index > 0 and timestamp <= previous_timestamp): - timestamp = frame_index / fps - frame_index += 1 - if timestamp + 1e-6 < next_time: + qualities: list[float] = [] + quality_available: list[bool] = [] + with csv_path.open("r", encoding="utf-8-sig", newline="") as stream: + reader = csv.DictReader(stream, skipinitialspace=True) + for raw_row in reader: + row = {str(key).strip(): str(value).strip() for key, value in raw_row.items() if key is not None} + timestamp = _openface_float(row, "timestamp") + frame = _openface_float(row, "frame") + confidence = _openface_float(row, "confidence") + success = _openface_float(row, "success") + if not math.isfinite(timestamp) or not math.isfinite(frame): continue - while next_time <= timestamp: - next_time += 1.0 / VISION_RATE_HZ - timestamp = min(max(timestamp, 0.0), duration_s) - timestamp_ms = max(last_timestamp_ms + 1, int(round(timestamp * 1000))) - last_timestamp_ms = timestamp_ms - rgb = cv2.cvtColor(bgr, cv2.COLOR_BGR2RGB) - image = mp.Image(image_format=mp.ImageFormat.SRGB, data=np.ascontiguousarray(rgb)) - result = landmarker.detect_for_video(image, timestamp_ms) + timestamp = float(np.clip(timestamp, 0.0, duration_s)) + vector = np.zeros(35, dtype=np.float32) + observed = np.zeros(35, dtype=bool) + good_face = success >= 1.0 and math.isfinite(confidence) and confidence >= 0.8 + if good_face: + for index, code in enumerate(AU_CODES): + value = _openface_float(row, f"AU{code:02d}_r") + if math.isfinite(value): + vector[index] = value + observed[index] = True + for offset, name in enumerate(("pose_Rx", "pose_Ry", "pose_Rz", "pose_Tx", "pose_Ty", "pose_Tz"), start=17): + value = _openface_float(row, name) + if math.isfinite(value): + vector[offset] = value + observed[offset] = True + gaze_names = ("gaze_0_x", "gaze_0_y", "gaze_0_z", "gaze_1_x", "gaze_1_y", "gaze_1_z") + for offset, name in enumerate(gaze_names, start=23): + value = _openface_float(row, name) + if math.isfinite(value): + vector[offset] = value + observed[offset] = True + geometry, geometry_mask = _openface_geometry(row) + vector[29:35] = geometry + observed[29:35] = geometry_mask timestamps.append(timestamp) - faces = result.face_landmarks - if not faces: - values.append(np.zeros(35, dtype=np.float32)) - masks.append(np.zeros(35, dtype=np.bool_)) - continue - blendshapes = result.face_blendshapes[0] if result.face_blendshapes else [] - matrix = result.facial_transformation_matrixes[0] if result.facial_transformation_matrixes else None - vector, mask = _vision_frame_features(faces[0], blendshapes, matrix) + frame_indices.append(int(frame)) values.append(vector) - masks.append(mask) - capture.release() + masks.append(observed) + qualities.append(float(np.clip(confidence, 0.0, 1.0)) if math.isfinite(confidence) and success >= 1.0 else 1.0) + quality_available.append(bool(math.isfinite(confidence) and success >= 1.0)) if not timestamps: - return np.empty(0, np.float32), np.empty((0, 35), np.float32), np.empty((0, 35), np.bool_) - return np.asarray(timestamps, np.float32), np.stack(values), np.stack(masks) + return (np.empty(0, np.float32), np.empty(0, np.int32), np.empty((0, 35), np.float32), + np.empty((0, 35), bool), np.empty(0, np.float32), np.empty(0, bool)) + order = np.argsort(np.asarray(timestamps), kind="stable") + return ( + np.asarray(timestamps, np.float32)[order], np.asarray(frame_indices, np.int32)[order], + np.stack(values)[order], np.stack(masks)[order], np.asarray(qualities, np.float32)[order], + np.asarray(quality_available, bool)[order], + ) def _load_models(device: torch.device) -> tuple[Any, Any, Any, Any, dict[str, Any]]: @@ -796,7 +775,6 @@ def _extract_native_sample( record: dict[str, Any], models: tuple[Any, Any, Any, Any, dict[str, Any]], device: torch.device, - face_model_path: Path, video_sha256: str, ) -> Sample: text_tokenizer, text_model, ctc_tokenizer, speech_model, model_info = models @@ -806,7 +784,9 @@ def _extract_native_sample( text_vectors, text_valid = _text_features(words, text_tokenizer, text_model, device) waveform = _decode_audio(video_path) audio_times, audio_vectors, audio_observed = _audio_features(waveform, duration_s) - vision_times, vision_vectors, vision_observed = _vision_features(video_path, duration_s, face_model_path) + output_name = f"{_safe_name(record['video_id'])}__{_safe_name(record['clip_id'])}" + (vision_times, vision_frame_indices, vision_vectors, vision_observed, + vision_quality, vision_quality_available) = _vision_features(video_path, duration_s, output_name) targets, word_targets = _ctc_targets(words, ctc_tokenizer) blank_id = int(ctc_tokenizer.pad_token_id) if targets: @@ -858,9 +838,14 @@ def _extract_native_sample( audio_times=audio_times, audio_features=audio_vectors.astype(np.float16), audio_observed=audio_observed, + audio_quality=np.clip((len(waveform) - np.arange(len(audio_times)) * FRAME_STEP) / FRAME_LENGTH, 0.0, 1.0).astype(np.float32), + audio_quality_available=np.ones(len(audio_times), bool), vision_times=vision_times, + vision_frame_indices=vision_frame_indices, vision_features=vision_vectors.astype(np.float16), vision_observed=vision_observed, + vision_quality=vision_quality, + vision_quality_available=vision_quality_available, ctc_times=ctc_frame_times, ctc_occupancy=occupancy.astype(np.float16), speech_features=deep_states.astype(np.float16), @@ -891,9 +876,14 @@ def _save_cache(path: Path, sample: Sample, cache_schema: str) -> None: audio_times=sample.audio_times.astype(np.float32), audio_features=sample.audio_features.astype(np.float16), audio_observed=sample.audio_observed, + audio_quality=sample.audio_quality.astype(np.float32), + audio_quality_available=sample.audio_quality_available, vision_times=sample.vision_times.astype(np.float32), + vision_frame_indices=sample.vision_frame_indices.astype(np.int32), vision_features=sample.vision_features.astype(np.float16), vision_observed=sample.vision_observed, + vision_quality=sample.vision_quality.astype(np.float32), + vision_quality_available=sample.vision_quality_available, ctc_times=sample.ctc_times.astype(np.float32), ctc_occupancy=sample.ctc_occupancy.astype(np.float16), speech_features=sample.speech_features.astype(np.float16), @@ -918,8 +908,14 @@ def _load_cache(path: Path, record: dict[str, Any], source_hash: str, cache_sche text_valid=np.asarray(data["text_valid"], dtype=np.bool_), hard_intervals=np.asarray(data["hard_intervals"], dtype=np.float32), hard_valid=np.asarray(data["hard_valid"], dtype=np.bool_), hard_quality=np.asarray(data["hard_quality"], dtype=np.float32), audio_times=np.asarray(data["audio_times"], dtype=np.float32), audio_features=np.asarray(data["audio_features"], dtype=np.float16), - audio_observed=np.asarray(data["audio_observed"], dtype=np.bool_), vision_times=np.asarray(data["vision_times"], dtype=np.float32), + audio_observed=np.asarray(data["audio_observed"], dtype=np.bool_), + audio_quality=np.asarray(data["audio_quality"], dtype=np.float32), + audio_quality_available=np.asarray(data["audio_quality_available"], dtype=np.bool_), + vision_times=np.asarray(data["vision_times"], dtype=np.float32), + vision_frame_indices=np.asarray(data["vision_frame_indices"], dtype=np.int32), vision_features=np.asarray(data["vision_features"], dtype=np.float16), vision_observed=np.asarray(data["vision_observed"], dtype=np.bool_), + vision_quality=np.asarray(data["vision_quality"], dtype=np.float32), + vision_quality_available=np.asarray(data["vision_quality_available"], dtype=np.bool_), ctc_times=np.asarray(data["ctc_times"], dtype=np.float32), ctc_occupancy=np.asarray(data["ctc_occupancy"], dtype=np.float16), speech_features=np.asarray(data["speech_features"], dtype=np.float16), boundary_summary=json.loads(str(data["boundary_summary"].item())), video_sha256=source_hash, @@ -979,17 +975,18 @@ def _project_rows( for target_index, (left, right) in enumerate(zip(target_edges[:-1], target_edges[1:])): if right <= left: continue - overlap = np.maximum( + physical_overlap = np.maximum( 0.0, np.minimum(intervals[:, 1], right) - np.maximum(intervals[:, 0], left), - ) * qualities - candidate = np.flatnonzero(overlap > 0) + ) + weighted_overlap = physical_overlap * qualities + candidate = np.flatnonzero(physical_overlap > 0) if not len(candidate): continue local_mask = observed[candidate] - local_weight = overlap[candidate, None] * local_mask + local_weight = weighted_overlap[candidate, None] * local_mask denominator = local_weight.sum(axis=0) - physical_coverage = (overlap[candidate, None] * local_mask).sum(axis=0) + physical_coverage = (physical_overlap[candidate, None] * local_mask).sum(axis=0) good = denominator > 0 if good.any(): output[target_index, good] = ( @@ -1000,11 +997,11 @@ def _project_rows( return output, mask, coverage -def _so3_weighted_mean(rotvecs: np.ndarray, weights: np.ndarray) -> np.ndarray | None: +def _so3_weighted_mean(euler_xyz: np.ndarray, weights: np.ndarray) -> np.ndarray | None: positive = weights > 0 if not positive.any(): return None - rotations = Rotation.from_rotvec(np.asarray(rotvecs[positive], dtype=np.float64)) + rotations = Rotation.from_euler("xyz", np.asarray(euler_xyz[positive], dtype=np.float64)) local_weights = np.asarray(weights[positive], dtype=np.float64) local_weights /= local_weights.sum() matrices = rotations.as_matrix() @@ -1021,12 +1018,12 @@ def _so3_weighted_mean(rotvecs: np.ndarray, weights: np.ndarray) -> np.ndarray | if np.linalg.norm(delta) < 1e-8: break mean_rotation = mean_rotation * Rotation.from_rotvec(delta) - return mean_rotation.as_rotvec().astype(np.float32) + return mean_rotation.as_euler("xyz").astype(np.float32) def _project_vision_geometry(sample: Sample, target_edges: np.ndarray, geometry_aware: bool) -> tuple[np.ndarray, np.ndarray, np.ndarray]: intervals = _voronoi_intervals(sample.vision_times, sample.duration_s) - quality = np.ones(len(intervals), dtype=np.float32) + quality = sample.vision_quality values, masks, coverage = _project_rows( sample.vision_features.astype(np.float32), sample.vision_observed, intervals, quality, target_edges ) @@ -1037,16 +1034,17 @@ def _project_vision_geometry(sample: Sample, target_edges: np.ndarray, geometry_ overlap = np.maximum(0.0, np.minimum(intervals[:, 1], right) - np.maximum(intervals[:, 0], left)) if not np.any(overlap > 0): continue - pose_rows = (overlap > 0) & sample.vision_observed[:, 17:20].all(axis=1) + weighted_overlap = overlap * quality + pose_rows = (weighted_overlap > 0) & sample.vision_observed[:, 17:20].all(axis=1) if pose_rows.any(): - vector = _so3_weighted_mean(raw[pose_rows, 17:20], overlap[pose_rows]) + vector = _so3_weighted_mean(raw[pose_rows, 17:20], weighted_overlap[pose_rows]) if vector is not None: values[target_index, 17:20] = vector masks[target_index, 17:20] = True for start in (23, 26): - valid_rows = (overlap > 0) & sample.vision_observed[:, start:start + 3].all(axis=1) + valid_rows = (weighted_overlap > 0) & sample.vision_observed[:, start:start + 3].all(axis=1) if valid_rows.any(): - weights = overlap[valid_rows].astype(np.float64) + weights = weighted_overlap[valid_rows].astype(np.float64) vector = np.average(raw[valid_rows, start:start + 3], axis=0, weights=weights) norm = float(np.linalg.norm(vector)) if norm > 1e-6: @@ -1070,7 +1068,7 @@ def _project_posterior_text(sample: Sample, target_edges: np.ndarray) -> tuple[n frame_edges = np.clip( first_edge + np.arange(len(sample.ctc_times) + 1, dtype=np.float64) * frame_step, 0.0, - sample.duration_s, + _audio_end_time(sample), ) occupancy = sample.ctc_occupancy.astype(np.float64) for target_index, (left, right) in enumerate(zip(target_edges[:-1], target_edges[1:])): @@ -1089,35 +1087,47 @@ def _project_posterior_text(sample: Sample, target_edges: np.ndarray) -> tuple[n def _normalized_hard_quality(sample: Sample) -> np.ndarray: - text_quality = np.zeros_like(sample.hard_quality, dtype=np.float32) + text_quality = np.ones_like(sample.hard_quality, dtype=np.float32) valid_quality = sample.hard_valid & (sample.hard_quality > 0) if valid_quality.any(): - quality_reference = float(np.median(sample.hard_quality[valid_quality])) - text_quality[valid_quality] = np.clip( - sample.hard_quality[valid_quality].astype(np.float64) / quality_reference, 0.25, 4.0 - ) + text_quality[valid_quality] = np.clip(sample.hard_quality[valid_quality], 0.0, 1.0) return text_quality +def _audio_end_time(sample: Sample) -> float: + """Recover decoded sample support from the final partial analysis window.""" + valid = np.flatnonzero(np.asarray(sample.audio_quality) > 0) + if not len(valid): + return 0.0 + index = int(valid[-1]) + quality = float(np.clip(sample.audio_quality[index], 0.0, 1.0)) + sample_count = index * FRAME_STEP + int(round(quality * FRAME_LENGTH)) + return float(min(sample.duration_s, sample_count / SAMPLE_RATE)) + + def _make_views(sample: Sample) -> tuple[View, View, View]: edges = _grid_edges(sample.duration_s) + audio_end_s = _audio_end_time(sample) + hard_intervals = np.clip(sample.hard_intervals.astype(np.float32), 0.0, audio_end_s) + hard_valid = sample.hard_valid & (hard_intervals[:, 1] > hard_intervals[:, 0]) hard_text_observed = np.broadcast_to(sample.text_valid[:, None], sample.text_features.shape).copy() text_quality = _normalized_hard_quality(sample) + text_quality[~hard_valid] = 0.0 text_hard = _project_rows( sample.text_features.astype(np.float32), hard_text_observed, - sample.hard_intervals, text_quality, edges, + hard_intervals, text_quality, edges, ) audio = _project_rows( sample.audio_features.astype(np.float32), sample.audio_observed, - _voronoi_intervals(sample.audio_times, sample.duration_s), - np.ones(len(sample.audio_times), dtype=np.float32), edges, + _voronoi_intervals(sample.audio_times, audio_end_s), + sample.audio_quality, edges, ) vision_b0 = _project_vision_geometry(sample, edges, geometry_aware=False) vision_b1 = _project_vision_geometry(sample, edges, geometry_aware=True) speech = _project_rows( sample.speech_features.astype(np.float32), np.ones(sample.speech_features.shape, dtype=np.bool_), - _voronoi_intervals(sample.ctc_times, sample.duration_s), + _voronoi_intervals(sample.ctc_times, audio_end_s), np.ones(len(sample.ctc_times), dtype=np.float32), edges, ) post_text = _project_posterior_text(sample, edges) @@ -1241,11 +1251,11 @@ def _dynamic_signature(sample: Sample, scaled_view: View) -> np.ndarray: audio_mask = scaled_view.observed["audio"] vision = scaled_view.features["vision"] vision_mask = scaled_view.observed["vision"] - # log-F0, log-energy; MediaPipe jaw-open proxy and normalized mouth aperture. + # log-F0, log-energy; OpenFace AU12 intensity and normalized mouth opening. audio_values = audio[:, [67, 66]] audio_valid = audio_mask[:, [67, 66]].all(axis=1) - vision_values = vision[:, [11, 31]] - vision_valid = vision_mask[:, [11, 31]].all(axis=1) + vision_values = vision[:, [10, 31]] + vision_valid = vision_mask[:, [10, 31]].all(axis=1) result: list[float] = [] for index in range(5): left, right = float(segments[index]), float(segments[index + 1]) @@ -1668,19 +1678,19 @@ def _write_report( lines = [ "# 问题一 B0-B4 模型对比结果", "", - "本报告按 `math/Q1/问题一.pdf` 第 4.8.3 节实施五组单因素对照。全部 100 条附件一视频均使用同一套冻结特征抽取器、0.1 秒主时间网格、观测掩码与按 `video_id` 分组的五折划分。情感标签仅用于折内的轻量预测探针，不进入时间对齐、CTC 后验或动态签名计算。", + "本报告按 `math/E题V2.pdf` 第 4.9.3 节实施五组单因素对照。全部 100 条附件一视频均使用同一套冻结特征抽取器、0.1 秒主时间网格、观测掩码与按 `video_id` 分组的五折划分。情感标签仅用于折内的轻量预测探针，不进入时间对齐、CTC 后验或动态签名计算。", "", "## 实际特征和比较版本", "", "| 版本 | 实施内容 |", "| --- | --- |", - "| B0 | CTC Viterbi 词区间与音频/视觉物理时间区间投影；训练折均值/标准差缩放；视觉旋转向量和视线向量作普通分量均值。 |", - "| B1 | 在 B0 上改用训练折中位数与 MAD 的稳健尺度（MAD 为零时回退到训练折标准差），并对视觉旋转用 SO(3) 均值、视线用归一化向量均值。 |", + "| B0 | 固定转写 CTC Viterbi 词区间与原生音频/视频时间归属区间的质量加权投影；训练折均值/标准差缩放。 |", + "| B1 | 在 B0 上改用训练折中位数与 MAD 的稳健尺度（MAD 为零时回退到训练折标准差），并对头部旋转用 SO(3) 均值、视线用归一化向量均值。 |", "| B2 | 在 B1 上只将文本词向量的硬边界投影替换为固定转写 CTC 状态图的前向–后向占据概率投影；媒体时间戳仍按物理时间。 |", - "| B3 | 在 B1 上仅附加音频 log-F0/能量与视觉 jaw-open/嘴部开合率的时间增广一、二阶路径签名；缺测点之间不连线。 |", + "| B3 | 在 B1 上仅附加音频 log-F0/能量与 OpenFace AU12/嘴部开合率的时间增广一、二阶路径签名；缺测点之间不连线。 |", "| B4 | 在 B1 上仅附加冻结 Wav2Vec2-base-960h 最后四层的时间投影表示。 |", "", - "附件一现有标签表和原始视频被直接使用。文本为 768 维 BERT-base-uncased 末四层均值；音频为 74 维（log-Mel 40、MFCC 13、ΔMFCC 13、韵律/谱统计 8）；视觉为 35 维（17 个 MediaPipe blendshape 代理、6 维头姿、6 维近似视线、6 维面部比例几何）。视觉代理和几何索引定义见 `compare_models.py`，它们与 OpenFace AU 定义并不等同；该限制须在论文中明示。", + "附件一现有标签表和原始视频被直接使用。文本为 768 维冻结 BERT-base-uncased 末四层均值；音频为 74 维（log-Mel 40、MFCC 13、ΔMFCC 13、韵律/谱统计 8）；视觉为 35 维 OpenFace（17 个 AU 强度、6 维头姿、6 维双眼视线、6 维无量纲几何），置信度低于 0.8 的面部量按缺失处理。基频/有声概率使用 librosa pYIN（80–400 Hz、400 样本帧、160 样本步长），谐噪比由预测基频处的自相关周期性另行计算；pYIN 对 80 Hz 与 25 ms 窗发出周期数不足提示，因此该基频下界结果需谨慎解释。", "", "## 结果", "", @@ -1727,7 +1737,7 @@ def _write_report( "uv run python compare_models.py", "```", "", - "特征缓存写在 `math/Q1/cache/native/`，正式结果只写在 `math/Q1/results/model_comparison/`。删除缓存后会从附件一重新提取。首次运行需要下载 BERT、Wav2Vec2 和 MediaPipe Face Landmarker 权重。", + "特征缓存写在 `math/Q1/cache/native/`，OpenFace 原始 CSV 写在 `math/Q1/cache/openface_outputs/`，正式结果写在 `math/Q1/results/model_comparison/`。删除缓存后会从附件一重新提取。运行前需准备 BERT、Wav2Vec2 权重及 OpenFace 2.2.0 Windows 包。", ] (output_dir / "report.md").write_text("\n".join(lines) + "\n", encoding="utf-8") @@ -1778,8 +1788,7 @@ def run(args: argparse.Namespace) -> None: source_hashes[record["sample_id"]] = _sha256(video_path) output_dir.mkdir(parents=True, exist_ok=True) cache_dir.mkdir(parents=True, exist_ok=True) - cache_schema = "q1-b0b4-v3" - face_hash = _ensure_face_model() + cache_schema = "q1-b0b4-v4-openface" samples: list[Sample] = [] missing_records: list[dict[str, Any]] = [] cache_paths = { @@ -1807,7 +1816,7 @@ def run(args: argparse.Namespace) -> None: for index, record in enumerate(missing_records, start=1): started = time.perf_counter() sample = _extract_native_sample( - record, models, device, FACE_MODEL_PATH, source_hashes[record["sample_id"]] + record, models, device, source_hashes[record["sample_id"]] ) _save_cache(cache_paths[record["sample_id"]], sample, cache_schema) cached_by_id[sample.sample_id] = sample @@ -1850,13 +1859,13 @@ def run(args: argparse.Namespace) -> None: "created_at_local": time.strftime("%Y-%m-%d %H:%M:%S %z"), "python": sys.version, "platform": platform.platform(), - "uv_version": subprocess.run(["uv", "--version"], capture_output=True, text=True).stdout.strip(), - "packages": {name: _version(name) for name in ("torch", "transformers", "numpy", "scipy", "scikit-learn", "mediapipe", "opencv-python-headless", "openpyxl", "matplotlib")}, + "uv_version": subprocess.run([shutil.which("uv"), "--version"], capture_output=True, text=True).stdout.strip() if shutil.which("uv") else "uv run parent; executable not on child PATH", + "packages": {name: _version(name) for name in ("torch", "transformers", "numpy", "scipy", "scikit-learn", "opencv-python-headless", "librosa", "openpyxl", "matplotlib")}, "device": args.device if args.device != "auto" else ("cuda" if torch.cuda.is_available() else "cpu"), "cuda_available": bool(torch.cuda.is_available()), "gpu_name": torch.cuda.get_device_name(0) if torch.cuda.is_available() and args.device != "cpu" else None, "models": model_info, - "face_landmarker_asset_sha256": face_hash, + "openface": {"version": "2.2.0", "executable": "FeatureExtraction", "landmark_model": "main_clnf_general.txt", "confidence_threshold": 0.8}, "inputs": { "label_file": str(label_file), "label_file_sha256": _sha256(label_file), @@ -1877,20 +1886,22 @@ def run(args: argparse.Namespace) -> None: "vision_dimension": 35, "audio_features": list(AUDIO_NAMES), "vision_features": list(VISION_NAMES), - "vision_feature_note": "17 MediaPipe blendshape proxies and approximate gaze/landmark geometry; not OpenFace AU labels", + "vision_feature_note": "OpenFace 2.2.0 AU intensities, pose, gaze, and six geometry values defined in E题V2.pdf section 4.2.3", "grid_step_s": GRID_STEP_S, "audio_window_samples": FRAME_LENGTH, "audio_step_samples": FRAME_STEP, "audio_fft": N_FFT, "audio_mel_bands": MEL_COUNT, - "vision_sample_rate_hz": VISION_RATE_HZ, + "pitch_estimator": {"name": "librosa.pyin", "version": _version("librosa"), "f0_range_hz": [80.0, 400.0], "frame_length_samples": FRAME_LENGTH, "hop_length_samples": FRAME_STEP, "center": False}, + "hnr_estimator": "autocorrelation periodicity at pYIN-detected F0; dB", + "vision_sample_rate_hz": "native OpenFace frame timestamps; no fixed-rate assumption", "grouping": "GroupKFold by video_id", "fold_count": N_FOLDS, "probe": {"classifier": "LogisticRegression", "C": 0.05, "regressor": "Ridge", "alpha": 25.0, "intensity_clip": [-3.0, 3.0]}, "bootstrap": {"unit": "video_id", "repeats": args.bootstrap_repeats, "seed": SEED}, "human_boundary_reference_count": 0, "boundary_interval_level": 0.90, - "hard_text_quality_weight": "per-sample median-normalized CTC path score clipped to [0.25, 4.0]; uncalibrated", + "hard_text_quality_weight": "raw fixed-transcript CTC word path score in [0,1]; unavailable scores use q*=1 and are flagged unavailable", "cache_schema": cache_schema, }, "output_dir": str(output_dir), diff --git a/math/Q1/compare_v2.py b/math/Q1/compare_v2.py new file mode 100644 index 0000000..faecedb --- /dev/null +++ b/math/Q1/compare_v2.py @@ -0,0 +1,307 @@ +"""Evaluate the Q1 V2 B0-B4 branches with leakage-safe video-group folds.""" +from __future__ import annotations + +import argparse +import csv +import hashlib +import json +import math +from pathlib import Path +from typing import Any + +import numpy as np +from sklearn.linear_model import LogisticRegression, Ridge +from sklearn.metrics import accuracy_score, f1_score, mean_absolute_error, mean_squared_error +from sklearn.model_selection import GroupKFold + +import compare_models as cm +import q1_io + +Q1 = Path(__file__).resolve().parent +OUT = Q1 / "results" / "model_comparison_v2" +MODALITIES = ("text", "audio", "vision", "speech") +METHODS = ("B0", "B1", "B2", "B3", "B4") + + +def digest(path: Path) -> str: + h = hashlib.sha256() + with path.open("rb") as stream: + for block in iter(lambda: stream.read(1024 * 1024), b""): + h.update(block) + return h.hexdigest() + + +def edges_from_bounds(bounds: np.ndarray) -> np.ndarray: + return np.concatenate((bounds[:1, 0], bounds[:, 1])).astype(np.float32) + + +def as_view(views: dict[str, dict[str, np.ndarray]], bounds: np.ndarray) -> cm.View: + return cm.View( + features={name: views[name]["x"].astype(np.float32) for name in MODALITIES}, + observed={name: views[name]["mask"].astype(bool) for name in MODALITIES}, + coverage={name: views[name]["coverage"].astype(np.float32) for name in MODALITIES}, + edges=edges_from_bounds(bounds), + ) + + +def load_rows(records: list[dict[str, Any]]) -> tuple[list[dict[str, Any]], list[cm.View], list[dict[str, np.ndarray]], list[cm.View], list[cm.View]]: + rows, views, dynamics = [], [], [] + feature_ids = {json.loads(line)["sample_id"] for line in (q1_io.FEATURE_DIR / "manifest_q1.jsonl").read_text(encoding="utf-8").splitlines()} + record_ids = [record["sample_id"] for record in records] + if len(set(record_ids)) != len(record_ids) or set(record_ids) != feature_ids: + raise ValueError("Q1 labels and V2 feature manifest keys are not a one-to-one match") + for record in records: + sample = q1_io.load_sample(record["sample_id"]) + base = {name: q1_io.get_view(sample, name, "sec") for name in ("text", "audio", "vision")} + base["speech"] = q1_io.get_view(sample, "speech", "sec") + vision_b1 = q1_io.get_view(sample, "vision", "sec", geometry_aware=True) + b1 = {**base, "vision": vision_b1} + posterior = {**b1, "text": q1_io.get_view(sample, "text", "posterior")} + rows.append({**record, "duration_s": float(sample["_meta"]["duration_s"])}) + # Every model branch shares the same physical primary time bounds. + bounds = sample["views_sec_time_bounds_s"].astype(np.float32) + views.append(as_view(base, bounds)) + views.append(as_view(b1, bounds)) + views.append(as_view(posterior, bounds)) + with np.load(sample["_path"], allow_pickle=False) as artifact: + dynamics.append({"x": artifact["views_dynamics_x"].astype(np.float32), "mask": artifact["views_dynamics_mask"].astype(bool), "bounds": artifact["views_dynamics_time_bounds_s"].astype(np.float32)}) + # Flatten rows as [B0,B1,B2] per sample into three separate lists. + n = len(records) + return rows, [views[3*i] for i in range(n)], dynamics, [views[3*i+1] for i in range(n)], [views[3*i+2] for i in range(n)] + + +def fit_scaler(views: list[cm.View], indices: np.ndarray, mode: str) -> dict[str, tuple[np.ndarray, np.ndarray]]: + scalers = {} + for name in MODALITIES: + d = views[int(indices[0])].features[name].shape[1] + center = np.zeros(d, np.float64) + scale = np.ones(d, np.float64) + for j in range(d): + chunks = [views[int(i)].features[name][:, j][views[int(i)].observed[name][:, j]] for i in indices] + chunks = [x for x in chunks if len(x)] + if not chunks: + continue + values = np.concatenate(chunks).astype(np.float64) + if mode == "robust": + center[j] = np.median(values) + mad = 1.4826 * np.median(np.abs(values - center[j])) + scale[j] = mad if mad > 1e-8 else (np.std(values) if np.std(values) > 1e-8 else 1.0) + else: + center[j] = np.mean(values) + scale[j] = np.std(values) if np.std(values) > 1e-8 else 1.0 + scalers[name] = (center.astype(np.float32), scale.astype(np.float32)) + return scalers + + +def scale_view(view: cm.View, scalers: dict[str, tuple[np.ndarray, np.ndarray]], robust: bool) -> cm.View: + result = {} + for name in MODALITIES: + center, scale = scalers[name] + values = (view.features[name] - center) / scale + if robust: + values = np.clip(values, -8.0, 8.0) + result[name] = np.where(view.observed[name], values, 0.0).astype(np.float32) + return cm.View(result, view.observed, view.coverage, view.edges) + + +def pool_progress(view: cm.View, include_speech: bool) -> np.ndarray: + duration = float(view.edges[-1]) + progress = np.linspace(0.0, duration, 6) + centers = (view.edges[:-1] + view.edges[1:]) / 2 + lengths = np.diff(view.edges) + pooled = [] + names = ("text", "audio", "vision") + (("speech",) if include_speech else ()) + for name in names: + values = view.features[name] + mask = view.observed[name] + coverage = view.coverage[name] + segments = [] + for left, right in zip(progress[:-1], progress[1:]): + overlap = np.maximum(0.0, np.minimum(view.edges[1:], right) - np.maximum(view.edges[:-1], left)) + weight = overlap[:, None] * coverage * mask + den = weight.sum(axis=0) + out = np.zeros(values.shape[1], np.float32) + good = den > 0 + if good.any(): + out[good] = (values * weight).sum(axis=0)[good] / den[good] + segments.append(out) + pooled.append(np.stack(segments).reshape(-1)) + return np.concatenate(pooled).astype(np.float32) + + +def pool_dynamics(item: dict[str, np.ndarray], duration: float) -> np.ndarray: + bounds = item["bounds"] + values = item["x"] + valid = item["mask"] + centers = bounds[:, 0].mean(axis=1) + grid_length = bounds[:, 0, 1] - bounds[:, 0, 0] + progress = np.linspace(0.0, duration, 6) + result = [] + for left, right in zip(progress[:-1], progress[1:]): + sel = (centers >= left) & (centers < right) + for branch in range(2): + ok = sel & valid[:, branch] + weights = grid_length[ok] + if ok.any() and weights.sum() > 0: + result.extend(np.average(values[ok, branch], axis=0, weights=weights).tolist()) + result.append(float(min(1.0, weights.sum() / max(right - left, 1e-8)))) + else: + result.extend([0.0] * 6) + result.append(0.0) + return np.asarray(result, np.float32) + + +def fit_dynamic_scaler(values: np.ndarray, indices: np.ndarray) -> tuple[np.ndarray, np.ndarray, np.ndarray]: + center = np.zeros(values.shape[1], np.float32) + scale = np.ones(values.shape[1], np.float32) + is_signature = np.ones(values.shape[1], bool) + # In each 14-column block, the final column is a measured coverage fraction. + is_signature[np.arange(6, values.shape[1], 7)] = False + for j in np.flatnonzero(is_signature): + coverage_j = (j // 7) * 7 + 6 + observed = values[indices, coverage_j] > 0 + vals = values[indices[observed], j] + if not len(vals): + continue + center[j] = np.median(vals) + mad = 1.4826 * np.median(np.abs(vals - center[j])) + scale[j] = mad if mad > 1e-8 else (np.std(vals) if np.std(vals) > 1e-8 else 1.0) + return center, scale, is_signature + + +def scale_dynamic(values: np.ndarray, params: tuple[np.ndarray, np.ndarray, np.ndarray]) -> np.ndarray: + center, scale, signature = params + result = values.copy() + result[:, signature] = np.clip((result[:, signature] - center[signature]) / scale[signature], -8.0, 8.0) + # Preserve zeros in missing signature blocks. + for block in range(10): + coverage_col = block * 7 + 6 + result[result[:, coverage_col] <= 0, block * 7:block * 7 + 6] = 0.0 + return result.astype(np.float32) + + +def metrics(y_class: np.ndarray, p_class: np.ndarray, y_value: np.ndarray, p_value: np.ndarray) -> dict[str, float]: + pearson = float(np.corrcoef(y_value, p_value)[0, 1]) if np.std(p_value) > 1e-12 else math.nan + return { + "accuracy": float(accuracy_score(y_class, p_class)), + "macro_f1": float(f1_score(y_class, p_class, labels=[0, 1, 2], average="macro", zero_division=0)), + "mae": float(mean_absolute_error(y_value, p_value)), + "rmse": float(np.sqrt(mean_squared_error(y_value, p_value))), + "pearson": pearson, + } + + +def write_csv(path: Path, rows: list[dict[str, Any]]) -> None: + if not rows: + return + path.parent.mkdir(parents=True, exist_ok=True) + with path.open("w", encoding="utf-8-sig", newline="") as stream: + writer = csv.DictWriter(stream, fieldnames=list(rows[0])) + writer.writeheader() + writer.writerows(rows) + + +def main() -> None: + parser = argparse.ArgumentParser() + parser.add_argument("--bootstrap-repeats", type=int, default=2000) + args = parser.parse_args() + records = cm._read_labels(cm.LABEL_FILE) + rows, b0, dynamics, b1, b2 = load_rows(records) + y_class = np.asarray([r["polarity"] for r in rows], np.int64) + y_value = np.asarray([r["sentiment"] for r in rows], np.float64) + groups = np.asarray([r["video_id"] for r in rows], str) + durations = np.asarray([r["duration_s"] for r in rows], np.float64) + dynamic_values = np.stack([pool_dynamics(d, durations[i]) for i, d in enumerate(dynamics)]) + variants = {"B0": b0, "B1": b1, "B2": b2, "B3": b1, "B4": b1} + splitter = GroupKFold(n_splits=cm.N_FOLDS) + folds = list(splitter.split(np.zeros(len(rows)), y_class, groups)) + class_pred = {m: np.full(len(rows), -1, np.int64) for m in METHODS} + value_pred = {m: np.full(len(rows), np.nan, np.float64) for m in METHODS} + fold_rows = [] + split_rows = [] + for fold, (train_idx, valid_idx) in enumerate(folds, start=1): + if set(groups[train_idx]) & set(groups[valid_idx]): + raise ValueError("video group leakage in Q1 folds") + for i in valid_idx: + split_rows.append({"sample_id": rows[i]["sample_id"], "video_id": groups[i], "fold": fold, "split": "valid_oof"}) + for method in METHODS: + source = variants[method] + robust = method != "B0" + scaler = fit_scaler(source, train_idx, "robust" if robust else "standard") + scaled = [scale_view(v, scaler, robust) for v in source] + include_speech = method == "B4" + x_train = np.stack([pool_progress(scaled[i], include_speech) for i in train_idx]) + x_valid = np.stack([pool_progress(scaled[i], include_speech) for i in valid_idx]) + if method == "B3": + dyn_scaler = fit_dynamic_scaler(dynamic_values, train_idx) + dyn_scaled = scale_dynamic(dynamic_values, dyn_scaler) + x_train = np.column_stack((x_train, dyn_scaled[train_idx])) + x_valid = np.column_stack((x_valid, dyn_scaled[valid_idx])) + clf = LogisticRegression(C=0.05, max_iter=2500, solver="lbfgs", random_state=cm.SEED) + clf.fit(x_train, y_class[train_idx]) + p_cls = clf.predict(x_valid) + reg = Ridge(alpha=25.0, solver="lsqr") + reg.fit(x_train, y_value[train_idx]) + p_val = np.clip(reg.predict(x_valid), -3.0, 3.0) + class_pred[method][valid_idx] = p_cls + value_pred[method][valid_idx] = p_val + met = metrics(y_class[valid_idx], p_cls, y_value[valid_idx], p_val) + fold_rows.append({"method": method, "fold": fold, "train_samples": len(train_idx), "valid_samples": len(valid_idx), "train_video_groups": len(set(groups[train_idx])), "valid_video_groups": len(set(groups[valid_idx])), "feature_dimension": int(x_train.shape[1]), **met}) + print(f"fold {fold}/{cm.N_FOLDS} complete", flush=True) + + summary = [] + prediction_rows = [] + for method in METHODS: + overall = metrics(y_class, class_pred[method], y_value, value_pred[method]) + fold = [r for r in fold_rows if r["method"] == method] + row = {"method": method, "sample_count": len(rows), "video_group_count": len(set(groups)), **{f"oof_{k}": v for k, v in overall.items()}} + for key in ("accuracy", "macro_f1", "mae", "rmse", "pearson"): + vals = np.asarray([r[key] for r in fold], np.float64) + row[f"fold_{key}_mean"] = float(np.nanmean(vals)) + row[f"fold_{key}_sd"] = float(np.nanstd(vals, ddof=1)) + summary.append(row) + for i, record in enumerate(rows): + line = {"sample_id": record["sample_id"], "video_id": record["video_id"], "clip_id": record["clip_id"], "true_polarity": int(y_class[i]), "true_sentiment": float(y_value[i])} + for method in METHODS: + line[f"{method}_predicted_polarity"] = int(class_pred[method][i]) + line[f"{method}_predicted_sentiment"] = float(value_pred[method][i]) + prediction_rows.append(line) + + rng = np.random.default_rng(cm.SEED + 880) + unique_groups = np.unique(groups) + group_ix = {g: np.flatnonzero(groups == g) for g in unique_groups} + deltas = [] + reference = "B1" + for method in METHODS: + if method == reference: + continue + samples = {metric: [] for metric in ("accuracy", "macro_f1", "mae", "rmse", "pearson")} + for _ in range(args.bootstrap_repeats): + selected_groups = rng.choice(unique_groups, size=len(unique_groups), replace=True) + ix = np.concatenate([group_ix[g] for g in selected_groups]) + base = metrics(y_class[ix], class_pred[reference][ix], y_value[ix], value_pred[reference][ix]) + alt = metrics(y_class[ix], class_pred[method][ix], y_value[ix], value_pred[method][ix]) + for key in samples: + samples[key].append(alt[key] - base[key]) + for key, values in samples.items(): + vals = np.asarray(values, np.float64) + deltas.append({"comparison": f"{method}-{reference}", "metric": key, "reference": reference, "estimate_delta": float(np.nanmedian(vals)), "ci95_low": float(np.nanpercentile(vals, 2.5)), "ci95_high": float(np.nanpercentile(vals, 97.5)), "bootstrap_repeats": args.bootstrap_repeats, "unit": "video_id"}) + + OUT.mkdir(parents=True, exist_ok=True) + write_csv(OUT / "comparison_summary.csv", summary) + write_csv(OUT / "fold_metrics.csv", fold_rows) + write_csv(OUT / "oof_predictions.csv", prediction_rows) + write_csv(OUT / "split_assignments.csv", sorted(split_rows, key=lambda r: r["sample_id"])) + write_csv(OUT / "group_bootstrap_deltas.csv", deltas) + manifest = {"version": "E题V2 Q1 B0-B4", "samples": len(rows), "video_groups": int(len(unique_groups)), "folds": cm.N_FOLDS, "grouping": "video_id GroupKFold; train/valid group disjoint", "scalers": "B0 train-fold mean/std; B1-B4 train-fold median/MAD; no held-fold fitting", "classifier": "LogisticRegression C=0.05", "regressor": "Ridge alpha=25", "branches": {"B0": "quality-weighted physical projection", "B1": "B0 plus train-fold robust scale and SO(3)/unit-gaze aggregation", "B2": "B1 plus CTC forward-backward text occupancy", "B3": "B1 plus native-row level-2 dynamics", "B4": "B1 plus frozen Wav2Vec2 auxiliary representation"}, "B5": "query H_time audit only; not predictive score", "B6": "content probe disabled", "feature_manifest_sha256": digest(q1_io.FEATURE_DIR / "feature_manifest.json"), "source_run_manifest": "features_v2/manifest_q1.jsonl", "bootstrap_repeats": args.bootstrap_repeats} + (OUT / "run_manifest.json").write_text(json.dumps(manifest, ensure_ascii=False, indent=2), encoding="utf-8") + report = ["# Q1 V2 B0-B4 对照", "", "本报告使用 `features_v2/` 的 100 个样本，以 `video_id` 做五折 GroupKFold。B0–B4 的缩放器只在各折训练部分拟合。分数是情感信息探针，不是真实对齐边界准确率。", "", "| 分支 | OOF Accuracy | OOF Macro-F1 | OOF MAE | OOF RMSE | OOF Pearson |", "|---|---:|---:|---:|---:|---:|"] + for row in summary: + report.append(f"| {row['method']} | {row['oof_accuracy']:.4f} | {row['oof_macro_f1']:.4f} | {row['oof_mae']:.4f} | {row['oof_rmse']:.4f} | {row['oof_pearson']:.4f} |") + report += ["", "B5 通过词查询 CSR 矩阵进行物理来源核查；没有人工边界真值，因此未报告边界误差或后验校准率。B6 内容探针未启用。视觉 17 维来自 OpenFace 2.2.0 AU 输出，不是 MediaPipe 代理。"] + (OUT / "report.md").write_text("\n".join(report) + "\n", encoding="utf-8") + print("Q1 V2 comparison:", [(r["method"], round(r["oof_accuracy"], 4), round(r["oof_macro_f1"], 4), round(r["oof_mae"], 4)) for r in summary], flush=True) + + +if __name__ == "__main__": + main() diff --git a/math/Q1/features_v2/-3g5yACwYnA__13.npz b/math/Q1/features_v2/-3g5yACwYnA__13.npz new file mode 100644 index 0000000..8347cd0 Binary files /dev/null and b/math/Q1/features_v2/-3g5yACwYnA__13.npz differ diff --git a/math/Q1/features_v2/-3g5yACwYnA__2.npz b/math/Q1/features_v2/-3g5yACwYnA__2.npz new file mode 100644 index 0000000..c9c00cd Binary files /dev/null and b/math/Q1/features_v2/-3g5yACwYnA__2.npz differ diff --git a/math/Q1/features_v2/-3g5yACwYnA__3.npz b/math/Q1/features_v2/-3g5yACwYnA__3.npz new file mode 100644 index 0000000..07cd43c Binary files /dev/null and b/math/Q1/features_v2/-3g5yACwYnA__3.npz differ diff --git a/math/Q1/features_v2/-3g5yACwYnA__9.npz 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disabled,features_v2/-iRBcNs9oI8__6.npz,030b0b8d8d4ae47799432ab71b66fcc881f077c5b0feef892c1f146dc0a592e3,success,c1b931d6d64931209313a8b2f0e501069e2056939a15e900c1ee0762ba3c0617 +-iRBcNs9oI8/9,-iRBcNs9oI8,9,text,3.4159998893737793,1.4199999868869781,5,768,35,768,fixed 0.1 s physical grid; direct native interval projection,"word-level, variable duration; fixed-transcript CTC source interval",0.41569087613386674,none,True,1.0,-iRBcNs9oI8__9.npz::native_text_*quality*,not_applicable,not_applicable,features_v2/-iRBcNs9oI8__9.npz,352bdcc73d3622d6abac1b09f2039b211d15b9bf7acee66f0b07783c9b7a4c74,success,c1b931d6d64931209313a8b2f0e501069e2056939a15e900c1ee0762ba3c0617 +-iRBcNs9oI8/9,-iRBcNs9oI8,9,audio,3.4159998893737793,3.3255532545012394,338,74,35,74,fixed 0.1 s physical grid; direct native interval projection,native 10 ms feature step; 25 ms windows; context ranges retained separately,0.9735226470135745,F0/HNR naturally undefined or unavailable in 180 rows; support masks 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disabled,features_v2/-lzEya4AM_4__5.npz,3b74de8d0e66fd754594f05985e5af3480adcc03555f79225d3b727cb4bed043,success,c1b931d6d64931209313a8b2f0e501069e2056939a15e900c1ee0762ba3c0617 +-lzEya4AM_4/6,-lzEya4AM_4,6,text,14.7919921875,10.32000094652176,43,768,148,768,fixed 0.1 s physical grid; direct native interval projection,"word-level, variable duration; fixed-transcript CTC source interval",0.6976748510753471,none,True,1.0,-lzEya4AM_4__6.npz::native_text_*quality*,not_applicable,not_applicable,features_v2/-lzEya4AM_4__6.npz,ff5da5afb551001d58100ed2471caea51c741046d5396957efbf40082307ca18,success,c1b931d6d64931209313a8b2f0e501069e2056939a15e900c1ee0762ba3c0617 +-lzEya4AM_4/6,-lzEya4AM_4,6,audio,14.7919921875,14.509920233004806,1475,74,148,74,fixed 0.1 s physical grid; direct native interval projection,native 10 ms feature step; 25 ms windows; context ranges retained separately,0.9809307663957827,F0/HNR naturally undefined or unavailable in 853 rows; support masks retained,True,1.0,-lzEya4AM_4__6.npz::native_audio_*quality*,-lzEya4AM_4__6.npz::query_word_audio_H_time,content probe disabled,features_v2/-lzEya4AM_4__6.npz,ff5da5afb551001d58100ed2471caea51c741046d5396957efbf40082307ca18,success,c1b931d6d64931209313a8b2f0e501069e2056939a15e900c1ee0762ba3c0617 +-lzEya4AM_4/6,-lzEya4AM_4,6,vision,14.7919921875,14.683000266551971,443,35,148,35,fixed 0.1 s physical grid; direct native interval projection,native OpenFace frame timestamps and frame indices,0.9926316942595378,OpenFace confidence/success gate rejected 2 native frames,True,1.0,-lzEya4AM_4__6.npz::native_vision_*quality*,-lzEya4AM_4__6.npz::query_word_vision_H_time,content probe disabled,features_v2/-lzEya4AM_4__6.npz,ff5da5afb551001d58100ed2471caea51c741046d5396957efbf40082307ca18,success,c1b931d6d64931209313a8b2f0e501069e2056939a15e900c1ee0762ba3c0617 +-mJ2ud6oKI8/1,-mJ2ud6oKI8,1,text,6.103000164031982,1.9600001871585846,13,768,62,768,fixed 0.1 s physical grid; direct native interval 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189, + 190, + 191, + 192, + 193, + 194, + 195, + 196, + 197, + 198, + 199, + 200, + 201 + ], + "vision_source_rows": [ + 56, + 57, + 58, + 59, + 60, + 61 + ], + "manual_boundary_audit": "not available; no empirical boundary error or calibration claimed", + "vision_backend": "OpenFace 2.2.0" +} \ No newline at end of file diff --git a/math/Q1/pyproject.toml b/math/Q1/pyproject.toml index f4afaf6..82697b4 100644 --- a/math/Q1/pyproject.toml +++ b/math/Q1/pyproject.toml @@ -3,8 +3,8 @@ name = "math-q1-comparison" version = "0.1.0" requires-python = ">=3.14" dependencies = [ + "librosa>=1.0.0", "matplotlib>=3.11.2", - "mediapipe>=1.0.1", "numpy>=2.5.2", "opencv-python-headless>=5.0.0.93", "openpyxl>=3.1.5", diff --git a/math/Q1/q1_io.py b/math/Q1/q1_io.py new file mode 100644 index 0000000..e0fea60 --- /dev/null +++ b/math/Q1/q1_io.py @@ -0,0 +1,230 @@ +"""Read and derive Q1 V2 feature views from the native-source artifacts.""" +from __future__ import annotations + +import json +import re +from pathlib import Path +from typing import Any + +import numpy as np +from scipy import sparse + +Q1_DIR = Path(__file__).resolve().parent +FEATURE_DIR = Q1_DIR / "features_v2" +MODALITIES = ("text", "audio", "vision") +FEATURE_DIMS = {"text": 768, "audio": 74, "vision": 35, "speech": 768} + + +def load_sample(sample_id: str, feature_dir: Path = FEATURE_DIR) -> dict[str, Any]: + """Load one sample by `video_id/clip_id` and return arrays plus metadata.""" + manifest = feature_dir / "manifest_q1.jsonl" + found = None + for line in manifest.read_text(encoding="utf-8").splitlines(): + row = json.loads(line) + if row["sample_id"] == sample_id: + found = row + break + if found is None: + raise KeyError(f"sample_id not found: {sample_id}") + path = Q1_DIR / found["feature_path"] + with np.load(path, allow_pickle=False) as archive: + result = {name: archive[name] for name in archive.files} + result["_path"] = path + result["_manifest"] = found + result["_meta"] = json.loads(str(result["meta_json"])) + return result + + +def csr_from_sample(sample: dict[str, Any], prefix: str) -> sparse.csr_matrix: + """Reconstruct a stored sparse alignment/query map.""" + shape = tuple(int(v) for v in sample[f"{prefix}_shape"]) + return sparse.csr_matrix( + ( + sample[f"{prefix}_data"].astype(np.float32), + sample[f"{prefix}_indices"].astype(np.int32), + sample[f"{prefix}_indptr"].astype(np.int32), + ), + shape=shape, + ) + + +def _native(sample: dict[str, Any], modality: str) -> tuple[np.ndarray, np.ndarray, np.ndarray, np.ndarray, np.ndarray]: + if modality == "text": + return ( + sample["native_text_features"].astype(np.float32), + np.broadcast_to(sample["native_text_observed"][:, None], sample["native_text_features"].shape), + sample["native_text_intervals"].astype(np.float32), + sample["native_text_quality_effective"].astype(np.float32), + sample["native_text_quality_available"].astype(bool), + ) + if modality in ("audio", "vision"): + return ( + sample[f"native_{modality}_features"].astype(np.float32), + sample[f"native_{modality}_mask"].astype(bool), + sample[f"native_{modality}_intervals"].astype(np.float32), + sample[f"native_{modality}_quality"].astype(np.float32), + np.full(len(sample[f"native_{modality}_times"]), bool(sample[f"native_{modality}_quality_available"]), dtype=bool), + ) + if modality == "speech": + meta = sample["_meta"] + safe = lambda value: re.sub(r"[^A-Za-z0-9_.-]+", "_", str(value)) + path = Q1_DIR / "cache" / "native" / f"{safe(meta['video_id'])}__{safe(meta['clip_id'])}.npz" + if not path.is_file(): + raise FileNotFoundError(f"B4 speech source cache is unavailable: {path}") + with np.load(path, allow_pickle=False) as archive: + values = archive["speech_features"].astype(np.float32) + times = sample["native_ctc_times"].astype(np.float32) + if len(values) != len(times): + raise ValueError("B4 speech rows do not match the stored CTC timestamps") + step = 320.0 / 16000.0 + intervals = np.column_stack((np.maximum(0.0, times - step / 2), np.minimum(float(meta["duration_s"]), times + step / 2))).astype(np.float32) + return values, np.isfinite(values), intervals, np.ones(len(values), np.float32), np.zeros(len(values), bool) + raise ValueError(f"unknown modality: {modality}") + + +def _aggregate( + values: np.ndarray, + observed: np.ndarray, + source_intervals: np.ndarray, + quality: np.ndarray, + target_intervals: np.ndarray, + quality_available: np.ndarray | None = None, +) -> dict[str, np.ndarray]: + """Quality-weight B0 means while keeping physical coverage and availability separate.""" + n, d = len(target_intervals), values.shape[1] + mean = np.zeros((n, d), np.float32) + var = np.zeros((n, d), np.float32) + count = np.zeros((n, d), np.uint8) + coverage = np.zeros((n, d), np.float32) + qbar = np.ones((n, d), np.float32) + qavail = np.zeros((n, d), np.float32) + available = np.zeros(len(values), bool) if quality_available is None else np.asarray(quality_available, bool) + mask = np.zeros((n, d), bool) + for i, (left, right) in enumerate(target_intervals): + width = float(right - left) + if width <= 0 or not len(source_intervals): + continue + overlap = np.maximum( + 0.0, + np.minimum(source_intervals[:, 1], right) - np.maximum(source_intervals[:, 0], left), + ) + physical = overlap[:, None] * observed + weighted = physical * quality[:, None] + total = weighted.sum(axis=0) + valid = total > 0 + if valid.any(): + weighted_sum = (values * weighted).sum(axis=0) + weighted_sq = (np.square(values) * weighted).sum(axis=0) + mean[i, valid] = (weighted_sum[valid] / total[valid]).astype(np.float32) + var[i, valid] = np.maximum(0.0, weighted_sq[valid] / total[valid] - mean[i, valid] ** 2) + mask[i, valid] = True + physical_total = physical.sum(axis=0) + physical_valid = physical_total > 0 + qbar[i, physical_valid] = weighted.sum(axis=0)[physical_valid] / physical_total[physical_valid] + qavail[i, physical_valid] = (physical * available[:, None]).sum(axis=0)[physical_valid] / physical_total[physical_valid] + coverage[i] = np.minimum(1.0, physical_total / width) + count[i] = np.minimum(255, ((overlap[:, None] > 0) & observed).sum(axis=0)).astype(np.uint8) + return { + "x": mean.astype(np.float16), + "var": var.astype(np.float32), + "count": count, + "coverage": coverage, + "mask": mask, + "quality_mean": qbar.astype(np.float32), + "quality_available_fraction": qavail.astype(np.float32), + } + + +def get_view( + sample: dict[str, Any], + modality: str, + view: str = "sec", + context_s: float | None = None, + geometry_aware: bool = False, +) -> dict[str, np.ndarray]: + """Return `sec`, `phase50`, `word`, `multi`, or `posterior` features. + + `multi` is always aggregated from native rows around each 0.1 s bin midpoint. + For it, set `context_s` to one of 0.1, 0.3, or 0.7. + """ + if modality not in (*MODALITIES, "speech"): + raise ValueError(f"unknown modality: {modality}") + if view in ("sec", "phase50", "word"): + bounds = sample[f"views_{view}_time_bounds_s"].astype(np.float32) + if modality == "speech": + values, observed, intervals, quality, available = _native(sample, modality) + return {**_aggregate(values, observed, intervals, quality, bounds, available), "time_bounds_s": bounds} + prefix = f"views_{view}_{modality}_" + result = { + "x": sample[prefix + "x"], + "var": sample[prefix + "var"], + "count": sample[prefix + "count"], + "coverage": sample[prefix + "coverage_u8"].astype(np.float32) / 255.0, + "mask": sample[prefix + "mask"].astype(bool), + "quality_mean": sample[prefix + "qbar"].astype(np.float32), + "quality_available_fraction": sample[prefix + "quality_available_fraction"].astype(np.float32), + "time_bounds_s": bounds, + } + if view == "sec" and modality == "vision" and geometry_aware: + result["x"] = sample["views_sec_vision_b1_x"] + result["mask"] = sample["views_sec_vision_b1_mask"].astype(bool) + return result + if view == "multi": + if context_s not in (0.1, 0.3, 0.7): + raise ValueError("context_s must be one of 0.1, 0.3, or 0.7") + centers = sample["views_sec_time_bounds_s"].astype(np.float32).mean(axis=1) + duration = float(sample["_meta"]["duration_s"]) + bounds = np.column_stack((np.maximum(0.0, centers - context_s / 2), np.minimum(duration, centers + context_s / 2))).astype(np.float32) + values, observed, intervals, quality, available = _native(sample, modality) + return {**_aggregate(values, observed, intervals, quality, bounds, available), "time_bounds_s": bounds} + if view == "posterior": + if modality != "text": + raise ValueError("posterior projection is defined for text only") + return posterior_text_view(sample) + raise ValueError(f"unknown view: {view}") + + +def posterior_text_view(sample: dict[str, Any]) -> dict[str, np.ndarray]: + """Project CTC forward-backward word occupancy directly to the 0.1 s grid.""" + edges = sample["views_sec_time_bounds_s"].astype(np.float32) + words = sample["native_text_features"].astype(np.float32) + word_ok = sample["native_text_observed"].astype(bool) + occupancy = sample["native_ctc_occupancy"].astype(np.float32) + times = sample["native_ctc_times"].astype(np.float32) + if occupancy.ndim != 2 or occupancy.shape[1] != len(words): + raise ValueError("CTC occupancy word dimension does not match the native text rows") + step = 320.0 / 16000.0 + half = step / 2 + duration = float(sample["_meta"]["duration_s"]) + source = np.column_stack((np.maximum(0.0, times - half), np.minimum(duration, times + half))).astype(np.float32) + n, d = len(edges), words.shape[1] + result = np.zeros((n, d), np.float32) + var = np.zeros((n, d), np.float32) + count = np.zeros(n, np.uint8) + coverage = np.zeros(n, np.float32) + mask = np.zeros(n, bool) + mass_by_word = np.zeros((n, len(words)), np.float32) + for i, (left, right) in enumerate(edges): + overlap = np.maximum(0.0, np.minimum(source[:, 1], right) - np.maximum(source[:, 0], left)) + mass_by_word[i] = (occupancy * overlap[:, None]).sum(axis=0) + w = mass_by_word[i] * word_ok + total = float(w.sum()) + if total > 0: + normalized = w / total + result[i] = normalized @ words + centered = words - result[i] + var[i] = (normalized[:, None] * np.square(centered)).sum(axis=0) + mask[i] = True + count[i] = min(255, int(np.count_nonzero(w > 0))) + coverage[i] = min(1.0, total / max(float(right - left), 1e-8)) + return { + "x": result.astype(np.float16), + "var": var, + "count": np.broadcast_to(count[:, None], result.shape).copy(), + "coverage": np.broadcast_to(coverage[:, None], result.shape).copy(), + "mask": np.broadcast_to(mask[:, None], result.shape).copy(), + "quality_mean": np.ones_like(result, dtype=np.float32), + "quality_available_fraction": np.zeros_like(result, dtype=np.float32), + "word_posterior_mass": mass_by_word, + "time_bounds_s": edges, + } diff --git a/math/Q1/results/alignment_query_example.json b/math/Q1/results/alignment_query_example.json new file mode 100644 index 0000000..40d8ebe --- /dev/null +++ b/math/Q1/results/alignment_query_example.json @@ -0,0 +1,48 @@ +{ + "sample_id": "-iRBcNs9oI8/8", + "selection": "manually selected example with valid audio and vision query maps", + "duration_s": 8.093000411987305, + "word_count": 21, + "words": [ + "I've", + "drawn", + "this", + "man", + "here,", + "and", + "if", + "you", + "can", + "tell,", + "he", + "has", + "a", + "lot", + "of", + "big", + "muscles,", + "he", + "looks", + "very", + "strong" + ], + "audio_query_shape": [ + 21, + 803 + ], + "audio_query_nnz": 495, + "audio_query_mapped_words": 21, + "vision_query_shape": [ + 21, + 241 + ], + "vision_query_nnz": 160, + "vision_query_mapped_words": 21, + "audio_query_feature_validity_channel": "log_energy (audio feature dimension 66)", + "vision_query_feature_validity_channel": "OpenFace AU12 intensity (vision feature dimension 10)", + "alignment_semantics": "per-word normalized overlap between stored CTC word intervals and native source intervals; no learned content similarity", + "coordinate_axes_shown": false, + "color_scale": "shared square-root intensity transform for visibility; original overlap weights retained", + "word_label_positions": "actual transcript labels placed at their CTC word-interval centers on the source-time axis", + "image": "/home/gloamxun/modeling_zhaocui/math/Q1/results/alignment_query_example.png" +} diff --git a/math/Q1/results/alignment_query_example.png b/math/Q1/results/alignment_query_example.png new file mode 100644 index 0000000..2edd99c Binary files /dev/null and b/math/Q1/results/alignment_query_example.png differ diff --git a/math/Q1/results/model_comparison/comparison.png b/math/Q1/results/model_comparison/comparison.png deleted file mode 100644 index 556343b..0000000 Binary files a/math/Q1/results/model_comparison/comparison.png and /dev/null differ diff --git a/math/Q1/results/model_comparison/comparison_summary.csv b/math/Q1/results/model_comparison/comparison_summary.csv deleted file mode 100644 index c001e08..0000000 --- a/math/Q1/results/model_comparison/comparison_summary.csv +++ /dev/null @@ -1,6 +0,0 @@ -method,sample_count,video_group_count,oof_accuracy,oof_macro_f1,oof_mae,oof_pearson,fold_accuracy_mean,fold_accuracy_sd,fold_macro_f1_mean,fold_macro_f1_sd,fold_mae_mean,fold_mae_sd,fold_pearson_mean,fold_pearson_sd -B0,100,37,0.6,0.3612633181126332,0.5642678308486938,0.34585652345724877,0.6,0.1274754878398196,0.33701813174429807,0.09810807621270928,0.5642678308486938,0.15030090846290933,0.40788979900767275,0.06001860958324475 -B1,100,37,0.61,0.387431302270012,0.5989421024918556,0.23765809617297712,0.61,0.1341640786499874,0.3493607699490052,0.11905440418044842,0.5989421024918556,0.15750913261096855,0.281166840616461,0.14435440813423514 -B2,100,37,0.58,0.33061794334825517,0.588000754788518,0.2790493470006418,0.5800000000000001,0.14404860290887933,0.3128829195495862,0.08742851668319461,0.588000754788518,0.14204292727229248,0.3331122890661654,0.08879703094318196 -B3,100,37,0.59,0.3587962962962963,0.5997931832820177,0.23011191320162028,0.5900000000000001,0.12942179105544785,0.33257284523004604,0.09564119982991781,0.5997931832820177,0.15746511520951317,0.2803250178248575,0.13217248970127823 -B4,100,37,0.6,0.4222603610475464,0.59276591360569,0.19864510121331094,0.6,0.13693063937629155,0.3976841268630668,0.08882960164587973,0.59276591360569,0.16014796281119822,0.24000288610371706,0.14964617105964673 diff --git a/math/Q1/results/model_comparison/fold_metrics.csv b/math/Q1/results/model_comparison/fold_metrics.csv deleted file mode 100644 index 248683a..0000000 --- a/math/Q1/results/model_comparison/fold_metrics.csv +++ /dev/null @@ -1,26 +0,0 @@ -method,fold,train_samples,valid_samples,train_video_groups,valid_video_groups,accuracy,macro_f1,mae,pearson,feature_dimension -B0,1,80,20,31,6,0.75,0.29411764705882354,0.4224671095609665,0.39024875749849447,4385 -B1,1,80,20,31,6,0.75,0.29411764705882354,0.43092925772070884,0.3768780281745036,4385 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-B3,3,80,20,29,8,0.65,0.44334975369458124,0.6637263983488083,0.36870656729912815,4455 -B4,3,80,20,29,8,0.5,0.3956043956043956,0.6777055777609349,0.23098821201949785,8225 -B0,4,80,20,29,8,0.4,0.19047619047619047,0.5507291875779629,0.32319803952574416,4385 -B1,4,80,20,29,8,0.4,0.19047619047619047,0.6101470191031695,0.04446251878558958,4385 -B2,4,80,20,29,8,0.35,0.1728395061728395,0.5764139499515295,0.17960866044359325,4385 -B3,4,80,20,29,8,0.4,0.19047619047619047,0.6146079197525978,0.0589277387406542,4455 -B4,4,80,20,29,8,0.45,0.2792022792022792,0.607093845307827,0.018750134966085342,8225 -B0,5,80,20,29,8,0.6,0.39316239316239315,0.427672965824604,0.4759961702531348,4385 -B1,5,80,20,29,8,0.6,0.39316239316239315,0.46998393908143044,0.3640829457789559,4385 -B2,5,80,20,29,8,0.6,0.39316239316239315,0.4762579582631588,0.3999345205851506,4385 -B3,5,80,20,29,8,0.55,0.37777777777777777,0.4736050248146057,0.34852228624958836,4455 -B4,5,80,20,29,8,0.65,0.5221783047870004,0.45780793130397796,0.4075125228658822,8225 diff --git a/math/Q1/results/model_comparison/group_bootstrap_deltas.csv b/math/Q1/results/model_comparison/group_bootstrap_deltas.csv deleted file mode 100644 index b895fb3..0000000 --- a/math/Q1/results/model_comparison/group_bootstrap_deltas.csv +++ /dev/null @@ -1,17 +0,0 @@ -comparison,metric,reference_oof,method_oof,delta_oof,group_bootstrap_ci95_low,group_bootstrap_ci95_high,bootstrap_repeats -B0-B1,accuracy,0.61,0.6,-0.010000000000000009,-0.029710396039603987,0.0,2000 -B0-B1,macro_f1,0.387431302270012,0.3612633181126332,-0.02616798415737881,-0.08327057744765032,0.0,2000 -B0-B1,mae,0.5989421024918556,0.5642678308486938,-0.034674271643161836,-0.06304207975806683,-0.012443204964559182,2000 -B0-B1,pearson,0.23765809617297712,0.34585652345724877,0.10819842728427165,0.04340079372240924,0.19005024141624596,2000 -B2-B1,accuracy,0.61,0.58,-0.030000000000000027,-0.0648204607046071,0.0,2000 -B2-B1,macro_f1,0.387431302270012,0.33061794334825517,-0.05681335892175682,-0.10940517350156256,-0.0009457159449812041,2000 -B2-B1,mae,0.5989421024918556,0.588000754788518,-0.010941347703337656,-0.027305471624463586,0.004017100735475708,2000 -B2-B1,pearson,0.23765809617297712,0.2790493470006418,0.041391250827664705,-0.009244736549056344,0.10131359014731482,2000 -B3-B1,accuracy,0.61,0.59,-0.020000000000000018,-0.05154639175257736,0.0,2000 -B3-B1,macro_f1,0.387431302270012,0.3587962962962963,-0.02863500597371571,-0.07212177947137302,0.0,2000 -B3-B1,mae,0.5989421024918556,0.5997931832820177,0.000851080790162051,-0.004701075716562739,0.006246566925533936,2000 -B3-B1,pearson,0.23765809617297712,0.23011191320162028,-0.007546182971356841,-0.022226358336772584,0.005402452990031458,2000 -B4-B1,accuracy,0.61,0.6,-0.010000000000000009,-0.08080808080808077,0.06196073008849559,2000 -B4-B1,macro_f1,0.387431302270012,0.4222603610475464,0.034829058777534394,-0.051408708516982864,0.13655330256210496,2000 -B4-B1,mae,0.5989421024918556,0.59276591360569,-0.006176188886165668,-0.03045045264816862,0.015397113913740889,2000 -B4-B1,pearson,0.23765809617297712,0.19864510121331094,-0.039012994959666175,-0.1082683426423725,0.03034022099301614,2000 diff --git a/math/Q1/results/model_comparison/modality_summary.csv b/math/Q1/results/model_comparison/modality_summary.csv deleted file mode 100644 index 71fa296..0000000 --- a/math/Q1/results/model_comparison/modality_summary.csv +++ /dev/null @@ -1,301 +0,0 @@ -sample_id,video_id,clip_id,modality,source_duration_s,observed_duration_s_mean_dimension,native_length,native_dimension,main_grid_length,grid_step_s,grid_dimension,mean_grid_coverage,status,source_video_sha256 --3g5yACwYnA/13,-3g5yACwYnA,13,text,5.5139970779418945,2.946523889899254,15,768,56,0.1,768,0.7015532851219177,ok,aeb47627f59dce3d0a85a44ef35e4a3bc18211498e98c8c11cf60269646df24f --3g5yACwYnA/13,-3g5yACwYnA,13,audio,5.5139970779418945,5.445240411887298,540,74,56,0.1,74,0.9882608652114868,ok,aeb47627f59dce3d0a85a44ef35e4a3bc18211498e98c8c11cf60269646df24f --3g5yACwYnA/13,-3g5yACwYnA,13,vision,5.5139970779418945,5.5139970779418945,43,35,56,0.1,35,1.0,ok,aeb47627f59dce3d0a85a44ef35e4a3bc18211498e98c8c11cf60269646df24f --3g5yACwYnA/3,-3g5yACwYnA,3,text,14.388997077941895,7.041063531115653,29,768,144,0.1,768,0.6343300342559814,ok,eff8cfefba2425155f2b72656829b34b23be8bfe1dcbece384154f56818aa26d --3g5yACwYnA/3,-3g5yACwYnA,3,audio,14.388997077941895,14.260037878559858,1433,74,144,0.1,74,0.9912122488021851,ok,eff8cfefba2425155f2b72656829b34b23be8bfe1dcbece384154f56818aa26d --3g5yACwYnA/3,-3g5yACwYnA,3,vision,14.388997077941895,14.388997077941895,103,35,144,0.1,35,1.0,ok,eff8cfefba2425155f2b72656829b34b23be8bfe1dcbece384154f56818aa26d --3g5yACwYnA/2,-3g5yACwYnA,2,text,9.394009590148926,5.1430321040563305,14,768,94,0.1,768,0.7563282251358032,ok,0619c01f137d017c15c058176f18a575919189c7e81ebd2bfb993afdb86f3de7 --3g5yACwYnA/2,-3g5yACwYnA,2,audio,9.394009590148926,9.331671435768538,924,74,94,0.1,74,0.9936367273330688,ok,0619c01f137d017c15c058176f18a575919189c7e81ebd2bfb993afdb86f3de7 --3g5yACwYnA/2,-3g5yACwYnA,2,vision,9.394009590148926,9.394009590148926,78,35,94,0.1,35,1.0,ok,0619c01f137d017c15c058176f18a575919189c7e81ebd2bfb993afdb86f3de7 --3g5yACwYnA/9,-3g5yACwYnA,9,text,8.816991806030273,5.6415157541632714,21,768,89,0.1,768,0.6637077927589417,ok,b962573b12ed1f06d5533f6427c80dce2bae3a99dd332f6d3fcb32c579f3f016 --3g5yACwYnA/9,-3g5yACwYnA,9,audio,8.816991806030273,8.735654204761659,870,74,89,0.1,74,0.9912108778953552,ok,b962573b12ed1f06d5533f6427c80dce2bae3a99dd332f6d3fcb32c579f3f016 --3g5yACwYnA/9,-3g5yACwYnA,9,vision,8.816991806030273,8.816991806030273,75,35,89,0.1,35,1.0,ok,b962573b12ed1f06d5533f6427c80dce2bae3a99dd332f6d3fcb32c579f3f016 --3nNcZdcdvU/5,-3nNcZdcdvU,5,text,7.867969036102295,5.002839090395719,18,768,79,0.1,768,0.7357116341590881,ok,7ea53ad502b77be7d2ee4494dc23a9478c897792203cf887d546e83d584c1728 --3nNcZdcdvU/5,-3nNcZdcdvU,5,audio,7.867969036102295,7.843361772234375,779,74,79,0.1,74,0.9971166849136353,ok,7ea53ad502b77be7d2ee4494dc23a9478c897792203cf887d546e83d584c1728 --3nNcZdcdvU/5,-3nNcZdcdvU,5,vision,7.867969036102295,7.816666602730405,67,35,79,0.1,35,0.9904456734657288,ok,7ea53ad502b77be7d2ee4494dc23a9478c897792203cf887d546e83d584c1728 --HwX2H8Z4hY/2,-HwX2H8Z4hY,2,text,3.9820311069488525,2.40418455898877,8,768,40,0.1,768,0.6164926290512085,ok,920a1052c09ebd1eedba6dd1ccfecd80f56f6f0fdcdd1f6dd32b0d90bcb89358 --HwX2H8Z4hY/2,-HwX2H8Z4hY,2,audio,3.9820311069488525,3.9192059241395896,392,74,40,0.1,74,0.9881895780563354,ok,920a1052c09ebd1eedba6dd1ccfecd80f56f6f0fdcdd1f6dd32b0d90bcb89358 --HwX2H8Z4hY/2,-HwX2H8Z4hY,2,vision,3.9820311069488525,0.8653643131256102,27,35,40,0.1,35,0.9814813733100891,ok,920a1052c09ebd1eedba6dd1ccfecd80f56f6f0fdcdd1f6dd32b0d90bcb89358 --HwX2H8Z4hY/5,-HwX2H8Z4hY,5,text,5.6529951095581055,3.0192474961280813,10,768,57,0.1,768,0.7021505832672119,ok,8d61b7f5840a8bd403d9bc6c3cd49029ffc4e304cf9c7834735c1a6bb5fd369d --HwX2H8Z4hY/5,-HwX2H8Z4hY,5,audio,5.6529951095581055,5.595076320642555,555,74,57,0.1,74,0.9900854229927063,ok,8d61b7f5840a8bd403d9bc6c3cd49029ffc4e304cf9c7834735c1a6bb5fd369d 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--9y-fZ3swSY/8,-9y-fZ3swSY,8,audio,4.988996982574463,4.9497673825665816,492,74,50,0.1,74,0.9931800365447998,ok,6140d031e614b62a5d8df73346fef2417c28cee3501310aa95aa40d358b4b256 --9y-fZ3swSY/8,-9y-fZ3swSY,8,vision,4.988996982574463,3.688997030258178,37,35,50,0.1,35,0.9487179517745972,ok,6140d031e614b62a5d8df73346fef2417c28cee3501310aa95aa40d358b4b256 --AUZQgSxyPQ/2,-AUZQgSxyPQ,2,text,22.511003494262695,12.134252551943066,41,768,226,0.1,768,0.6386448740959167,ok,e09034b30bb4f8fb9f9c2568afc20f2a764e327fe6ef4e13f21804eaac51bb7b --AUZQgSxyPQ/2,-AUZQgSxyPQ,2,audio,22.511003494262695,22.31367928599184,2241,74,226,0.1,74,0.9917553663253784,ok,e09034b30bb4f8fb9f9c2568afc20f2a764e327fe6ef4e13f21804eaac51bb7b --AUZQgSxyPQ/2,-AUZQgSxyPQ,2,vision,22.511003494262695,22.511003494262695,144,35,226,0.1,35,1.0,ok,e09034b30bb4f8fb9f9c2568afc20f2a764e327fe6ef4e13f21804eaac51bb7b --HeZS2-Prhc/2,-HeZS2-Prhc,2,text,8.261979103088379,3.552112135011702,16,768,83,0.1,768,0.6830984950065613,ok,edb0fa22fdfbd990c8174764af78670bd2ecad799240d35d96a1124a3cd9dc0c --HeZS2-Prhc/2,-HeZS2-Prhc,2,audio,8.261979103088379,8.205439110059995,816,74,83,0.1,74,0.9933875799179077,ok,edb0fa22fdfbd990c8174764af78670bd2ecad799240d35d96a1124a3cd9dc0c --HeZS2-Prhc/2,-HeZS2-Prhc,2,vision,8.261979103088379,8.261979103088379,70,35,83,0.1,35,1.0,ok,edb0fa22fdfbd990c8174764af78670bd2ecad799240d35d96a1124a3cd9dc0c --MeTTeMJBNc/0,-MeTTeMJBNc,0,text,9.300000190734863,4.416411150246859,21,768,94,0.1,768,0.6400595903396606,ok,54e2097f7bdb455d243e72254e5af7ed16160739f2f3cfd22f57d2729ec1acbe --MeTTeMJBNc/0,-MeTTeMJBNc,0,audio,9.300000190734863,9.216486695006088,922,74,94,0.1,74,0.9939717650413513,ok,54e2097f7bdb455d243e72254e5af7ed16160739f2f3cfd22f57d2729ec1acbe --MeTTeMJBNc/0,-MeTTeMJBNc,0,vision,9.300000190734863,9.200000190734862,78,35,94,0.1,35,1.0,ok,54e2097f7bdb455d243e72254e5af7ed16160739f2f3cfd22f57d2729ec1acbe --MeTTeMJBNc/13,-MeTTeMJBNc,13,text,5.430013179779053,2.997564935684203,14,768,55,0.1,768,0.6661255359649658,ok,80c5d996e5d7b61c58e1fe32d706efcaf80c8c8cddb5c37a5c66d527786c2a44 --MeTTeMJBNc/13,-MeTTeMJBNc,13,audio,5.430013179779053,5.368323606413764,526,74,55,0.1,74,0.9918515682220459,ok,80c5d996e5d7b61c58e1fe32d706efcaf80c8c8cddb5c37a5c66d527786c2a44 --MeTTeMJBNc/13,-MeTTeMJBNc,13,vision,5.430013179779053,5.430013179779053,41,35,55,0.1,35,1.0,ok,80c5d996e5d7b61c58e1fe32d706efcaf80c8c8cddb5c37a5c66d527786c2a44 --MeTTeMJBNc/7,-MeTTeMJBNc,7,text,10.51699161529541,6.728291415888818,31,768,106,0.1,768,0.7313360571861267,ok,40716dc7402fd6398038eded58ce939ec76be6afbeea346b968bf4c427088f3a --MeTTeMJBNc/7,-MeTTeMJBNc,7,audio,10.51699161529541,10.441329748243898,1042,74,106,0.1,74,0.9934103488922119,ok,40716dc7402fd6398038eded58ce939ec76be6afbeea346b968bf4c427088f3a --MeTTeMJBNc/7,-MeTTeMJBNc,7,vision,10.51699161529541,10.51699161529541,84,35,106,0.1,35,1.0,ok,40716dc7402fd6398038eded58ce939ec76be6afbeea346b968bf4c427088f3a --RfYyzHpjk4/11,-RfYyzHpjk4,11,text,5.238996982574463,3.062753976881504,17,768,53,0.1,768,0.6960803866386414,ok,96e481cd732001239639c8cb4e7f94e570925e5a15940920ffab0cec1f13f904 --RfYyzHpjk4/11,-RfYyzHpjk4,11,audio,5.238996982574463,5.202267333462432,508,74,53,0.1,74,0.9958056807518005,ok,96e481cd732001239639c8cb4e7f94e570925e5a15940920ffab0cec1f13f904 --RfYyzHpjk4/11,-RfYyzHpjk4,11,vision,5.238996982574463,5.238996982574463,40,35,53,0.1,35,1.0,ok,96e481cd732001239639c8cb4e7f94e570925e5a15940920ffab0cec1f13f904 --RfYyzHpjk4/8,-RfYyzHpjk4,8,text,4.588996887207031,2.8058770607668286,17,768,46,0.1,768,0.684955358505249,ok,ed8c672c532b8c7d1c830c82d6e2c14fcb3bbd3dc1a86670a03a6c8e83c02f3c --RfYyzHpjk4/8,-RfYyzHpjk4,8,audio,4.588996887207031,4.553010454316745,454,74,46,0.1,74,0.994469404220581,ok,ed8c672c532b8c7d1c830c82d6e2c14fcb3bbd3dc1a86670a03a6c8e83c02f3c --RfYyzHpjk4/8,-RfYyzHpjk4,8,vision,4.588996887207031,4.588996887207031,33,35,46,0.1,35,1.0,ok,ed8c672c532b8c7d1c830c82d6e2c14fcb3bbd3dc1a86670a03a6c8e83c02f3c --RfYyzHpjk4/2,-RfYyzHpjk4,2,text,5.516016006469727,3.372718970850109,25,768,56,0.1,768,0.7175998091697693,ok,5e428ee22de58c9d6561b9b4353bef9dfb811a5841d9ab07b5bc453d697ad17f --RfYyzHpjk4/2,-RfYyzHpjk4,2,audio,5.516016006469727,5.478826378849712,540,74,56,0.1,74,0.9948742389678955,ok,5e428ee22de58c9d6561b9b4353bef9dfb811a5841d9ab07b5bc453d697ad17f --RfYyzHpjk4/2,-RfYyzHpjk4,2,vision,5.516016006469727,5.416016006469727,43,35,56,0.1,35,1.0,ok,5e428ee22de58c9d6561b9b4353bef9dfb811a5841d9ab07b5bc453d697ad17f --UUCSKoHeMA/0,-UUCSKoHeMA,0,text,7.800000190734863,4.133793779369442,18,768,79,0.1,768,0.666740894317627,ok,3f9792888ec8e969f61cfb6cb4de7bdf7ef8944afe0a9d2a9d13586e1f13b898 --UUCSKoHeMA/0,-UUCSKoHeMA,0,audio,7.800000190734863,7.750270468963159,774,74,79,0.1,74,0.9943835139274597,ok,3f9792888ec8e969f61cfb6cb4de7bdf7ef8944afe0a9d2a9d13586e1f13b898 --UUCSKoHeMA/0,-UUCSKoHeMA,0,vision,7.800000190734863,7.700000190734862,66,35,79,0.1,35,1.0,ok,3f9792888ec8e969f61cfb6cb4de7bdf7ef8944afe0a9d2a9d13586e1f13b898 --ri04Z7vwnc/0,-ri04Z7vwnc,0,text,2.806999921798706,2.1131306469440463,8,768,29,0.1,768,0.7826409935951233,ok,93021c70c8fad20ad3fded80e7fc790a2f9c96835de58a3b694c6906de42684b --ri04Z7vwnc/0,-ri04Z7vwnc,0,audio,2.806999921798706,2.8018783078000356,277,74,29,0.1,74,0.9982975125312805,ok,93021c70c8fad20ad3fded80e7fc790a2f9c96835de58a3b694c6906de42684b --ri04Z7vwnc/0,-ri04Z7vwnc,0,vision,2.806999921798706,0.0,14,35,29,0.1,35,0.0,ok,93021c70c8fad20ad3fded80e7fc790a2f9c96835de58a3b694c6906de42684b --ri04Z7vwnc/2,-ri04Z7vwnc,2,text,6.0269999504089355,3.9384737918153405,16,768,61,0.1,768,0.7431082725524902,ok,f5993ce3a6ee56298462c08692a96f78c7d914d7264257ed401de7d6e17fd148 --ri04Z7vwnc/2,-ri04Z7vwnc,2,audio,6.0269999504089355,6.008905370493193,592,74,61,0.1,74,0.9971521496772766,ok,f5993ce3a6ee56298462c08692a96f78c7d914d7264257ed401de7d6e17fd148 --ri04Z7vwnc/2,-ri04Z7vwnc,2,vision,6.0269999504089355,2.106416702270508,30,35,61,0.1,35,0.9906440377235413,ok,f5993ce3a6ee56298462c08692a96f78c7d914d7264257ed401de7d6e17fd148 --ri04Z7vwnc/5,-ri04Z7vwnc,5,text,3.5450000762939453,1.8027290821075441,9,768,36,0.1,768,0.721091628074646,ok,2a5e4319bf592a18c8eb5117f7c7ec30c6c79528f9eac9fe4fb85bf70f277736 --ri04Z7vwnc/5,-ri04Z7vwnc,5,audio,3.5450000762939453,3.534527108637063,344,74,36,0.1,74,0.9974266886711121,ok,2a5e4319bf592a18c8eb5117f7c7ec30c6c79528f9eac9fe4fb85bf70f277736 --ri04Z7vwnc/5,-ri04Z7vwnc,5,vision,3.5450000762939453,3.5450000762939453,18,35,36,0.1,35,1.0,ok,2a5e4319bf592a18c8eb5117f7c7ec30c6c79528f9eac9fe4fb85bf70f277736 --s9qJ7ATP7w/1,-s9qJ7ATP7w,1,text,4.7919921875,2.610484106093645,11,768,48,0.1,768,0.7055363059043884,ok,a33e8f82a185bcb7648b523927308cdc2142e3076479ba2b45cd0e828636fc09 --s9qJ7ATP7w/1,-s9qJ7ATP7w,1,audio,4.7919921875,4.72247887628304,465,74,48,0.1,74,0.9860281348228455,ok,a33e8f82a185bcb7648b523927308cdc2142e3076479ba2b45cd0e828636fc09 --s9qJ7ATP7w/1,-s9qJ7ATP7w,1,vision,4.7919921875,4.7919921875,35,35,48,0.1,35,1.0,ok,a33e8f82a185bcb7648b523927308cdc2142e3076479ba2b45cd0e828636fc09 --s9qJ7ATP7w/0,-s9qJ7ATP7w,0,text,6.800000190734863,3.6206328462809334,24,768,69,0.1,768,0.6351987719535828,ok,f2324dbc6debe0d1e4254e6f943523373e3cbb30d8d0555413ce3a7b370a4af5 --s9qJ7ATP7w/0,-s9qJ7ATP7w,0,audio,6.800000190734863,6.715675868979983,672,74,69,0.1,74,0.9885490536689758,ok,f2324dbc6debe0d1e4254e6f943523373e3cbb30d8d0555413ce3a7b370a4af5 --s9qJ7ATP7w/0,-s9qJ7ATP7w,0,vision,6.800000190734863,6.199999928474425,56,35,69,0.1,35,0.984375,ok,f2324dbc6debe0d1e4254e6f943523373e3cbb30d8d0555413ce3a7b370a4af5 --s9qJ7ATP7w/5,-s9qJ7ATP7w,5,text,8.561002731323242,3.4511515218298876,19,768,86,0.1,768,0.5150972604751587,ok,bd35eb8de64ce1f8b27921294598f7cf5bb971255738f51d06458c7096c58eae --s9qJ7ATP7w/5,-s9qJ7ATP7w,5,audio,8.561002731323242,8.46259727510246,840,74,86,0.1,74,0.9896790981292725,ok,bd35eb8de64ce1f8b27921294598f7cf5bb971255738f51d06458c7096c58eae --s9qJ7ATP7w/5,-s9qJ7ATP7w,5,vision,8.561002731323242,8.561002731323242,72,35,86,0.1,35,1.0,ok,bd35eb8de64ce1f8b27921294598f7cf5bb971255738f51d06458c7096c58eae --s9qJ7ATP7w/4,-s9qJ7ATP7w,4,text,4.427018165588379,2.2374289706349377,9,768,45,0.1,768,0.6215080618858337,ok,76e0672ffce5857a789b41fb10606402f7da58c33579b1032a8282f86fb35bc9 --s9qJ7ATP7w/4,-s9qJ7ATP7w,4,audio,4.427018165588379,4.367301462550421,425,74,45,0.1,74,0.9892621040344238,ok,76e0672ffce5857a789b41fb10606402f7da58c33579b1032a8282f86fb35bc9 --s9qJ7ATP7w/4,-s9qJ7ATP7w,4,vision,4.427018165588379,3.027018189430237,31,35,45,0.1,35,0.96875,ok,76e0672ffce5857a789b41fb10606402f7da58c33579b1032a8282f86fb35bc9 --s9qJ7ATP7w/7,-s9qJ7ATP7w,7,text,6.966015815734863,3.9709798723459264,28,768,70,0.1,768,0.661829948425293,ok,5301f4403cf7cd299cc525d2f443392ac70fd70c3c9cd4a09406f2ba4df6734d --s9qJ7ATP7w/7,-s9qJ7ATP7w,7,audio,6.966015815734863,6.848488390969263,684,74,70,0.1,74,0.9849807620048523,ok,5301f4403cf7cd299cc525d2f443392ac70fd70c3c9cd4a09406f2ba4df6734d --s9qJ7ATP7w/7,-s9qJ7ATP7w,7,vision,6.966015815734863,4.0493486523628235,57,35,70,0.1,35,0.9496123194694519,ok,5301f4403cf7cd299cc525d2f443392ac70fd70c3c9cd4a09406f2ba4df6734d --s9qJ7ATP7w/6,-s9qJ7ATP7w,6,text,2.4749999046325684,1.6227161765098577,5,768,25,0.1,768,0.8113580942153931,ok,40b684fd1b4559f0f82e72f9b47f4ce7c5e15059fe8d0d8ab112637cd3386451 --s9qJ7ATP7w/6,-s9qJ7ATP7w,6,audio,2.4749999046325684,2.4289188214250514,232,74,25,0.1,74,0.9844902753829956,ok,40b684fd1b4559f0f82e72f9b47f4ce7c5e15059fe8d0d8ab112637cd3386451 --s9qJ7ATP7w/6,-s9qJ7ATP7w,6,vision,2.4749999046325684,1.8999999761581425,14,35,25,0.1,35,1.0,ok,40b684fd1b4559f0f82e72f9b47f4ce7c5e15059fe8d0d8ab112637cd3386451 --s9qJ7ATP7w/8,-s9qJ7ATP7w,8,text,3.2949869632720947,1.9395141303539274,13,768,33,0.1,768,0.6465047001838684,ok,1de4d91bd9d9fb508a3779658747da88460db0bdb1beefe7ea5b2c77edfd2239 --s9qJ7ATP7w/8,-s9qJ7ATP7w,8,audio,3.2949869632720947,3.253163003921509,319,74,33,0.1,74,0.9880942702293396,ok,1de4d91bd9d9fb508a3779658747da88460db0bdb1beefe7ea5b2c77edfd2239 --s9qJ7ATP7w/8,-s9qJ7ATP7w,8,vision,3.2949869632720947,3.016666531562805,20,35,33,0.1,35,0.9731181859970093,ok,1de4d91bd9d9fb508a3779658747da88460db0bdb1beefe7ea5b2c77edfd2239 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,text,29.288021087646484,15.053765958920112,49,768,293,0.1,768,0.6873865723609924,ok,2f16da1baa8660e5bfc608f5237cdd59725d16e57a19bc02c4556cd2c7129a46 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,audio,29.288021087646484,28.759709144524624,2911,74,293,0.1,74,0.9836021065711975,ok,2f16da1baa8660e5bfc608f5237cdd59725d16e57a19bc02c4556cd2c7129a46 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,vision,29.288021087646484,27.471354246139526,178,35,293,0.1,35,0.999393880367279,ok,2f16da1baa8660e5bfc608f5237cdd59725d16e57a19bc02c4556cd2c7129a46 --yRb-Jum7EQ/5,-yRb-Jum7EQ,5,text,13.169010162353516,8.127011682093151,25,768,132,0.1,768,0.7192046046257019,ok,6d6145293cf84d1fc8324dfa8d39465e2d7fc07affb67ff68deeabf6e3c410d9 --yRb-Jum7EQ/5,-yRb-Jum7EQ,5,audio,13.169010162353516,12.971401820754682,1305,74,132,0.1,74,0.9867846369743347,ok,6d6145293cf84d1fc8324dfa8d39465e2d7fc07affb67ff68deeabf6e3c410d9 --yRb-Jum7EQ/5,-yRb-Jum7EQ,5,vision,13.169010162353516,13.169010162353516,97,35,132,0.1,35,1.0,ok,6d6145293cf84d1fc8324dfa8d39465e2d7fc07affb67ff68deeabf6e3c410d9 --yRb-Jum7EQ/6,-yRb-Jum7EQ,6,text,11.241994857788086,4.740236129239202,19,768,113,0.1,768,0.6869907975196838,ok,b51eb9ad06de804934cb6a315de591ba9ff7f8aa71bffff7f8001ab29945d989 --yRb-Jum7EQ/6,-yRb-Jum7EQ,6,audio,11.241994857788086,11.070711010679133,1125,74,113,0.1,74,0.9854583740234375,ok,b51eb9ad06de804934cb6a315de591ba9ff7f8aa71bffff7f8001ab29945d989 --yRb-Jum7EQ/6,-yRb-Jum7EQ,6,vision,11.241994857788086,11.241994857788086,87,35,113,0.1,35,1.0,ok,b51eb9ad06de804934cb6a315de591ba9ff7f8aa71bffff7f8001ab29945d989 diff --git a/math/Q1/results/model_comparison/oof_predictions.csv b/math/Q1/results/model_comparison/oof_predictions.csv deleted file mode 100644 index b866563..0000000 --- a/math/Q1/results/model_comparison/oof_predictions.csv +++ /dev/null @@ -1,101 +0,0 @@ -sample_id,video_id,clip_id,true_polarity,true_polarity_name,true_sentiment,B0_predicted_polarity,B1_predicted_polarity,B2_predicted_polarity,B3_predicted_polarity,B4_predicted_polarity,B0_predicted_sentiment,B1_predicted_sentiment,B2_predicted_sentiment,B3_predicted_sentiment,B4_predicted_sentiment --3g5yACwYnA/13,-3g5yACwYnA,13,2,positive,0.6666666865348816,2,2,2,2,2,0.13452544808387756,0.16021420061588287,0.14872726798057556,0.16442018747329712,0.229058176279068 --3g5yACwYnA/3,-3g5yACwYnA,3,1,neutral,0.0,2,2,2,2,2,0.3026959300041199,0.33461102843284607,0.42589470744132996,0.31887251138687134,0.29829922318458557 --3g5yACwYnA/2,-3g5yACwYnA,2,1,neutral,0.0,2,2,2,2,2,0.3966212272644043,0.46180492639541626,0.48163092136383057,0.43820273876190186,0.5120640397071838 --3g5yACwYnA/9,-3g5yACwYnA,9,2,positive,0.6666666865348816,2,2,2,2,2,0.6833762526512146,0.7414957880973816,0.7930513024330139,0.7018600106239319,0.6162992715835571 --3nNcZdcdvU/5,-3nNcZdcdvU,5,1,neutral,0.0,0,0,0,0,0,-0.7614330053329468,-0.6502371430397034,-0.6979431509971619,-0.6381849050521851,-0.5865846872329712 --HwX2H8Z4hY/2,-HwX2H8Z4hY,2,1,neutral,0.0,2,2,2,2,2,0.6054284572601318,0.5735942721366882,0.6148816347122192,0.5838509798049927,0.8063328266143799 --HwX2H8Z4hY/5,-HwX2H8Z4hY,5,0,negative,-1.0,0,0,2,2,2,0.08644700050354004,-0.01681867241859436,0.054207056760787964,0.008860379457473755,0.08198326826095581 --HwX2H8Z4hY/6,-HwX2H8Z4hY,6,1,neutral,0.0,2,2,2,2,2,0.31941771507263184,0.4352392554283142,0.45426928997039795,0.40970659255981445,0.5301598310470581 --HwX2H8Z4hY/9,-HwX2H8Z4hY,9,0,negative,-0.3333333432674408,0,0,0,0,0,-0.07338133454322815,-0.14210763573646545,-0.13199511170387268,-0.13720062375068665,-0.2480643391609192 --NFrJFQijFE/1,-NFrJFQijFE,1,2,positive,0.3333333432674408,2,2,2,2,1,-0.029091298580169678,0.04221409559249878,0.023884594440460205,0.038062989711761475,-0.10948124527931213 --NFrJFQijFE/2,-NFrJFQijFE,2,1,neutral,0.0,2,2,2,2,2,0.5534588098526001,0.6096377372741699,0.5728316307067871,0.5841389894485474,0.6658575534820557 --THoVjtIkeU/12,-THoVjtIkeU,12,2,positive,2.0,2,2,2,2,2,0.1105184555053711,-0.015041038393974304,0.01798933744430542,0.013076543807983398,0.05507504940032959 --THoVjtIkeU/2,-THoVjtIkeU,2,2,positive,1.3333333730697632,2,2,2,2,2,0.14952212572097778,-0.03578713536262512,0.21528872847557068,-0.047229185700416565,0.07181030511856079 --THoVjtIkeU/6,-THoVjtIkeU,6,2,positive,2.6666667461395264,2,2,2,2,2,0.28439241647720337,0.10436569154262543,0.19625744223594666,0.109825998544693,0.11878173053264618 --UuX1xuaiiE/1,-UuX1xuaiiE,1,2,positive,1.6666666269302368,2,2,2,2,2,0.05641767382621765,0.05484718084335327,0.02277640998363495,0.05113929510116577,0.011383742094039917 --UuX1xuaiiE/0,-UuX1xuaiiE,0,2,positive,2.6666667461395264,2,2,2,2,2,0.6992747783660889,0.6104735136032104,0.7187632918357849,0.6213169097900391,0.5144999027252197 --UuX1xuaiiE/3,-UuX1xuaiiE,3,2,positive,0.3333333432674408,2,2,2,2,2,0.66947340965271,0.5266174077987671,0.5624967217445374,0.5222238898277283,0.45163899660110474 --UuX1xuaiiE/6,-UuX1xuaiiE,6,0,negative,-0.3333333432674408,2,2,2,2,2,0.12534436583518982,0.002005934715270996,-0.03466030955314636,-0.01757238805294037,0.03905734419822693 --a55Q6RWvTA/3,-a55Q6RWvTA,3,2,positive,0.6666666865348816,2,2,2,2,2,0.24422422051429749,0.13229034841060638,0.1552799940109253,0.1265096515417099,0.17101362347602844 --aNfi7CP8vM/7,-aNfi7CP8vM,7,1,neutral,0.0,2,2,2,2,2,0.7103666663169861,0.8981346487998962,0.7498640418052673,0.908927321434021,0.7986767292022705 --aqamKhZ1Ec/0,-aqamKhZ1Ec,0,0,negative,-2.0,2,2,2,2,2,0.14777150750160217,0.2721712589263916,0.20749390125274658,0.26992136240005493,0.2557317018508911 --dxfTGcXJoc/1,-dxfTGcXJoc,1,2,positive,1.6666666269302368,2,2,2,2,2,0.4534122347831726,0.15173421800136566,0.23860448598861694,0.08927315473556519,0.17231377959251404 --dxfTGcXJoc/0,-dxfTGcXJoc,0,2,positive,1.0,2,2,2,1,2,0.30912163853645325,0.18118944764137268,0.1967533975839615,0.17624947428703308,0.20736707746982574 --dxfTGcXJoc/2,-dxfTGcXJoc,2,2,positive,0.6666666865348816,2,2,2,2,2,0.5904080867767334,0.34547320008277893,0.4100586771965027,0.3144497573375702,0.33179861307144165 --dxfTGcXJoc/6,-dxfTGcXJoc,6,2,positive,0.6666666865348816,2,2,2,2,2,0.40664565563201904,0.07521255314350128,0.0900307297706604,0.107652947306633,0.09203940629959106 --egA8-b7-3M/26,-egA8-b7-3M,26,2,positive,1.6666666269302368,2,2,2,2,2,0.8926460146903992,0.8544832468032837,0.7031165957450867,0.8596105575561523,0.6629092693328857 --egA8-b7-3M/17,-egA8-b7-3M,17,2,positive,0.3333333432674408,2,2,2,2,2,0.780834972858429,0.8010746240615845,0.7224219441413879,0.7491263151168823,0.7902140617370605 --egA8-b7-3M/18,-egA8-b7-3M,18,2,positive,1.0,2,2,2,2,2,0.8284801244735718,0.8428431153297424,0.7629272937774658,0.8139240741729736,0.759922981262207 --egA8-b7-3M/16,-egA8-b7-3M,16,2,positive,0.6666666865348816,2,2,2,2,2,1.1456997394561768,1.103100299835205,0.9217796921730042,1.0922913551330566,0.9465919733047485 --egA8-b7-3M/13,-egA8-b7-3M,13,2,positive,0.3333333432674408,2,2,2,2,2,0.29149097204208374,0.2857578694820404,0.29504942893981934,0.2710241973400116,0.433204710483551 --egA8-b7-3M/1,-egA8-b7-3M,1,2,positive,0.6666666865348816,2,2,2,2,2,0.49869486689567566,0.5516833662986755,0.4600910544395447,0.5341068506240845,0.5454411506652832 --egA8-b7-3M/6,-egA8-b7-3M,6,2,positive,0.6666666865348816,2,2,2,2,2,0.8187044262886047,0.8529066443443298,0.7433335781097412,0.8614661693572998,0.7032537460327148 --egA8-b7-3M/9,-egA8-b7-3M,9,2,positive,0.3333333432674408,2,2,2,2,2,0.746141791343689,0.755176305770874,0.7585423588752747,0.7326465845108032,0.7642356157302856 --egA8-b7-3M/20,-egA8-b7-3M,20,2,positive,0.3333333432674408,2,2,2,2,2,0.75407874584198,0.783722460269928,0.7880091667175293,0.7994571924209595,0.7963440418243408 --iRBcNs9oI8/3,-iRBcNs9oI8,3,2,positive,0.6666666865348816,2,2,2,2,2,0.41121792793273926,0.26391637325286865,0.16125774383544922,0.30018502473831177,0.22292546927928925 --iRBcNs9oI8/7,-iRBcNs9oI8,7,2,positive,0.6666666865348816,2,2,2,2,2,0.6934136152267456,0.5427778959274292,0.5866559743881226,0.5839468240737915,0.5824995636940002 --iRBcNs9oI8/6,-iRBcNs9oI8,6,2,positive,0.3333333432674408,2,2,2,2,2,0.4273873567581177,0.3189065456390381,0.3010154962539673,0.3516676127910614,0.32149577140808105 --iRBcNs9oI8/9,-iRBcNs9oI8,9,2,positive,1.3333333730697632,2,2,1,2,2,0.01312372088432312,-0.0918610543012619,0.1977950930595398,-0.06410297751426697,-0.14683973789215088 --iRBcNs9oI8/8,-iRBcNs9oI8,8,2,positive,1.0,2,2,2,2,2,0.45394086837768555,0.2737142741680145,0.34107109904289246,0.34081369638442993,0.36690521240234375 --lzEya4AM_4/5,-lzEya4AM_4,5,0,negative,-0.6666666865348816,2,1,1,1,2,0.003696233034133911,0.07954774796962738,-0.02835392951965332,0.06377251446247101,0.0930773913860321 --lzEya4AM_4/6,-lzEya4AM_4,6,0,negative,-0.3333333432674408,1,1,1,1,1,-0.08578968048095703,-0.05591443181037903,-0.16103187203407288,-0.07273416221141815,-0.03954911231994629 --mJ2ud6oKI8/1,-mJ2ud6oKI8,1,1,neutral,0.0,2,2,2,2,1,0.32054486870765686,0.31638309359550476,0.4096267521381378,0.32599377632141113,0.11944134533405304 --mJ2ud6oKI8/2,-mJ2ud6oKI8,2,1,neutral,0.0,2,2,2,2,1,0.3205912411212921,0.2857860326766968,0.32545098662376404,0.2961588501930237,0.07219411432743073 --mJ2ud6oKI8/6,-mJ2ud6oKI8,6,2,positive,0.3333333432674408,2,2,2,2,2,0.34881988167762756,0.2555202841758728,0.19199120998382568,0.22443163394927979,0.11697705090045929 --mJ2ud6oKI8/9,-mJ2ud6oKI8,9,1,neutral,0.0,2,2,2,2,2,0.49129533767700195,0.509657621383667,0.40949302911758423,0.49832504987716675,0.3923254609107971 --mJ2ud6oKI8/8,-mJ2ud6oKI8,8,0,negative,-0.3333333432674408,0,0,0,0,0,0.033514365553855896,-0.12224322557449341,0.015729933977127075,-0.13064196705818176,-0.10159948468208313 --mqbVkbCndg/0,-mqbVkbCndg,0,1,neutral,0.0,2,2,2,2,2,-0.09232228994369507,-0.27456536889076233,-0.23857474327087402,-0.2712118625640869,-0.06543052196502686 --t217m2on-s/2,-t217m2on-s,2,2,positive,0.6666666865348816,2,2,2,2,2,0.4828706979751587,0.4535056948661804,0.48303860425949097,0.4338659644126892,0.29441648721694946 --t217m2on-s/7,-t217m2on-s,7,0,negative,-0.6666666865348816,2,2,2,2,2,0.03153911232948303,0.12483498454093933,0.23645390570163727,0.14657872915267944,0.2676320970058441 --tANM6ETl_M/3,-tANM6ETl_M,3,2,positive,0.3333333432674408,2,2,2,2,2,0.13329337537288666,0.27301740646362305,0.20109084248542786,0.23898470401763916,0.2801833152770996 --tPCytz4rww/11,-tPCytz4rww,11,1,neutral,0.0,2,2,2,2,2,0.39490315318107605,0.41642117500305176,0.5103898644447327,0.40319329500198364,0.5221617221832275 --tPCytz4rww/10,-tPCytz4rww,10,1,neutral,0.0,2,2,2,2,2,0.45396602153778076,0.48757827281951904,0.39305949211120605,0.48652955889701843,0.5163553357124329 --tPCytz4rww/12,-tPCytz4rww,12,1,neutral,0.0,2,2,2,2,2,0.4888620376586914,0.47673290967941284,0.523354709148407,0.47867047786712646,0.5164443254470825 --tPCytz4rww/16,-tPCytz4rww,16,1,neutral,0.0,2,2,2,2,2,0.16386589407920837,0.1889176368713379,0.15202002227306366,0.20772001147270203,0.10384060442447662 --tPCytz4rww/18,-tPCytz4rww,18,1,neutral,0.0,2,2,2,2,2,0.39335885643959045,0.48845911026000977,0.4801775813102722,0.49252307415008545,0.5596518516540527 --vxjVxOeScU/4,-vxjVxOeScU,4,2,positive,1.0,2,2,2,2,2,1.300539255142212,1.3340058326721191,1.3243328332901,1.3665581941604614,1.3101918697357178 --wMB_hJL-3o/7,-wMB_hJL-3o,7,2,positive,0.3333333432674408,2,2,2,2,2,0.43083706498146057,0.3697093427181244,0.3281114399433136,0.3639947175979614,0.4309353828430176 --wny0OAz3g8/1,-wny0OAz3g8,1,2,positive,0.3333333432674408,2,2,2,2,2,-0.029849499464035034,-0.0726122260093689,-0.024748489260673523,-0.07751013338565826,0.01515229046344757 --wny0OAz3g8/0,-wny0OAz3g8,0,2,positive,0.3333333432674408,1,1,1,1,1,-0.26475363969802856,-0.4248991906642914,-0.3667675256729126,-0.43525469303131104,-0.2892696261405945 --wny0OAz3g8/3,-wny0OAz3g8,3,0,negative,-1.3333333730697632,2,2,2,2,2,-0.03229987621307373,0.011097535490989685,-0.044357895851135254,0.014330193400382996,0.1011495590209961 --wny0OAz3g8/2,-wny0OAz3g8,2,0,negative,-0.3333333432674408,2,2,2,2,2,0.0680823028087616,0.020685836672782898,0.1548982560634613,0.049939438700675964,0.12679153680801392 --wny0OAz3g8/5,-wny0OAz3g8,5,2,positive,1.0,2,2,2,2,2,0.4779983460903168,0.42994704842567444,0.3525465130805969,0.4249609410762787,0.4561484158039093 --wny0OAz3g8/7,-wny0OAz3g8,7,1,neutral,0.0,2,2,2,2,2,0.14757554233074188,0.11216723173856735,0.15002727508544922,0.10439274460077286,0.08023504912853241 --wny0OAz3g8/9,-wny0OAz3g8,9,2,positive,0.6666666865348816,2,2,2,2,2,0.18945443630218506,0.2243257611989975,0.255195677280426,0.2078581154346466,0.26747772097587585 --571d8cVauQ/0,-571d8cVauQ,0,1,neutral,0.0,1,1,1,1,1,0.1813371479511261,0.26319703459739685,0.20845845341682434,0.2597145736217499,0.2923925817012787 --571d8cVauQ/5,-571d8cVauQ,5,2,positive,0.3333333432674408,2,2,2,2,2,0.7947983145713806,0.8263474702835083,0.8470317125320435,0.8056427836418152,0.7695794105529785 --I_e4mIh0yE/1,-I_e4mIh0yE,1,0,negative,-0.6666666865348816,1,1,2,1,2,-0.053890615701675415,0.05120442807674408,0.14258822798728943,0.058895498514175415,-0.0020049959421157837 --I_e4mIh0yE/3,-I_e4mIh0yE,3,2,positive,0.6666666865348816,2,2,2,2,2,0.20941728353500366,0.2584538459777832,0.3930857181549072,0.27197059988975525,0.3383082151412964 --UacrmKiTn4/10,-UacrmKiTn4,10,0,negative,-0.6666666865348816,2,2,2,2,2,-0.007775545120239258,0.10976105183362961,0.2304498553276062,0.1546456217765808,0.1571420133113861 --UacrmKiTn4/4,-UacrmKiTn4,4,0,negative,-1.3333333730697632,2,2,2,2,2,0.24989673495292664,0.44462817907333374,0.4752929210662842,0.4392329156398773,0.5184646844863892 --hnBHBN8p5A/7,-hnBHBN8p5A,7,2,positive,0.6666666865348816,2,2,2,2,2,0.25469517707824707,0.267363965511322,0.26611560583114624,0.2937210500240326,0.4176241457462311 --hnBHBN8p5A/6,-hnBHBN8p5A,6,2,positive,1.0,2,2,2,2,2,0.7116098403930664,0.6368920803070068,0.8011423349380493,0.6396559476852417,0.7429358959197998 --qDkUB0GgYY/6,-qDkUB0GgYY,6,2,positive,1.3333333730697632,2,2,2,2,2,1.4230821132659912,1.456520915031433,1.482230544090271,1.4008221626281738,1.3085699081420898 --uywlfIYOS8/4,-uywlfIYOS8,4,2,positive,0.3333333432674408,2,2,2,2,2,0.6702563762664795,0.7197655439376831,0.6297314763069153,0.7727823257446289,0.7619336843490601 --6rXp3zJ3kc/8,-6rXp3zJ3kc,8,0,negative,-1.0,2,2,2,2,2,0.23289291560649872,0.10650955140590668,-0.048172906041145325,0.1659325510263443,0.07517096400260925 --9y-fZ3swSY/0,-9y-fZ3swSY,0,2,positive,1.0,2,2,2,2,2,0.8935344815254211,0.981560468673706,1.0655876398086548,0.9575732946395874,0.960616946220398 --9y-fZ3swSY/4,-9y-fZ3swSY,4,1,neutral,0.0,2,2,2,2,1,0.7359274625778198,0.8043063282966614,0.8141930103302002,0.8211376667022705,0.801345944404602 --9y-fZ3swSY/8,-9y-fZ3swSY,8,2,positive,1.6666666269302368,2,2,2,2,2,0.0990075170993805,0.17485348880290985,0.26351824402809143,0.15360157191753387,0.2083582729101181 --AUZQgSxyPQ/2,-AUZQgSxyPQ,2,2,positive,0.6666666865348816,2,2,2,2,2,0.9318890571594238,1.1048165559768677,1.1751078367233276,1.091732382774353,0.7978025078773499 --HeZS2-Prhc/2,-HeZS2-Prhc,2,2,positive,0.6666666865348816,2,2,2,2,2,0.42690128087997437,0.37649014592170715,0.3945169448852539,0.3838789463043213,0.30630016326904297 --MeTTeMJBNc/0,-MeTTeMJBNc,0,2,positive,0.3333333432674408,2,2,2,2,2,0.5873996019363403,0.4888506829738617,0.520802915096283,0.4796018600463867,0.48370563983917236 --MeTTeMJBNc/13,-MeTTeMJBNc,13,2,positive,0.3333333432674408,2,2,2,2,2,0.681941032409668,0.7230368852615356,0.6091403365135193,0.7292149662971497,0.745182454586029 --MeTTeMJBNc/7,-MeTTeMJBNc,7,2,positive,1.3333333730697632,2,2,2,2,2,0.5029646158218384,0.47240275144577026,0.5074828863143921,0.46745914220809937,0.47605717182159424 --RfYyzHpjk4/11,-RfYyzHpjk4,11,2,positive,2.0,2,2,2,2,2,0.5564365983009338,0.42342162132263184,0.5021690726280212,0.43483608961105347,0.43543678522109985 --RfYyzHpjk4/8,-RfYyzHpjk4,8,2,positive,0.3333333432674408,2,2,2,2,2,0.3994223177433014,0.3921676576137543,0.2823079228401184,0.40095123648643494,0.42251622676849365 --RfYyzHpjk4/2,-RfYyzHpjk4,2,2,positive,0.3333333432674408,2,2,2,2,1,0.365897536277771,0.38750067353248596,0.23726055026054382,0.3845585286617279,0.21417461335659027 --UUCSKoHeMA/0,-UUCSKoHeMA,0,1,neutral,0.0,2,2,2,2,2,0.5638669729232788,0.5825111269950867,0.6482444405555725,0.5764590501785278,0.5579362511634827 --ri04Z7vwnc/0,-ri04Z7vwnc,0,1,neutral,0.0,2,2,2,2,1,0.26682645082473755,0.1752839833498001,0.11657405644655228,0.17440180480480194,-0.12501448392868042 --ri04Z7vwnc/2,-ri04Z7vwnc,2,0,negative,-0.3333333432674408,2,2,2,2,1,0.41648173332214355,0.39698678255081177,0.31453409790992737,0.42282843589782715,-0.06992921233177185 --ri04Z7vwnc/5,-ri04Z7vwnc,5,2,positive,0.3333333432674408,2,2,2,2,2,0.7894954681396484,0.9298861026763916,0.8353837132453918,0.9478996992111206,0.9307202100753784 --s9qJ7ATP7w/1,-s9qJ7ATP7w,1,2,positive,0.6666666865348816,2,2,2,2,2,0.8451777696609497,0.7406796216964722,0.6926915645599365,0.7564423084259033,0.7351438403129578 --s9qJ7ATP7w/0,-s9qJ7ATP7w,0,0,negative,-0.3333333432674408,2,2,2,2,0,0.08492019772529602,0.08116327226161957,0.09997616708278656,0.09164288640022278,-0.18887805938720703 --s9qJ7ATP7w/5,-s9qJ7ATP7w,5,0,negative,-2.0,2,0,2,0,2,0.25190818309783936,0.23056381940841675,0.42701321840286255,0.2685755491256714,0.35108593106269836 --s9qJ7ATP7w/4,-s9qJ7ATP7w,4,1,neutral,0.0,2,2,2,2,2,0.8093756437301636,0.6910800933837891,0.8017246723175049,0.6906447410583496,0.7730451822280884 --s9qJ7ATP7w/7,-s9qJ7ATP7w,7,2,positive,1.0,2,2,2,2,1,0.04829922318458557,-0.06272962689399719,0.04885163903236389,-0.056273818016052246,-0.3453366756439209 --s9qJ7ATP7w/6,-s9qJ7ATP7w,6,1,neutral,0.0,2,2,2,2,2,-0.11959794163703918,0.12442992627620697,0.22614140808582306,0.12353259325027466,0.05900001525878906 --s9qJ7ATP7w/8,-s9qJ7ATP7w,8,2,positive,1.3333333730697632,2,2,2,2,1,0.5094736218452454,0.4484489858150482,0.6055055856704712,0.42063793540000916,0.0980398952960968 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,1,neutral,0.0,0,0,0,0,0,-0.39470893144607544,-0.5162537693977356,-0.5732794404029846,-0.5318436622619629,-0.47799739241600037 --yRb-Jum7EQ/5,-yRb-Jum7EQ,5,0,negative,-0.6666666865348816,1,1,1,1,1,-0.31519562005996704,-0.4650754928588867,-0.48384714126586914,-0.4728321433067322,-0.4012225568294525 --yRb-Jum7EQ/6,-yRb-Jum7EQ,6,1,neutral,0.0,0,0,0,0,0,-0.3192596435546875,-0.48287540674209595,-0.5565515160560608,-0.4418525695800781,-0.5206273794174194 diff --git a/math/Q1/results/model_comparison/report.md b/math/Q1/results/model_comparison/report.md deleted file mode 100644 index c17e450..0000000 --- a/math/Q1/results/model_comparison/report.md +++ /dev/null @@ -1,61 +0,0 @@ -# 问题一 B0-B4 模型对比结果 - -本报告按 `math/Q1/问题一.pdf` 第 4.8.3 节实施五组单因素对照。全部 100 条附件一视频均使用同一套冻结特征抽取器、0.1 秒主时间网格、观测掩码与按 `video_id` 分组的五折划分。情感标签仅用于折内的轻量预测探针，不进入时间对齐、CTC 后验或动态签名计算。 - -## 实际特征和比较版本 - -| 版本 | 实施内容 | -| --- | --- | -| B0 | CTC Viterbi 词区间与音频/视觉物理时间区间投影；训练折均值/标准差缩放；视觉旋转向量和视线向量作普通分量均值。 | -| B1 | 在 B0 上改用训练折中位数与 MAD 的稳健尺度（MAD 为零时回退到训练折标准差），并对视觉旋转用 SO(3) 均值、视线用归一化向量均值。 | -| B2 | 在 B1 上只将文本词向量的硬边界投影替换为固定转写 CTC 状态图的前向–后向占据概率投影；媒体时间戳仍按物理时间。 | -| B3 | 在 B1 上仅附加音频 log-F0/能量与视觉 jaw-open/嘴部开合率的时间增广一、二阶路径签名；缺测点之间不连线。 | -| B4 | 在 B1 上仅附加冻结 Wav2Vec2-base-960h 最后四层的时间投影表示。 | - -附件一现有标签表和原始视频被直接使用。文本为 768 维 BERT-base-uncased 末四层均值；音频为 74 维（log-Mel 40、MFCC 13、ΔMFCC 13、韵律/谱统计 8）；视觉为 35 维（17 个 MediaPipe blendshape 代理、6 维头姿、6 维近似视线、6 维面部比例几何）。视觉代理和几何索引定义见 `compare_models.py`，它们与 OpenFace AU 定义并不等同；该限制须在论文中明示。 - -## 结果 - -分类按连续标签的严格符号构造 Negative/Neutral/Positive，强度预测限幅到 [-3, 3]。每折训练折单独拟合标准化器、逻辑回归（C=0.05）与 Ridge（alpha=25）；固定五折由 GroupKFold 按原始 `video_id` 分组。总体 OOF 指标按 100 条留组预测计算。 - -| 方法 | OOF Accuracy | OOF Macro-F1 | OOF MAE | OOF Pearson | Macro-F1 折均值±SD | -| --- | ---: | ---: | ---: | ---: | ---: | -| B0 | 0.600 | 0.361 | 0.564 | 0.346 | 0.337 ± 0.098 | -| B1 | 0.610 | 0.387 | 0.599 | 0.238 | 0.349 ± 0.119 | -| B2 | 0.580 | 0.331 | 0.588 | 0.279 | 0.313 ± 0.087 | -| B3 | 0.590 | 0.359 | 0.600 | 0.230 | 0.333 ± 0.096 | -| B4 | 0.600 | 0.422 | 0.593 | 0.199 | 0.398 ± 0.089 | - -按当前 OOF 探针，Macro-F1 最高的是 B4（0.422），MAE 最低的是 B0（0.564）。相对 B1，B4 的 Macro-F1 差为 +0.035，视频组 Bootstrap 95% 区间 [-0.051, +0.137]，区间跨过零。B0 的 MAE 差为 -0.035，区间 [-0.063, -0.012]，Pearson 差为 +0.108。B2 的 Macro-F1 差为 -0.057，区间 [-0.109, -0.001]，MAE 差为 -0.011；B3 的 Macro-F1 差为 -0.029，区间 [-0.072, +0.000]。组 Bootstrap 只反映当前 37 个来源视频上的抽样不确定性，未作多重比较校正。 - -## 覆盖与对齐核验 - -样本数：100；标签表连续标签与极性一致 100/100；CTC 硬对齐完整的样本 91/100。B0 硬区间平均文本覆盖率为 0.673，B2 平均词占据后验质量为 0.229（这是期望占据率，不是覆盖率）；视觉检测覆盖率（按 0.1 秒网格平均）为 0.859。后验内部 90% 边界区间平均宽度为起点 0.131 秒、终点 0.111 秒。没有人工边界子集，因此这些宽度只是模型内部不确定性摘要，不是经验校准率或边界误差。 - -B0–B4 的特征来源、有效掩码、连续覆盖率、词边界后验宽度、折内预测及视频哈希均分别保存在配套 CSV/JSON 中。没有人工词边界时不报告 IoU/MATE，也不把不同方法的预测探针分数解释为对齐真值。 - -## 文件 - -- `comparison_summary.csv`：五种方法总体 OOF 与折均值指标。 -- `fold_metrics.csv`：每折分类/回归指标与特征维数。 -- `oof_predictions.csv`：每条样本的留组预测。 -- `group_bootstrap_deltas.csv`：相对 B1 的视频组配对 Bootstrap 95% 区间。 -- `sample_alignment_summary.csv`：100 条样本、硬/概率文本覆盖和后验边界宽度。 -- `modality_summary.csv`：300 行样本-模态明细。 -- `word_alignment_posterior.csv`：逐词硬边界、实际相对质量权重及后验边界区间。 -- `split_assignments.csv`：逐样本折号。 -- `comparison.png`：核心 OOF 指标图。 -- `typical_alignment_example.png`：中位时长样本的词边界、覆盖率、声学/视觉轨迹与视频帧核验图。 -- `run_manifest.json`：环境、模型 revision、参数、哈希与运行时间。 - -## 复现 - -在仓库根目录执行： - -```bash -cd math/Q1 -uv sync -uv run python compare_models.py -``` - -特征缓存写在 `math/Q1/cache/native/`，正式结果只写在 `math/Q1/results/model_comparison/`。删除缓存后会从附件一重新提取。首次运行需要下载 BERT、Wav2Vec2 和 MediaPipe Face Landmarker 权重。 diff --git a/math/Q1/results/model_comparison/sample_alignment_summary.csv b/math/Q1/results/model_comparison/sample_alignment_summary.csv deleted file mode 100644 index 75d637f..0000000 --- a/math/Q1/results/model_comparison/sample_alignment_summary.csv +++ /dev/null @@ -1,101 +0,0 @@ -sample_id,video_id,clip_id,source_video_sha256,duration_s,word_count,hard_aligned_word_count,unlocated_word_count,posterior_usable_word_count,mean_start_interval_width90_s,mean_end_interval_width90_s,text_hard_grid_coverage,text_posterior_grid_occupancy,audio_grid_coverage,vision_grid_coverage,audio_native_rows,vision_native_rows,status --3g5yACwYnA/13,-3g5yACwYnA,13,aeb47627f59dce3d0a85a44ef35e4a3bc18211498e98c8c11cf60269646df24f,5.5139970779418945,15,15,0,15,0.037333333333333406,0.020000000000000004,0.7015532851219177,0.24074573814868927,0.9882608652114868,1.0,540,43,ok --3g5yACwYnA/3,-3g5yACwYnA,3,eff8cfefba2425155f2b72656829b34b23be8bfe1dcbece384154f56818aa26d,14.388997077941895,29,29,0,29,0.2793103448275863,0.25931034482758614,0.6343300342559814,0.19729532301425934,0.9912122488021851,1.0,1433,103,ok --3g5yACwYnA/2,-3g5yACwYnA,2,0619c01f137d017c15c058176f18a575919189c7e81ebd2bfb993afdb86f3de7,9.394009590148926,14,14,0,14,0.2828571428571428,0.19142857142857145,0.7563282251358032,0.15269099175930023,0.9936367273330688,1.0,924,78,ok --3g5yACwYnA/9,-3g5yACwYnA,9,b962573b12ed1f06d5533f6427c80dce2bae3a99dd332f6d3fcb32c579f3f016,8.816991806030273,21,21,0,21,0.22095238095238093,0.1942857142857142,0.6637077927589417,0.26207172870635986,0.9912108778953552,1.0,870,75,ok --3nNcZdcdvU/5,-3nNcZdcdvU,5,7ea53ad502b77be7d2ee4494dc23a9478c897792203cf887d546e83d584c1728,7.867969036102295,18,18,0,18,0.03555555555555544,0.012222222222222258,0.7357116341590881,0.22051197290420532,0.9971166849136353,0.9904456734657288,779,67,ok --HwX2H8Z4hY/2,-HwX2H8Z4hY,2,920a1052c09ebd1eedba6dd1ccfecd80f56f6f0fdcdd1f6dd32b0d90bcb89358,3.9820311069488525,8,7,1,7,0.12285714285714287,0.12285714285714275,0.6164926290512085,0.18007618188858032,0.9881895780563354,0.9814813733100891,392,27,ok --HwX2H8Z4hY/5,-HwX2H8Z4hY,5,8d61b7f5840a8bd403d9bc6c3cd49029ffc4e304cf9c7834735c1a6bb5fd369d,5.6529951095581055,10,9,1,9,0.037777777777777764,0.040000000000000036,0.7021505832672119,0.22856950759887695,0.9900854229927063,0.666666567325592,555,44,ok --HwX2H8Z4hY/6,-HwX2H8Z4hY,6,696576dcbd0dc42cb678fa40d8a0f0f419a3072bfa7662d653756ab29bba4c46,3.3580079078674316,7,7,0,7,0.048571428571428564,0.03428571428571422,0.5562952756881714,0.1454559713602066,0.9901678562164307,0.841666579246521,326,21,ok --HwX2H8Z4hY/9,-HwX2H8Z4hY,9,90c18e627f27a12c14e21ba24c79edf3008762b4ac26874b490ad3f888381702,7.733983993530273,22,22,0,22,0.16363636363636375,0.15181818181818188,0.6705501675605774,0.25460928678512573,0.9946621060371399,0.0,764,65,ok --NFrJFQijFE/1,-NFrJFQijFE,1,d8fcf16c6eb51c56947ec3d0549c6f3bc7a0cf1fc5f5d89e8b38d4249a08db4f,5.745999813079834,16,16,0,16,0.46625000000000005,0.47125000000000006,0.7835317254066467,0.27368244528770447,0.9922494292259216,0.0,566,44,ok --NFrJFQijFE/2,-NFrJFQijFE,2,a54a5c144a64f5abd26b19aafa6cea8142ee08e9385fa508fa70c934f6b616c1,6.855999946594238,18,18,0,18,0.17888888888888899,0.1544444444444445,0.7431879639625549,0.24775999784469604,0.9926568269729614,0.0,670,55,ok --THoVjtIkeU/12,-THoVjtIkeU,12,e2f148f4f2e74724dc13b3ce870a0ce6a06740cfc224f5a9b3d0a870b196e7d4,14.896029472351074,39,39,0,39,0.05999999999999991,0.05282051282051286,0.6352806687355042,0.23379945755004883,0.9911767244338989,1.0,1481,106,ok --THoVjtIkeU/2,-THoVjtIkeU,2,35a6c2464ffd68dd96411edb5dc2763f0efb59f264c1d8b737e616fa6b0d1d5b,4.2919921875,10,10,0,10,0.016000000000000004,0.007999999999999985,0.7164996266365051,0.2465074211359024,0.9895758628845215,1.0,424,31,ok --THoVjtIkeU/6,-THoVjtIkeU,6,efaa55ee6394032c867046690a92c29edfd825005f0a090cca5ccb763b227f64,8.097004890441895,30,30,0,30,0.053333333333333295,0.05733333333333333,0.6787540316581726,0.30513063073158264,0.9927164316177368,1.0,799,68,ok --UuX1xuaiiE/1,-UuX1xuaiiE,1,d5bbda38fcec15817d2b87bab5dcc559d6d425f7d28a82e6c32d13f14b48650c,10.350000381469727,27,27,0,27,0.09555555555555556,0.060000000000000046,0.6550575494766235,0.22912898659706116,0.9925051927566528,0.8333339691162109,1027,83,ok --UuX1xuaiiE/0,-UuX1xuaiiE,0,f578b305d53bc152702f5e771de0fcd12d1e9aaefc5cefce3d2082a417aab7c8,3.6333329677581787,9,9,0,9,0.03777777777777775,0.04666666666666665,0.6484582424163818,0.2555619180202484,0.994590699672699,0.9444444179534912,358,25,ok --UuX1xuaiiE/3,-UuX1xuaiiE,3,eddb408f25bdc13e6de2fb74caeed709cb7a8f00640e7897135330437f66a2aa,4.1300129890441895,9,9,0,9,0.07777777777777779,0.0600000000000001,0.7240580320358276,0.16585363447666168,0.992123007774353,0.976190447807312,404,29,ok --UuX1xuaiiE/6,-UuX1xuaiiE,6,f0131ac00e44410fbd32c547a0d421c2791172434fc0203bb969abe14a530532,8.113997459411621,22,22,0,22,0.06363636363636366,0.0736363636363637,0.7064024806022644,0.25750458240509033,0.984533965587616,0.9776423573493958,795,68,ok --a55Q6RWvTA/3,-a55Q6RWvTA,3,15d029fc15f50b268b98f1e8abc65e45582e638c13a018d7aa74a18373275946,22.15397071838379,65,65,0,65,0.2215384615384614,0.18892307692307703,0.6580277681350708,0.23805321753025055,0.9912921786308289,1.0,2209,142,ok --aNfi7CP8vM/7,-aNfi7CP8vM,7,0b6389f45bb966113c65a11998c6e7facdd24c8c42acf2e8cf32e0f2139402e1,8.694987297058105,18,18,0,18,0.2511111111111111,0.24000000000000002,0.7001731395721436,0.23255421221256256,0.9945195913314819,1.0,854,74,ok --aqamKhZ1Ec/0,-aqamKhZ1Ec,0,6f6e674bbba4353399e9e7825217f37e6d8ca1adf9675f33cf37106f31c55548,10.966667175292969,14,13,1,13,0.22461538461538455,0.08615384615384586,0.71061772108078,0.1247716099023819,0.9910455346107483,1.0,1090,86,ok --dxfTGcXJoc/1,-dxfTGcXJoc,1,b5ffdc98a4a98b8f0aae55dee5fed66a43bcb129f47a250a004c1cc74e572595,16.16100311279297,36,36,0,36,0.07777777777777778,0.033333333333333375,0.6812966465950012,0.2449914664030075,0.9900091290473938,1.0,1602,112,ok --dxfTGcXJoc/0,-dxfTGcXJoc,0,04bd0be907fb46c613f926fe1b06bc2c3b30881c293156510baa34a4105ade55,20.5,41,38,3,38,0.09315789473684201,0.06789473684210537,0.7333337664604187,0.209048330783844,0.9891952872276306,0.99895840883255,2042,134,ok --dxfTGcXJoc/2,-dxfTGcXJoc,2,46a5e523b5dd00364c99a3bcbc6fae4c80e1382a84b5b5e681c46eb074ed10f7,16.697982788085938,34,32,2,32,0.048124999999999946,0.03624999999999996,0.6593995094299316,0.2266717106103897,0.9901677966117859,1.0,1664,115,ok --dxfTGcXJoc/6,-dxfTGcXJoc,6,55c1ff86729ab21da743a5107ed07b220e41b4193cd1c0ba9f009e65c3ab0513,12.735026359558105,27,27,0,27,0.05851851851851849,0.05407407407407409,0.715381383895874,0.25197115540504456,0.9889141917228699,1.0,1263,95,ok --egA8-b7-3M/26,-egA8-b7-3M,26,11f78aed680ea9c5862a15e04ff6c1f8776c46d29c98b68d28773ff39d959685,6.030990123748779,15,15,0,15,0.08133333333333341,0.02533333333333337,0.6877890825271606,0.22332797944545746,0.9945786595344543,1.0,593,47,ok --egA8-b7-3M/17,-egA8-b7-3M,17,f967e81e0edd51c3700671721afb3fbecbbc32652f27d2db40ea444e8d80c68f,7.271028995513916,16,16,0,16,0.017499999999999995,0.019999999999999962,0.7292676568031311,0.24067606031894684,0.9916234016418457,1.0,710,60,ok --egA8-b7-3M/18,-egA8-b7-3M,18,fd4bc95a6adfb16a9588b7ed65cc2812186ce3d607804dc76f4486312951ef90,8.386002540588379,22,22,0,22,0.052727272727272734,0.021818181818181796,0.6243576407432556,0.26077014207839966,0.9932008385658264,1.0,827,71,ok --egA8-b7-3M/16,-egA8-b7-3M,16,4c015f85e3bd901ecedde8c0c2ca4a756d9a77dfe4177625c481581f2037ff9c,5.538021087646484,11,11,0,11,0.010909090909090908,0.0181818181818182,0.7375588417053223,0.23636400699615479,0.9940068125724792,1.0,549,43,ok --egA8-b7-3M/13,-egA8-b7-3M,13,cbd627c225ebca37521ae238cb9ec254cad236822f4f37ebfbb039e6c56aea4c,4.18398380279541,11,11,0,11,0.23818181818181816,0.23090909090909092,0.6372604370117188,0.2536529004573822,0.9924017786979675,1.0,403,29,ok --egA8-b7-3M/1,-egA8-b7-3M,1,589a7989b1b4888568c31614a2d6beefba88fb87289c85b94df2d8051500403b,10.266016006469727,20,19,1,19,1.0621052631578947,1.0526315789473684,0.6490206122398376,0.19601602852344513,0.9937204718589783,1.0,1016,83,ok --egA8-b7-3M/6,-egA8-b7-3M,6,2e88a00d5e55863aa956b4b0949fc0e4f2975ccfd83b3194957f6fca86ecfce0,6.264974117279053,12,12,0,12,0.08833333333333332,0.03666666666666665,0.7164138555526733,0.2193591147661209,0.9942464828491211,1.0,619,50,ok --egA8-b7-3M/9,-egA8-b7-3M,9,bcd643f328616312eae9b28e6c9aabbe8acaec3e4c4be58daeb45e3eee4d973c,5.0899739265441895,10,10,0,10,0.007999999999999962,0.011999999999999966,0.597113311290741,0.2590937316417694,0.9939422011375427,1.0,494,38,ok --egA8-b7-3M/20,-egA8-b7-3M,20,719ef133920e74b3ea33925d2bca0270b062199116867568f88ac83cadcd74e8,6.644987106323242,20,20,0,20,0.077,0.021000000000000008,0.6985589861869812,0.2369300276041031,0.992087185382843,1.0,648,54,ok --iRBcNs9oI8/3,-iRBcNs9oI8,3,39c547acd1a8da2ebc6c6ab008191a5676420398a974cd9611cad087f0ccec50,5.620999813079834,8,8,0,8,0.10250000000000009,0.07500000000000001,0.6791599988937378,0.1166667565703392,0.9954468607902527,0.0,554,28,ok --iRBcNs9oI8/7,-iRBcNs9oI8,7,cc7b1c7a06ec41d72007b5c42fb8036f30b66d5cf76e3f093160c22fc5e38081,4.104000091552734,9,9,0,9,0.10222222222222223,0.02666666666666669,0.7135127186775208,0.18537555634975433,0.995795726776123,0.0,401,21,ok --iRBcNs9oI8/6,-iRBcNs9oI8,6,030b0b8d8d4ae47799432ab71b66fcc881f077c5b0feef892c1f146dc0a592e3,2.9030001163482666,5,5,0,5,0.03999999999999999,0.04399999999999998,0.7227271199226379,0.12799954414367676,0.9973600506782532,0.0,283,15,ok --iRBcNs9oI8/9,-iRBcNs9oI8,9,352bdcc73d3622d6abac1b09f2039b211d15b9bf7acee66f0b07783c9b7a4c74,3.4159998893737793,5,5,0,5,0.20800000000000002,0.016000000000000014,0.643750011920929,0.14118166267871857,0.993934154510498,0.0,338,17,ok --iRBcNs9oI8/8,-iRBcNs9oI8,8,72a49e3da2862addcde033bd2fbae957d086533664ca4dcbccd3a851bcd50412,8.093000411987305,21,21,0,21,0.23238095238095247,0.2228571428571429,0.6192578673362732,0.18252728879451752,0.9947929382324219,0.0,803,41,ok --lzEya4AM_4/5,-lzEya4AM_4,5,3b74de8d0e66fd754594f05985e5af3480adcc03555f79225d3b727cb4bed043,7.675000190734863,19,19,0,19,0.12000000000000004,0.09473684210526319,0.7427374720573425,0.2366195172071457,0.9901386499404907,1.0,757,64,ok --lzEya4AM_4/6,-lzEya4AM_4,6,ff5da5afb551001d58100ed2471caea51c741046d5396957efbf40082307ca18,14.7919921875,43,43,0,43,0.05023255813953489,0.024651162790697716,0.7318416833877563,0.2524191737174988,0.9907644391059875,1.0,1475,105,ok --mJ2ud6oKI8/1,-mJ2ud6oKI8,1,c8e3acb4ca08679796c4c8cdfcd8c2b3cffc0465015efaffa1eccdb55ff4f45b,6.103000164031982,13,13,0,13,0.733846153846154,0.7399999999999998,0.8174015879631042,0.1573781669139862,1.0,0.0,606,31,ok --mJ2ud6oKI8/2,-mJ2ud6oKI8,2,c41790f8b75f886bd1f5d6d72cbab1985306d0b715e5ae47203f3d0c8a3e7b28,5.730999946594238,11,11,0,11,0.4636363636363635,0.46181818181818185,0.9266790151596069,0.2666672170162201,1.0,0.0,571,29,ok --mJ2ud6oKI8/6,-mJ2ud6oKI8,6,134a3a4ebbc423760133b0da0e90cfe84d75ea85df3968000afd84153c5d828d,2.256999969482422,5,5,0,5,0.11199999999999996,0.06400000000000003,0.6512578129768372,0.15656699240207672,0.9862568378448486,1.0,223,12,ok --mJ2ud6oKI8/9,-mJ2ud6oKI8,9,df3442f3ed8f894b507923e87e426ae9636790a4a502d00c350a215270cc3e47,7.0329999923706055,22,22,0,22,0.11999999999999994,0.09454545454545453,0.5777366757392883,0.25714901089668274,0.9846946001052856,0.9856857061386108,691,35,ok --mJ2ud6oKI8/8,-mJ2ud6oKI8,8,6af6614c9838417a48c4817f4dd5bf1e6669eb5f78f983e9a68adc113fcdc7cc,4.191999912261963,11,11,0,11,0.14363636363636367,0.06363636363636366,0.6529467701911926,0.26233649253845215,0.9846959114074707,1.0,418,21,ok --mqbVkbCndg/0,-mqbVkbCndg,0,cdeba953bba30907814acf72f3e35582dec263eaa25bdd922dad7fafe02e4dda,6.466667175292969,12,12,0,12,0.06166666666666665,0.03333333333333339,0.7074670791625977,0.20000411570072174,0.9905118346214294,1.0,639,53,ok --t217m2on-s/2,-t217m2on-s,2,6713a983112173204502dc5adbb886bc6c38554b4627698611931420c47663a8,5.6860032081604,12,12,0,12,0.21666666666666665,0.2333333333333333,0.6279765367507935,0.16491496562957764,0.9959543347358704,1.0,564,45,ok --t217m2on-s/7,-t217m2on-s,7,41c76b8a733ecb780d56348f55d00f0ba0c07f44f46e93044e62d876710180b7,17.183008193969727,45,45,0,45,0.048444444444444436,0.017777777777777892,0.6867958903312683,0.23202678561210632,0.9928514361381531,1.0,1703,117,ok --tANM6ETl_M/3,-tANM6ETl_M,3,6d3af064c060dad3816a9e1dfa00101faebd8b7da7d8ceea85b0bc0fca70abd6,6.758008003234863,22,22,0,22,0.030909090909090896,0.021818181818181792,0.5859207510948181,0.2757546901702881,0.9936580061912537,0.9898989200592041,661,54,ok --tPCytz4rww/11,-tPCytz4rww,11,6dc09d02467baaef67594ff32cffb01f8ed1565cda4c5abd161b8261a51e2e5d,5.466991901397705,17,17,0,17,0.09764705882352945,0.08588235294117644,0.6753751635551453,0.28518491983413696,0.9890678524971008,1.0,538,43,ok --tPCytz4rww/10,-tPCytz4rww,10,758183192cbd5f0f20823d26ece3ddee40dec0aadec35247b2495510a53f52f8,4.788997173309326,12,12,0,12,0.04499999999999999,0.00833333333333334,0.5449775457382202,0.225633442401886,0.9894654750823975,1.0,468,35,ok --tPCytz4rww/12,-tPCytz4rww,12,e3c7f9cd67ad2d20fef997696dc278361f97f027db58762e22104e5720d509d5,11.863997459411621,26,26,0,26,0.14461538461538456,0.08769230769230774,0.654129683971405,0.22372934222221375,0.9875938892364502,1.0,1174,91,ok --tPCytz4rww/16,-tPCytz4rww,16,8b3f82f9628792eebaf8c227becc2ebeba59bb8abb668bcca86e07fb1a992a93,7.205989837646484,16,16,0,16,0.05125000000000004,0.013749999999999984,0.4489554166793823,0.17846456170082092,0.988937258720398,1.0,714,59,ok --tPCytz4rww/18,-tPCytz4rww,18,eece70451e9c37a4b5f375bf646f66e09113fe3467f35bf1720cc14d986c1776,6.644987106323242,16,16,0,16,0.16375,0.1275,0.6719247698783875,0.22222484648227692,0.9872123599052429,1.0,657,54,ok --vxjVxOeScU/4,-vxjVxOeScU,4,00282df9a314394f19d616d561bd1916d1d30dca4c814dfb43630ca164f4c719,9.127017974853516,21,21,0,21,0.06380952380952383,0.037142857142857144,0.6465563774108887,0.2219761461019516,0.9960808753967285,1.0,904,77,ok --wMB_hJL-3o/7,-wMB_hJL-3o,7,04a73d73fd150b07edab8e652fd14c9cb4a0f6e017ea97b17e8146e377b9fae7,6.044010162353516,22,22,0,22,0.012727272727272738,0.021818181818181816,0.658498227596283,0.31481292843818665,0.9895980954170227,0.9836065769195557,598,48,ok --wny0OAz3g8/1,-wny0OAz3g8,1,c5535859f129ce04da5f5b5104d02d4168057b9d947a5349d423278ad4f3d8e8,6.844009876251221,23,22,1,22,0.013636363636363648,0.011818181818181823,0.62252277135849,0.3443901240825653,0.995954155921936,0.9950981140136719,678,56,ok --wny0OAz3g8/0,-wny0OAz3g8,0,1cc21b4432e2f4b592284ee40558a18acc7d208019117aebdb2f6a1b67ea198d,3.3333330154418945,9,9,0,9,0.32000000000000006,0.2866666666666667,0.6052471995353699,0.2736770212650299,0.9955413937568665,0.9999999403953552,328,21,ok --wny0OAz3g8/3,-wny0OAz3g8,3,ea917c506bc9fa39460f2b722f7c416f646312bb17cd74baa618905b54837bce,6.146028995513916,20,20,0,20,0.022999999999999986,0.02399999999999995,0.7014381289482117,0.3213139474391937,0.9980819821357727,0.9895832538604736,610,49,ok --wny0OAz3g8/2,-wny0OAz3g8,2,1825fb37db2e914fb616cd80aebd613afd873eecb7edd4d0b53158bfda0e522a,6.686978816986084,23,23,0,23,0.02869565217391302,0.026086956521739167,0.7553136348724365,0.33939871191978455,0.9957627058029175,0.9848485589027405,653,54,ok --wny0OAz3g8/5,-wny0OAz3g8,5,6c6a8a4cba654b25190ab1793bfae81c3d2159ecd6cbc02d3fcbd598543acce0,6.9119791984558105,20,20,0,20,0.004999999999999982,0.004999999999999982,0.6063091158866882,0.3181923031806946,0.9961636066436768,0.9895831346511841,675,56,ok --wny0OAz3g8/7,-wny0OAz3g8,7,cbf9cac1048ce191aef781d0c4563eb97f9f3ddd52eb1f9551fa78d31d70e7cd,8.06796932220459,29,29,0,29,0.0186206896551724,0.017241379310344838,0.6700748205184937,0.3224986493587494,0.9956274628639221,1.0,792,68,ok --wny0OAz3g8/9,-wny0OAz3g8,9,b76f70fe783ee76bf1b637137226c98e67d13a6b15ec725894175b36cd76a136,6.2130208015441895,20,20,0,20,0.025999999999999975,0.027000000000000024,0.6688015460968018,0.3180274963378906,0.9969837069511414,0.9672130942344666,605,49,ok --571d8cVauQ/0,-571d8cVauQ,0,defc62e1530d9b0cd27f2acfe042b71dd84d7e8c85f1df261f04912091976088,5.066667079925537,12,12,0,12,0.07500000000000001,0.03000000000000001,0.6978414058685303,0.2360049933195114,0.9903978705406189,1.0,500,39,ok --571d8cVauQ/5,-571d8cVauQ,5,e304c03fac1f477823fe0926c4fb421b9c4e4091f85718b729afe856c24a7d3e,15.272981643676758,43,43,0,43,0.14604651162790694,0.11534883720930222,0.7017207741737366,0.23815667629241943,0.9918006062507629,1.0,1512,108,ok --I_e4mIh0yE/1,-I_e4mIh0yE,1,8453a966d4bd1f0179eb86a35cd34c0864a3a3bc2fa86f37783060cc0d14f5df,7.622004985809326,18,18,0,18,0.061111111111111116,0.02333333333333332,0.6546477675437927,0.2152525633573532,0.985649049282074,1.0,745,63,ok --I_e4mIh0yE/3,-I_e4mIh0yE,3,a015f02ae51d74c42ad27e2a0831263a303f0658ac8d984819e27ad61342b23e,9.163021087646484,22,22,0,22,0.13,0.11545454545454543,0.6251755356788635,0.24003465473651886,0.9852646589279175,1.0,900,77,ok --UacrmKiTn4/10,-UacrmKiTn4,10,00312e0602dbeac970de5d7dd0e8a970e514fe45d7fe6625b4f454b299e36360,7.361979007720947,18,18,0,18,0.04555555555555555,0.07222222222222224,0.47940683364868164,0.20824021100997925,0.9955651164054871,1.0,725,60,ok --UacrmKiTn4/4,-UacrmKiTn4,4,a7f2ab0d6ee2e2a2d5cd4239f03e6cac67c618ddb744891323df3ff87e29af84,4.741015911102295,14,14,0,14,0.06714285714285716,0.09857142857142863,0.7214669585227966,0.246806800365448,0.9926760792732239,1.0,469,35,ok --hnBHBN8p5A/7,-hnBHBN8p5A,7,0ec6fb76226315d3fafbb483e3500e60cc8a6729617b10e4b4b76163595080fb,7.372000217437744,13,13,0,13,0.01846153846153847,0.021538461538461593,0.657243549823761,0.1729772984981537,0.9905768632888794,0.0,731,37,ok --hnBHBN8p5A/6,-hnBHBN8p5A,6,997f6808ac3973ddd71800e91c8e10755c10b5037186d84348a79e00d672fdc7,6.401000022888184,13,13,0,13,0.04307692307692312,0.012307692307692353,0.7618876099586487,0.22187285125255585,0.9932082295417786,0.0,634,32,ok --qDkUB0GgYY/6,-qDkUB0GgYY,6,ab19bf4a761d3919b7113b1104ccaadbbf0c4e7b45694904d094280a2c329c8b,4.677995204925537,16,16,0,16,0.033749999999999974,0.02250000000000002,0.6504627466201782,0.24682332575321198,0.9946085214614868,1.0,462,35,ok --uywlfIYOS8/4,-uywlfIYOS8,4,fde46f5222cf5cfec7af9c93214c972ce2d686b0bf9c90a291021601968986f9,6.044987201690674,18,18,0,18,0.0433333333333333,0.04333333333333334,0.6908547878265381,0.25089454650878906,0.9957761168479919,1.0,589,48,ok --6rXp3zJ3kc/8,-6rXp3zJ3kc,8,59b77a0f873b7fa95e7327b93d64bb5a4bdae84039321988ef70bba8e63ee1ae,12.805012702941895,34,34,0,34,0.06470588235294118,0.034705882352941086,0.63474440574646,0.22114422917366028,0.9899758696556091,1.0,1274,95,ok --9y-fZ3swSY/0,-9y-fZ3swSY,0,29a1fd181293cdbe24e50edcad51e3cc0f27a5824d840bcc39d453b272fb6e3c,6.8333330154418945,22,22,0,22,0.023636363636363688,0.019999999999999997,0.5440928339958191,0.2264895737171173,0.9948647022247314,1.0,676,57,ok --9y-fZ3swSY/4,-9y-fZ3swSY,4,fe04a26710e85c58bdaad5a48618c7e0f742d82b0d920eb4a046c8f14a6921dc,2.8210289478302,9,9,0,9,0.1711111111111111,0.15999999999999998,0.5274830460548401,0.1851968914270401,0.9926167726516724,1.0,267,15,ok --9y-fZ3swSY/8,-9y-fZ3swSY,8,6140d031e614b62a5d8df73346fef2417c28cee3501310aa95aa40d358b4b256,4.988996982574463,12,12,0,12,0.07333333333333339,0.05333333333333331,0.562736988067627,0.18345493078231812,0.9931800365447998,0.9487179517745972,492,37,ok --AUZQgSxyPQ/2,-AUZQgSxyPQ,2,e09034b30bb4f8fb9f9c2568afc20f2a764e327fe6ef4e13f21804eaac51bb7b,22.511003494262695,41,41,0,41,0.6434146341463415,0.6102439024390245,0.6386448740959167,0.19374850392341614,0.9917553663253784,1.0,2241,144,ok --HeZS2-Prhc/2,-HeZS2-Prhc,2,edb0fa22fdfbd990c8174764af78670bd2ecad799240d35d96a1124a3cd9dc0c,8.261979103088379,16,16,0,16,0.14125000000000004,0.08125000000000016,0.6830984950065613,0.15250585973262787,0.9933875799179077,1.0,816,70,ok --MeTTeMJBNc/0,-MeTTeMJBNc,0,54e2097f7bdb455d243e72254e5af7ed16160739f2f3cfd22f57d2729ec1acbe,9.300000190734863,21,21,0,21,0.03714285714285711,0.026666666666666637,0.6400595903396606,0.22926528751850128,0.9939717650413513,1.0,922,78,ok --MeTTeMJBNc/13,-MeTTeMJBNc,13,80c5d996e5d7b61c58e1fe32d706efcaf80c8c8cddb5c37a5c66d527786c2a44,5.430013179779053,14,14,0,14,0.042857142857142864,0.00714285714285715,0.6661255359649658,0.2075468748807907,0.9918515682220459,1.0,526,41,ok --MeTTeMJBNc/7,-MeTTeMJBNc,7,40716dc7402fd6398038eded58ce939ec76be6afbeea346b968bf4c427088f3a,10.51699161529541,31,31,0,31,0.03225806451612902,0.02387096774193552,0.7313360571861267,0.269477516412735,0.9934103488922119,1.0,1042,84,ok --RfYyzHpjk4/11,-RfYyzHpjk4,11,96e481cd732001239639c8cb4e7f94e570925e5a15940920ffab0cec1f13f904,5.238996982574463,17,17,0,17,0.018823529411764742,0.025882352941176467,0.6960803866386414,0.27842891216278076,0.9958056807518005,1.0,508,40,ok --RfYyzHpjk4/8,-RfYyzHpjk4,8,ed8c672c532b8c7d1c830c82d6e2c14fcb3bbd3dc1a86670a03a6c8e83c02f3c,4.588996887207031,17,17,0,17,0.04588235294117646,0.005882352941176463,0.684955358505249,0.27527740597724915,0.994469404220581,1.0,454,33,ok --RfYyzHpjk4/2,-RfYyzHpjk4,2,5e428ee22de58c9d6561b9b4353bef9dfb811a5841d9ab07b5bc453d697ad17f,5.516016006469727,25,25,0,25,0.12960000000000005,0.12880000000000008,0.7175998091697693,0.3444570004940033,0.9948742389678955,1.0,540,43,ok --UUCSKoHeMA/0,-UUCSKoHeMA,0,3f9792888ec8e969f61cfb6cb4de7bdf7ef8944afe0a9d2a9d13586e1f13b898,7.800000190734863,18,18,0,18,0.23000000000000004,0.20999999999999996,0.666740894317627,0.22424933314323425,0.9943835139274597,1.0,774,66,ok --ri04Z7vwnc/0,-ri04Z7vwnc,0,93021c70c8fad20ad3fded80e7fc790a2f9c96835de58a3b694c6906de42684b,2.806999921798706,8,8,0,8,0.35999999999999993,0.3525,0.7826409935951233,0.25714799761772156,0.9982975125312805,0.0,277,14,ok --ri04Z7vwnc/2,-ri04Z7vwnc,2,f5993ce3a6ee56298462c08692a96f78c7d914d7264257ed401de7d6e17fd148,6.0269999504089355,16,16,0,16,0.23374999999999996,0.22875,0.7431082725524902,0.26666611433029175,0.9971521496772766,0.9906440377235413,592,30,ok --ri04Z7vwnc/5,-ri04Z7vwnc,5,2a5e4319bf592a18c8eb5117f7c7ec30c6c79528f9eac9fe4fb85bf70f277736,3.5450000762939453,9,8,1,8,0.21249999999999986,0.23999999999999994,0.721091628074646,0.21714359521865845,0.9974266886711121,1.0,344,18,ok --s9qJ7ATP7w/1,-s9qJ7ATP7w,1,a33e8f82a185bcb7648b523927308cdc2142e3076479ba2b45cd0e828636fc09,4.7919921875,11,11,0,11,0.01636363636363641,0.021818181818181816,0.7055363059043884,0.16956037282943726,0.9860281348228455,1.0,465,35,ok --s9qJ7ATP7w/0,-s9qJ7ATP7w,0,f2324dbc6debe0d1e4254e6f943523373e3cbb30d8d0555413ce3a7b370a4af5,6.800000190734863,24,24,0,24,0.056666666666666664,0.029999999999999957,0.6351987719535828,0.2500007152557373,0.9885490536689758,0.984375,672,56,ok --s9qJ7ATP7w/5,-s9qJ7ATP7w,5,bd35eb8de64ce1f8b27921294598f7cf5bb971255738f51d06458c7096c58eae,8.561002731323242,19,19,0,19,0.25578947368421046,0.26210526315789456,0.5150972604751587,0.16428017616271973,0.9896790981292725,1.0,840,72,ok --s9qJ7ATP7w/4,-s9qJ7ATP7w,4,76e0672ffce5857a789b41fb10606402f7da58c33579b1032a8282f86fb35bc9,4.427018165588379,9,9,0,9,0.07555555555555557,0.024444444444444453,0.6215080618858337,0.20000608265399933,0.9892621040344238,0.96875,425,31,ok --s9qJ7ATP7w/7,-s9qJ7ATP7w,7,5301f4403cf7cd299cc525d2f443392ac70fd70c3c9cd4a09406f2ba4df6734d,6.966015815734863,28,28,0,28,0.029285714285714304,0.02428571428571429,0.661829948425293,0.29855138063430786,0.9849807620048523,0.9496123194694519,684,57,ok --s9qJ7ATP7w/6,-s9qJ7ATP7w,6,40b684fd1b4559f0f82e72f9b47f4ce7c5e15059fe8d0d8ab112637cd3386451,2.4749999046325684,5,5,0,5,0.21599999999999997,0.16400000000000006,0.8113580942153931,0.14165958762168884,0.9844902753829956,1.0,232,14,ok --s9qJ7ATP7w/8,-s9qJ7ATP7w,8,1de4d91bd9d9fb508a3779658747da88460db0bdb1beefe7ea5b2c77edfd2239,3.2949869632720947,13,12,1,12,0.07166666666666661,0.06166666666666667,0.6465047001838684,0.2687399089336395,0.9880942702293396,0.9731181859970093,319,20,ok --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,2f16da1baa8660e5bfc608f5237cdd59725d16e57a19bc02c4556cd2c7129a46,29.288021087646484,49,49,0,49,0.2922448979591836,0.2689795918367347,0.6873865723609924,0.18630558252334595,0.9836021065711975,0.999393880367279,2911,178,ok --yRb-Jum7EQ/5,-yRb-Jum7EQ,5,6d6145293cf84d1fc8324dfa8d39465e2d7fc07affb67ff68deeabf6e3c410d9,13.169010162353516,25,25,0,25,0.14880000000000007,0.18799999999999997,0.7192046046257019,0.19541765749454498,0.9867846369743347,1.0,1305,97,ok --yRb-Jum7EQ/6,-yRb-Jum7EQ,6,b51eb9ad06de804934cb6a315de591ba9ff7f8aa71bffff7f8001ab29945d989,11.241994857788086,19,19,0,19,0.09578947368421038,0.15263157894736842,0.6869907975196838,0.16814078390598297,0.9854583740234375,1.0,1125,87,ok diff --git a/math/Q1/results/model_comparison/typical_alignment_example.png b/math/Q1/results/model_comparison/typical_alignment_example.png deleted file mode 100644 index d56096b..0000000 Binary files a/math/Q1/results/model_comparison/typical_alignment_example.png and /dev/null differ diff --git a/math/Q1/results/model_comparison/word_alignment_posterior.csv b/math/Q1/results/model_comparison/word_alignment_posterior.csv deleted file mode 100644 index e5714f8..0000000 --- a/math/Q1/results/model_comparison/word_alignment_posterior.csv +++ /dev/null @@ -1,1933 +0,0 @@ -sample_id,video_id,clip_id,word_index,word,hard_start_s,hard_end_s,hard_valid,ctc_quality_score_uncalibrated,relative_quality_weight,start_mean_s,end_mean_s,start_p05_s,start_p95_s,end_p05_s,end_p95_s,start_width90_s,end_width90_s --3g5yACwYnA/13,-3g5yACwYnA,13,0,They've,0.0024999999441206455,0.5625,True,3.1319849491673324e-11,4.0,0.019184879635086593,0.5625060804898443,0.0025000000000000005,0.10250000000000001,0.5625,0.5625,0.1,0.0 --3g5yACwYnA/13,-3g5yACwYnA,13,1,been,1.222499966621399,1.3624999523162842,True,5.074469056759456e-12,2.26932692527771,1.2063062407761618,1.38194823633117,1.1425,1.2625,1.3625,1.4224999999999999,0.11999999999999988,0.05999999999999983 --3g5yACwYnA/13,-3g5yACwYnA,13,2,able,1.4424999952316284,1.6024999618530273,True,2.422228541874849e-13,0.25,1.4426709260933925,1.5958374384159129,1.4425,1.4425,1.5825,1.6025,0.0,0.020000000000000018 --3g5yACwYnA/13,-3g5yACwYnA,13,3,to,1.622499942779541,1.7024999856948853,True,1.4663940634679351e-12,0.6557784676551819,1.63353469473686,1.702500930802706,1.6225,1.6425,1.7025,1.7025,0.020000000000000018,0.0 --3g5yACwYnA/13,-3g5yACwYnA,13,4,find,1.7625000476837158,2.0225000381469727,True,2.2361119032809906e-12,1.0,1.7625198227574603,2.022487282563605,1.7625,1.7625,2.0225,2.0225,0.0,0.0 --3g5yACwYnA/13,-3g5yACwYnA,13,5,solutions,2.1624999046325684,2.6424999237060547,True,7.178173853927827e-12,3.210113763809204,2.162477129647909,2.642508732091731,2.1625,2.1625,2.6425,2.6425,0.0,0.0 --3g5yACwYnA/13,-3g5yACwYnA,13,6,or,2.7225000858306885,2.802500009536743,True,1.8666060017102915e-11,4.0,2.7225030011118756,2.8025052458122928,2.7225,2.7225,2.8025,2.8025,0.0,0.0 --3g5yACwYnA/13,-3g5yACwYnA,13,7,at,3.0225000381469727,3.122499942779541,True,7.055260780979011e-13,0.3155146539211273,3.0114486420923248,3.1096179351127704,2.9425,3.0225,3.0425,3.1225,0.08000000000000007,0.08000000000000007 --3g5yACwYnA/13,-3g5yACwYnA,13,8,least,3.1624999046325684,3.382499933242798,True,4.716877496230287e-12,2.109410285949707,3.1602214981987653,3.377016650868552,3.1225,3.1625,3.3625,3.3825,0.040000000000000036,0.020000000000000018 --3g5yACwYnA/13,-3g5yACwYnA,13,9,bring,3.4625000953674316,3.7225000858306885,True,5.437177401021454e-13,0.25,3.4542782483017413,3.707435340678973,3.3825,3.4625,3.6825,3.7225,0.08000000000000007,0.040000000000000036 --3g5yACwYnA/13,-3g5yACwYnA,13,10,some,3.762500047683716,3.9625000953674316,True,4.003620351911152e-12,1.7904382944107056,3.7678537500060894,3.962399443995387,3.7625,3.8025,3.9625,3.9625,0.040000000000000036,0.0 --3g5yACwYnA/13,-3g5yACwYnA,13,11,answers,4.002500057220459,4.322500228881836,True,3.1072377743718294e-12,1.3895716667175293,4.002374694620699,4.31993317940175,4.0025,4.0025,4.3025,4.322500000000001,0.0,0.020000000000000462 --3g5yACwYnA/13,-3g5yACwYnA,13,12,to,4.362500190734863,4.422500133514404,True,1.1880822931367718e-13,0.25,4.360161068296207,4.4264563847068485,4.3425,4.402500000000001,4.4225,4.4625,0.0600000000000005,0.040000000000000036 --3g5yACwYnA/13,-3g5yACwYnA,13,13,the,4.462500095367432,4.5625,True,2.673985605692892e-15,0.25,4.469530870157028,4.569707820997299,4.4625,4.482500000000001,4.562500000000001,4.5825000000000005,0.020000000000000462,0.019999999999999574 --3g5yACwYnA/13,-3g5yACwYnA,13,14,table.,4.602499961853027,4.882500171661377,True,1.6668160992064363e-13,0.25,4.602502613481098,4.882542159056495,4.602500000000001,4.602500000000001,4.8825,4.8825,0.0,0.0 --3g5yACwYnA/3,-3g5yACwYnA,3,0,We're,0.0024999999441206455,0.16249999403953552,True,1.0417753465441493e-10,4.0,0.01892479479475388,0.3908951550217483,0.0025000000000000005,0.0425,0.1625,0.8624999999999999,0.04,0.7 --3g5yACwYnA/3,-3g5yACwYnA,3,1,a,0.20250000059604645,0.2224999964237213,True,2.0192024051055024e-13,0.25,0.5809306189576965,0.6009306189578986,0.2025,1.2425,0.2225,1.2625,1.04,1.04 --3g5yACwYnA/3,-3g5yACwYnA,3,2,huge,0.6025000214576721,0.862500011920929,True,2.080993537212361e-11,4.0,0.8749699312498749,1.1586938794079154,0.6024999999999999,1.3625,0.8624999999999999,1.6625,0.7600000000000001,0.8000000000000002 --3g5yACwYnA/3,-3g5yACwYnA,3,3,user,1.3624999523162842,1.662500023841858,True,1.8008346550080212e-11,4.0,1.6450011455096585,1.9430967049678605,1.3625,2.2425,1.6625,2.5025,0.8800000000000001,0.8399999999999999 --3g5yACwYnA/3,-3g5yACwYnA,3,4,of,2.422499895095825,2.4825000762939453,True,2.5086363108356435e-12,0.6720010638237,2.3888363472402654,2.5262128094487677,2.1625,2.6025,2.4425,2.6625,0.43999999999999995,0.2200000000000002 --3g5yACwYnA/3,-3g5yACwYnA,3,5,adhesives,2.6424999237060547,3.262500047683716,True,1.9735572551193847e-11,4.0,2.6479228501381638,3.2627808520362973,2.5625,2.7225,3.2625,3.2625,0.16000000000000014,0.0 --3g5yACwYnA/3,-3g5yACwYnA,3,6,for,3.302500009536743,3.4825000762939453,True,5.313816608953914e-10,4.0,3.305240723840881,3.485738646070515,3.3025,3.3025,3.4825,3.4825,0.0,0.0 --3g5yACwYnA/3,-3g5yACwYnA,3,7,our,3.5625,4.34250020980835,True,1.8105811988577969e-12,0.4850095212459564,3.6584500267844233,4.351316019909387,3.5625,4.202500000000001,4.3425,4.442500000000001,0.6400000000000006,0.10000000000000053 --3g5yACwYnA/3,-3g5yACwYnA,3,8,"operation,",4.582499980926514,5.142499923706055,True,2.16136266870115e-12,0.5789751410484314,4.582841088198986,5.142577850811578,4.5825000000000005,4.5825000000000005,5.1425,5.1425,0.0,0.0 --3g5yACwYnA/3,-3g5yACwYnA,3,9,called,5.502500057220459,5.78249979019165,True,7.694975732996934e-12,2.0612919330596924,5.469346469231026,5.787966327255339,5.242500000000001,5.5425,5.782500000000001,5.8425,0.2999999999999998,0.05999999999999961 --3g5yACwYnA/3,-3g5yACwYnA,3,10,"flocking,",5.862500190734863,6.242499828338623,True,3.7366615877887366e-12,1.0009584426879883,5.862416384166256,6.255591073381409,5.862500000000001,5.862500000000001,6.242500000000001,6.2625,0.0,0.019999999999999574 --3g5yACwYnA/3,-3g5yACwYnA,3,11,and,6.602499961853027,6.742499828338623,True,3.1151616659494397e-13,0.25,6.595235466538168,6.747981306446609,6.282500000000001,6.6225000000000005,6.702500000000001,6.742500000000001,0.33999999999999986,0.040000000000000036 --3g5yACwYnA/3,-3g5yACwYnA,3,12,we,7.022500038146973,7.082499980926514,True,3.7330837206195344e-12,1.0,7.025503971831001,7.085534043478729,7.022500000000001,7.022500000000001,7.0825000000000005,7.0825000000000005,0.0,0.0 --3g5yACwYnA/3,-3g5yACwYnA,3,13,don't,7.162499904632568,7.34250020980835,True,1.3746884186538466e-10,4.0,7.163477889296987,7.344480228729067,7.142500000000001,7.1625000000000005,7.3425,7.3425,0.019999999999999574,0.0 --3g5yACwYnA/3,-3g5yACwYnA,3,14,have,7.522500038146973,7.662499904632568,True,1.6831982923887386e-14,0.25,7.518314039598685,7.660886400412066,7.482500000000001,7.522500000000001,7.6225000000000005,7.702500000000001,0.040000000000000036,0.08000000000000007 --3g5yACwYnA/3,-3g5yACwYnA,3,15,the,7.722499847412109,7.882500171661377,True,8.987861453355062e-13,0.25,7.7243982678780885,7.882159094863079,7.7225,7.7625,7.862500000000001,7.8825,0.040000000000000036,0.019999999999999574 --3g5yACwYnA/3,-3g5yACwYnA,3,16,technical,8.022500038146973,8.662500381469727,True,1.3002188301719508e-12,0.348296195268631,8.011902283844488,8.662006267621967,7.942500000000001,8.0425,8.6625,8.6625,0.09999999999999964,0.0 --3g5yACwYnA/3,-3g5yACwYnA,3,17,inside,8.72249984741211,9.0024995803833,True,2.5177188350648805e-13,0.25,8.71091233648601,9.001311320857447,8.6825,8.7225,8.9825,9.0025,0.040000000000000924,0.019999999999999574 --3g5yACwYnA/3,-3g5yACwYnA,3,18,compounding,9.40250015258789,10.22249984741211,True,6.742292813465001e-13,0.25,9.359030940393758,10.232189826338123,9.022499999999999,9.4025,10.2225,10.3025,0.3800000000000008,0.08000000000000007 --3g5yACwYnA/3,-3g5yACwYnA,3,19,or,10.342499732971191,10.40250015258789,True,2.5491054037561633e-13,0.25,10.398864243814538,10.46224094293215,10.3425,10.5025,10.4025,10.5625,0.16000000000000014,0.16000000000000014 --3g5yACwYnA/3,-3g5yACwYnA,3,20,the,10.5024995803833,10.682499885559082,True,1.6563738770326852e-13,0.25,10.54237820403615,10.694267109284878,10.4625,10.6625,10.5625,10.782499999999999,0.1999999999999993,0.21999999999999886 --3g5yACwYnA/3,-3g5yACwYnA,3,21,technical,10.802499771118164,11.242500305175781,True,3.798831735291053e-11,4.0,10.778501265601966,11.232468921558434,10.5825,10.8425,10.9625,11.3825,0.2599999999999998,0.41999999999999993 --3g5yACwYnA/3,-3g5yACwYnA,3,22,expertise,11.362500190734863,11.90250015258789,True,2.313237492182485e-12,0.6196585893630981,11.339150095742763,11.878519378812266,10.9825,11.4225,11.4825,11.942499999999999,0.4399999999999995,0.4599999999999991 --3g5yACwYnA/3,-3g5yACwYnA,3,23,to,11.962499618530273,12.022500038146973,True,2.884898700136751e-12,0.772792398929596,11.943536876391573,12.008612822373081,11.6025,12.0025,11.6825,12.0825,0.40000000000000036,0.40000000000000036 --3g5yACwYnA/3,-3g5yACwYnA,3,24,do,12.1225004196167,12.202500343322754,True,8.551721136784707e-11,4.0,12.100686304121547,12.180724080264547,11.8225,12.1225,11.9025,12.2025,0.3000000000000007,0.3000000000000007 --3g5yACwYnA/3,-3g5yACwYnA,3,25,these,12.242500305175781,13.162500381469727,True,2.1788269105593727e-11,4.0,12.236831720783304,13.084602136464406,12.0025,12.2425,12.3225,13.1825,0.2400000000000002,0.8599999999999994 --3g5yACwYnA/3,-3g5yACwYnA,3,26,types,13.202500343322754,13.462499618530273,True,1.7226959442284695e-11,4.0,13.170666582865142,13.46226141424027,12.9225,13.2025,13.3825,13.7225,0.28000000000000114,0.33999999999999986 --3g5yACwYnA/3,-3g5yACwYnA,3,27,of,13.702500343322754,13.802499771118164,True,6.332336998510213e-12,1.6962751150131226,13.783998039741556,13.89545682407746,13.4625,13.9225,13.7225,14.0025,0.4599999999999991,0.27999999999999936 --3g5yACwYnA/3,-3g5yACwYnA,3,28,things.,13.922499656677246,14.262499809265137,True,1.0484706852720294e-11,2.808591365814209,13.996225018186697,14.291213862031034,13.9225,14.0625,14.2625,14.3225,0.14000000000000057,0.0600000000000005 --3g5yACwYnA/2,-3g5yACwYnA,2,0,Key,0.12250000238418579,0.2824999988079071,True,1.2059077694748233e-12,0.46602973341941833,0.12004656147855662,0.2754928971448747,0.0025000000000000005,0.1825,0.2025,0.28250000000000003,0.18,0.08000000000000002 --3g5yACwYnA/2,-3g5yACwYnA,2,1,Polymer,1.4225000143051147,1.9824999570846558,True,1.2241609635699202e-11,4.0,1.2243119624106564,1.9746772787439282,0.2625,1.4224999999999999,1.5225,2.0225,1.16,0.5 --3g5yACwYnA/2,-3g5yACwYnA,2,2,brings,2.0425000190734863,2.302500009536743,True,1.1930802483114955e-12,0.46107247471809387,2.0715362022919037,2.346903905400217,1.8625,2.1025,2.2425,2.5225,0.24,0.2799999999999998 --3g5yACwYnA/2,-3g5yACwYnA,2,3,a,2.502500057220459,2.5225000381469727,True,2.7638483949404824e-12,1.0681045055389404,2.5343152915969336,2.5543152915969847,2.5025,2.6425,2.5225,2.6625,0.14000000000000012,0.14000000000000012 --3g5yACwYnA/2,-3g5yACwYnA,2,4,technical,2.922499895095825,3.682499885559082,True,6.836649302233155e-11,4.0,2.945770103472421,3.662219509655508,2.9225,2.9225,3.5425,3.6825,0.0,0.14000000000000012 --3g5yACwYnA/2,-3g5yACwYnA,2,5,aspect,3.762500047683716,4.102499961853027,True,7.779469071971662e-14,0.25,3.762773828203278,4.127419794909451,3.6625,3.8225000000000002,4.1025,4.1625000000000005,0.16000000000000014,0.0600000000000005 --3g5yACwYnA/2,-3g5yACwYnA,2,6,to,4.382500171661377,4.442500114440918,True,2.0063360695043997e-11,4.0,4.397380835314191,4.461387623157674,4.3825,4.3825,4.442500000000001,4.522500000000001,0.0,0.08000000000000007 --3g5yACwYnA/2,-3g5yACwYnA,2,7,our,4.502500057220459,4.862500190734863,True,9.0564179419661e-12,3.4999029636383057,4.554801215071612,4.891103084451879,4.5025,4.6225000000000005,4.862500000000001,4.862500000000001,0.1200000000000001,0.0 --3g5yACwYnA/2,-3g5yACwYnA,2,8,operation,5.462500095367432,6.142499923706055,True,2.41139139905977e-12,0.9318955540657043,5.434152783262643,6.164972441664202,5.282500000000001,5.5025,6.142500000000001,6.3825,0.21999999999999975,0.23999999999999932 --3g5yACwYnA/2,-3g5yACwYnA,2,9,that,6.222499847412109,6.382500171661377,True,2.55808666350249e-13,0.25,6.2506696287137125,6.425851613401193,6.2225,6.5025,6.3825,6.742500000000001,0.28000000000000025,0.3600000000000003 --3g5yACwYnA/2,-3g5yACwYnA,2,10,we,6.682499885559082,6.742499828338623,True,3.615498471356421e-13,0.25,6.68956208113118,6.750288014655133,6.6825,6.822500000000001,6.742500000000001,6.8825,0.14000000000000057,0.13999999999999968 --3g5yACwYnA/2,-3g5yACwYnA,2,11,don't,6.822500228881836,7.002500057220459,True,1.598295940041794e-10,4.0,6.829173580026902,7.0141967823015605,6.822500000000001,6.9225,6.982500000000001,7.1625000000000005,0.09999999999999964,0.17999999999999972 --3g5yACwYnA/2,-3g5yACwYnA,2,12,have,7.042500019073486,7.202499866485596,True,5.563233250807653e-13,0.25,7.07007014122585,7.245521610851821,7.0425,7.282500000000001,7.202500000000001,7.5425,0.2400000000000002,0.33999999999999986 --3g5yACwYnA/2,-3g5yACwYnA,2,13,internally.,7.28249979019165,9.182499885559082,True,4.959014102134951e-12,1.9164384603500366,7.391144668115456,9.147154329969988,7.282500000000001,8.2625,9.0825,9.2225,0.9799999999999986,0.14000000000000057 --3g5yACwYnA/9,-3g5yACwYnA,9,0,We,0.0024999999441206455,0.0625,True,1.3202740289930404e-10,4.0,0.0037092361625596475,0.06376428622874805,0.0025000000000000005,0.0025000000000000005,0.0625,0.0625,0.0,0.0 --3g5yACwYnA/9,-3g5yACwYnA,9,1,have,0.12250000238418579,0.8824999928474426,True,4.727816987730449e-13,0.4530237317085266,0.24601737150185057,0.9129629357636357,0.1225,0.8025,0.8825,1.0425,0.6799999999999999,0.16000000000000003 --3g5yACwYnA/9,-3g5yACwYnA,9,2,many,0.9225000143051147,1.1024999618530273,True,3.4017011213069437e-13,0.3259541094303131,0.9672695832607601,1.1443447348089129,0.9225,1.1225,1.1025,1.3225,0.20000000000000007,0.21999999999999997 --3g5yACwYnA/9,-3g5yACwYnA,9,3,new,1.1825000047683716,1.3224999904632568,True,3.941063621282215e-12,3.7763631343841553,1.262579923107276,1.4144081895232492,1.1824999999999999,1.6025,1.3225,1.8025,0.42000000000000015,0.48 --3g5yACwYnA/9,-3g5yACwYnA,9,4,opportunities,1.6024999618530273,2.4024999141693115,True,1.088685782149601e-12,1.0431885719299316,1.6586099648067913,2.444467497988983,1.6025,1.8825,2.4025,2.7025,0.28,0.30000000000000027 --3g5yACwYnA/9,-3g5yACwYnA,9,5,through,2.4825000762939453,2.7825000286102295,True,4.15607964167862e-14,0.25,2.5234634994329452,2.8696162143253496,2.4825,2.8025,2.7825,3.4425,0.3200000000000003,0.6599999999999997 --3g5yACwYnA/9,-3g5yACwYnA,9,6,the,2.802500009536743,3.442500114440918,True,1.9428814026362096e-12,1.8616865873336792,2.902911114428035,3.464744278514586,2.8025,3.4825,3.4425,3.6025,0.6799999999999997,0.16000000000000014 --3g5yACwYnA/9,-3g5yACwYnA,9,7,way,3.4825000762939453,3.6024999618530273,True,3.119503787230027e-12,2.9891369342803955,3.5099164031810415,3.63228134889645,3.4825,3.6825,3.6025,3.8225000000000002,0.20000000000000018,0.2200000000000002 --3g5yACwYnA/9,-3g5yACwYnA,9,8,things,3.682499885559082,4.002500057220459,True,6.429745516393914e-13,0.6161040663719177,3.7145892049209013,4.026147698972161,3.6825,3.9225,3.9825,4.2625,0.23999999999999977,0.28000000000000025 --3g5yACwYnA/9,-3g5yACwYnA,9,9,have,4.022500038146973,4.162499904632568,True,1.5793911859775245e-13,0.25,4.060617069421903,4.224488988758646,4.022500000000001,4.3025,4.1625000000000005,4.522500000000001,0.27999999999999936,0.3600000000000003 --3g5yACwYnA/9,-3g5yACwYnA,9,10,changed,4.202499866485596,4.522500038146973,True,2.325777157669018e-12,2.228580951690674,4.267085991580041,4.5723446469859,4.202500000000001,4.5825000000000005,4.522500000000001,4.862500000000001,0.3799999999999999,0.33999999999999986 --3g5yACwYnA/9,-3g5yACwYnA,9,11,through,4.582499980926514,5.582499980926514,True,1.854727959757496e-12,1.7772172689437866,4.6221517393402145,5.554001297056343,4.5825000000000005,4.8825,5.4625,5.6225000000000005,0.2999999999999998,0.16000000000000014 --3g5yACwYnA/9,-3g5yACwYnA,9,12,the,5.622499942779541,5.742499828338623,True,3.626375675441773e-12,3.4748260974884033,5.595031140793692,5.718768123192464,5.522500000000001,5.6625000000000005,5.6225000000000005,5.8025,0.13999999999999968,0.17999999999999972 --3g5yACwYnA/9,-3g5yACwYnA,9,13,"years,",5.78249979019165,5.982500076293945,True,3.45286983954949e-14,0.25,5.757698982112918,5.970677998071189,5.6425,5.8425,5.902500000000001,6.0425,0.20000000000000018,0.13999999999999968 --3g5yACwYnA/9,-3g5yACwYnA,9,14,looking,6.042500019073486,6.442500114440918,True,1.2439189218602098e-12,1.1919344663619995,6.0297255832126435,6.383957853422528,5.9225,6.0825000000000005,6.282500000000001,6.442500000000001,0.16000000000000014,0.16000000000000014 --3g5yACwYnA/9,-3g5yACwYnA,9,15,for,6.462500095367432,6.5625,True,1.4023155466696968e-12,1.343711495399475,6.419190410852593,6.540302343999718,6.3425,6.4625,6.482500000000001,6.562500000000001,0.1200000000000001,0.08000000000000007 --3g5yACwYnA/9,-3g5yACwYnA,9,16,new,6.642499923706055,6.84250020980835,True,1.043613546275468e-12,1.0,6.635691555353821,6.833978589755013,6.642500000000001,6.642500000000001,6.8425,6.8425,0.0,0.0 --3g5yACwYnA/9,-3g5yACwYnA,9,17,niche,6.862500190734863,7.0625,True,5.4846457372493065e-14,0.25,6.854528859600319,7.055299959028502,6.862500000000001,6.862500000000001,7.062500000000001,7.062500000000001,0.0,0.0 --3g5yACwYnA/9,-3g5yACwYnA,9,18,"high-end,",7.082499980926514,7.462500095367432,True,7.439023897749808e-13,0.7128140330314636,7.0769385969042,7.45691194296881,7.0825000000000005,7.0825000000000005,7.4625,7.4625,0.0,0.0 --3g5yACwYnA/9,-3g5yACwYnA,9,19,value-added,7.5625,8.082500457763672,True,5.798322705221487e-14,0.25,7.552404120714275,8.074980337515674,7.522500000000001,7.562500000000001,8.0425,8.0825,0.040000000000000036,0.03999999999999915 --3g5yACwYnA/9,-3g5yACwYnA,9,20,products.,8.102499961853027,8.662500381469727,True,2.1248971752616495e-14,0.25,8.098459094614249,8.634617109598796,8.1025,8.1025,8.5425,8.6825,0.0,0.1399999999999988 --3nNcZdcdvU/5,-3nNcZdcdvU,5,0,Noncompliance,0.5425000190734863,1.5425000190734863,True,3.009791851513177e-13,4.0,0.5421899065110246,1.5434444401076381,0.5225,0.5425,1.5425,1.5425,0.020000000000000018,0.0 --3nNcZdcdvU/5,-3nNcZdcdvU,5,1,can,1.6825000047683716,1.8624999523162842,True,4.914635593020883e-14,0.9133073091506958,1.682499728861315,1.8625016311882543,1.6824999999999999,1.6824999999999999,1.8625,1.8625,0.0,0.0 --3nNcZdcdvU/5,-3nNcZdcdvU,5,2,result,1.9824999570846558,2.502500057220459,True,5.090972131707727e-13,4.0,1.9826826486872584,2.502627463381576,1.9825,1.9825,2.5025,2.5025,0.0,0.0 --3nNcZdcdvU/5,-3nNcZdcdvU,5,3,in,2.6024999618530273,2.702500104904175,True,1.6868163089196406e-14,0.3134681284427643,2.602500402040593,2.7114411198718202,2.6025,2.6025,2.7025,2.7225,0.0,0.020000000000000018 --3nNcZdcdvU/5,-3nNcZdcdvU,5,4,legal,2.8424999713897705,3.122499942779541,True,1.6298654049659578e-13,3.0288469791412354,2.8319148446350573,3.108045806654291,2.8025,2.8425,3.0625,3.1225,0.03999999999999959,0.06000000000000005 --3nNcZdcdvU/5,-3nNcZdcdvU,5,5,liability,3.1424999237060547,3.802500009536743,True,4.397796688447586e-13,4.0,3.1425001068073284,3.8025137671985,3.1425,3.1425,3.8025,3.8025,0.0,0.0 --3nNcZdcdvU/5,-3nNcZdcdvU,5,6,to,3.9825000762939453,4.142499923706055,True,2.3713054631870067e-13,4.0,3.982500462639652,4.142499970675897,3.9825,3.9825,4.1425,4.1425,0.0,0.0 --3nNcZdcdvU/5,-3nNcZdcdvU,5,7,you,4.262499809265137,4.522500038146973,True,9.180395498160389e-15,0.25,4.256718628077809,4.512681988741261,4.202500000000001,4.2625,4.4225,4.522500000000001,0.05999999999999961,0.10000000000000053 --3nNcZdcdvU/5,-3nNcZdcdvU,5,8,and,4.5625,5.142499923706055,True,9.738124342279983e-14,1.8096764087677002,4.610781303553796,5.143268143927736,4.562500000000001,5.0425,5.1425,5.1425,0.47999999999999954,0.0 --3nNcZdcdvU/5,-3nNcZdcdvU,5,9,to,5.242499828338623,5.322500228881836,True,1.2475421086802219e-13,2.318359613418579,5.242284573869038,5.322497097245752,5.242500000000001,5.242500000000001,5.322500000000001,5.322500000000001,0.0,0.0 --3nNcZdcdvU/5,-3nNcZdcdvU,5,10,the,5.422500133514404,5.522500038146973,True,5.847647127806e-14,1.0866926908493042,5.420521893684469,5.521005673422197,5.402500000000001,5.4225,5.522500000000001,5.522500000000001,0.019999999999999574,0.0 --3nNcZdcdvU/5,-3nNcZdcdvU,5,11,school,5.542500019073486,5.802499771118164,True,5.076406095748951e-15,0.25,5.541309582381759,5.801309274139924,5.5425,5.5425,5.8025,5.8025,0.0,0.0 --3nNcZdcdvU/5,-3nNcZdcdvU,5,12,district,5.822500228881836,6.182499885559082,True,2.3873014813431616e-16,0.25,5.822409113735198,6.18241082307903,5.822500000000001,5.822500000000001,6.1825,6.1825,0.0,0.0 --3nNcZdcdvU/5,-3nNcZdcdvU,5,13,in,6.202499866485596,6.262499809265137,True,3.187962021713249e-15,0.25,6.202413110773365,6.2624131946284285,6.202500000000001,6.202500000000001,6.2625,6.2625,0.0,0.0 --3nNcZdcdvU/5,-3nNcZdcdvU,5,14,which,6.28249979019165,6.462500095367432,True,3.9412292157998865e-16,0.25,6.282413518600741,6.46250329822077,6.282500000000001,6.282500000000001,6.4625,6.4625,0.0,0.0 --3nNcZdcdvU/5,-3nNcZdcdvU,5,15,you,6.482500076293945,6.622499942779541,True,4.329610265143072e-14,0.804589569568634,6.482504276688287,6.617728718552279,6.482500000000001,6.482500000000001,6.5825000000000005,6.6225000000000005,0.0,0.040000000000000036 --3nNcZdcdvU/5,-3nNcZdcdvU,5,16,are,6.642499923706055,6.742499828338623,True,4.5697071750531656e-14,0.8492078185081482,6.642361698991119,6.743794056590974,6.642500000000001,6.642500000000001,6.742500000000001,6.742500000000001,0.0,0.0 --3nNcZdcdvU/5,-3nNcZdcdvU,5,17,employed.,6.84250020980835,7.28249979019165,True,6.300834149135931e-14,1.170910358428955,6.83813239815432,7.282623043355807,6.822500000000001,6.8425,7.282500000000001,7.282500000000001,0.019999999999999574,0.0 --HwX2H8Z4hY/2,-HwX2H8Z4hY,2,0,”,nan,nan,False,0.0,nan,nan,nan,nan,nan,nan,nan,nan,nan --HwX2H8Z4hY/2,-HwX2H8Z4hY,2,1,[President,0.10249999910593033,0.762499988079071,True,8.245064109539332e-14,4.0,0.10250473972383489,0.7625327724371536,0.10250000000000001,0.10250000000000001,0.7625,0.7625,0.0,0.0 --HwX2H8Z4hY/2,-HwX2H8Z4hY,2,2,Ronald,0.8224999904632568,1.8025000095367432,True,5.068065997592048e-16,0.25,0.854274069167481,1.7270714047834743,0.8225,1.0225,1.3625,2.0425,0.19999999999999996,0.6799999999999999 --HwX2H8Z4hY/2,-HwX2H8Z4hY,2,3,Reagan:],1.8624999523162842,2.802500009536743,True,1.1842246509850916e-14,1.0,1.9694596577449979,2.8033453188270716,1.6625,2.2825,2.8025,2.8225,0.6200000000000001,0.019999999999999574 --HwX2H8Z4hY/2,-HwX2H8Z4hY,2,4,"""Look",2.882499933242798,3.0225000381469727,True,2.492327701099535e-14,2.104607105255127,2.881426774537937,3.0216973335913506,2.8825,2.8825,3.0225,3.0225,0.0,0.0 --HwX2H8Z4hY/2,-HwX2H8Z4hY,2,5,at,3.1024999618530273,3.1624999046325684,True,2.696593126813346e-15,0.25,3.1034472692660957,3.16550226599371,3.1025,3.1425,3.1625,3.2225,0.040000000000000036,0.06000000000000005 --HwX2H8Z4hY/2,-HwX2H8Z4hY,2,6,the,3.242500066757202,3.3424999713897705,True,2.8035099876354622e-14,2.367380142211914,3.2418077886934986,3.342347080125065,3.2425,3.2425,3.3425,3.3425,0.0,0.0 --HwX2H8Z4hY/2,-HwX2H8Z4hY,2,7,record,3.422499895095825,3.9024999141693115,True,5.635536779396251e-16,0.25,3.421806202848189,3.881243156703797,3.4225,3.4225,3.8025,3.9025,0.0,0.09999999999999964 --HwX2H8Z4hY/5,-HwX2H8Z4hY,5,0,"""",nan,nan,False,0.0,nan,nan,nan,nan,nan,nan,nan,nan,nan --HwX2H8Z4hY/5,-HwX2H8Z4hY,5,1,President,0.8025000095367432,1.2424999475479126,True,1.1130892147120756e-14,0.25,0.7991785910278454,1.249418363734453,0.8025,0.8025,1.2425,1.2625,0.0,0.020000000000000018 --HwX2H8Z4hY/5,-HwX2H8Z4hY,5,2,Ronald,1.3224999904632568,1.662500023841858,True,6.521055939158471e-13,3.265170097351074,1.3182879263108291,1.657037437672821,1.2625,1.3225,1.6025,1.6625,0.06000000000000005,0.06000000000000005 --HwX2H8Z4hY/5,-HwX2H8Z4hY,5,3,Reagan,1.7024999856948853,2.122499942779541,True,1.9971566447059969e-13,1.0,1.7002046832597368,2.1152442116829513,1.7025,1.7025,2.0625,2.1225,0.0,0.06000000000000005 --HwX2H8Z4hY/5,-HwX2H8Z4hY,5,4,blamed,2.202500104904175,2.5625,True,1.681951561534334e-13,0.8421730995178223,2.1942407816196767,2.5565269463501545,2.1225,2.2025,2.5025,2.5625,0.08000000000000007,0.06000000000000005 --HwX2H8Z4hY/5,-HwX2H8Z4hY,5,5,the,2.6624999046325684,2.762500047683716,True,1.4306970931858738e-14,0.25,2.643355740531605,2.752176231037962,2.6025,2.6625,2.7225,2.7625,0.06000000000000005,0.040000000000000036 --HwX2H8Z4hY/5,-HwX2H8Z4hY,5,6,professional,2.7825000286102295,3.422499895095825,True,1.6846922891011057e-14,0.25,2.7774452139102097,3.4217504683401407,2.7425,2.7825,3.4225,3.4225,0.040000000000000036,0.0 --HwX2H8Z4hY/5,-HwX2H8Z4hY,5,7,bureaucracy,3.4625000953674316,4.202499866485596,True,5.344916132951627e-13,2.676262855529785,3.4615893755070632,4.158197134262134,3.4625,3.4625,4.1425,4.202500000000001,0.0,0.0600000000000005 --HwX2H8Z4hY/5,-HwX2H8Z4hY,5,8,of,4.302499771118164,4.382500171661377,True,8.464278540218362e-13,4.0,4.265456447231751,4.360272046146851,4.202500000000001,4.3025,4.322500000000001,4.3825,0.09999999999999964,0.05999999999999961 --HwX2H8Z4hY/5,-HwX2H8Z4hY,5,9,education,4.462500095367432,5.082499980926514,True,6.528327141028245e-13,3.268810749053955,4.462466272651668,5.082501771556385,4.4625,4.4625,5.0825000000000005,5.0825000000000005,0.0,0.0 --HwX2H8Z4hY/6,-HwX2H8Z4hY,6,0,And,0.0024999999441206455,0.6424999833106995,True,9.006679205073899e-16,0.25,0.049993577900290236,0.6401664878744063,0.0025000000000000005,0.2425,0.6224999999999999,0.6425,0.24,0.020000000000000018 --HwX2H8Z4hY/6,-HwX2H8Z4hY,6,1,in,0.6825000047683716,0.762499988079071,True,1.0384882278386635e-14,0.25,0.6755059356561959,0.7452473237909909,0.6625,0.6825,0.7224999999999999,0.7625,0.020000000000000018,0.040000000000000036 --HwX2H8Z4hY/6,-HwX2H8Z4hY,6,2,"part,",0.8424999713897705,1.1825000047683716,True,4.603873096013615e-14,0.3257012665271759,0.8366663344434105,1.175919532391122,0.7625,0.8424999999999999,1.1025,1.1824999999999999,0.07999999999999996,0.07999999999999985 --HwX2H8Z4hY/6,-HwX2H8Z4hY,6,3,Al,1.5425000190734863,1.622499942779541,True,1.3575890628683696e-12,4.0,1.542340600155332,1.622350825487453,1.5425,1.5425,1.6225,1.6225,0.0,0.0 --HwX2H8Z4hY/6,-HwX2H8Z4hY,6,4,Shanker,1.722499966621399,2.1624999046325684,True,1.41352627844836e-13,1.0,1.7221858829602623,2.1581962257056984,1.7225,1.7225,2.1025,2.1625,0.0,0.06000000000000005 --HwX2H8Z4hY/6,-HwX2H8Z4hY,6,5,did,2.262500047683716,2.4024999141693115,True,8.53964848054195e-13,4.0,2.2624871936417077,2.405549344077747,2.2625,2.2625,2.4025,2.4025,0.0,0.0 --HwX2H8Z4hY/6,-HwX2H8Z4hY,6,6,too,2.682499885559082,2.822499990463257,True,9.367995962294984e-12,4.0,2.678787842175452,2.8245599587910464,2.6825,2.6825,2.8025,2.8425,0.0,0.03999999999999959 --HwX2H8Z4hY/9,-HwX2H8Z4hY,9,0,It,0.5625,0.6424999833106995,True,9.704259118015809e-15,0.25,0.3968797872067635,0.6168155228213217,0.0625,0.5824999999999999,0.5824999999999999,0.6425,0.5199999999999999,0.06000000000000005 --HwX2H8Z4hY/9,-HwX2H8Z4hY,9,1,is,0.6825000047683716,0.7425000071525574,True,1.4060067942810867e-13,0.25,0.6826864336953968,0.7429342737517168,0.6825,0.6825,0.7424999999999999,0.7424999999999999,0.0,0.0 --HwX2H8Z4hY/9,-HwX2H8Z4hY,9,2,a,0.8424999713897705,0.862500011920929,True,3.836665414622825e-13,0.2704606354236603,0.8431059245975748,0.863105924597575,0.8424999999999999,0.8424999999999999,0.8624999999999999,0.8624999999999999,0.0,0.0 --HwX2H8Z4hY/9,-HwX2H8Z4hY,9,3,word,0.9225000143051147,1.162500023841858,True,2.349814407723999e-13,0.25,0.9232465709824628,1.1633531719563064,0.9225,0.9225,1.1624999999999999,1.1624999999999999,0.0,0.0 --HwX2H8Z4hY/9,-HwX2H8Z4hY,9,4,which,1.2625000476837158,1.5625,True,5.4473098801870526e-14,0.25,1.2682948092150728,1.5630203083225693,1.2625,1.3225,1.5625,1.5625,0.06000000000000005,0.0 --HwX2H8Z4hY/9,-HwX2H8Z4hY,9,5,the,1.722499966621399,1.8224999904632568,True,8.272986245713709e-13,0.5831931829452515,1.6909958021630012,1.7986297285033759,1.6225,1.7225,1.7225,1.8225,0.09999999999999987,0.10000000000000009 --HwX2H8Z4hY/9,-HwX2H8Z4hY,9,6,administrator,1.8825000524520874,2.622499942779541,True,7.934183908833714e-13,0.559309720993042,1.8591177881897383,2.7274044722357593,1.8025,1.8825,2.6225,3.1625,0.08000000000000007,0.54 --HwX2H8Z4hY/9,-HwX2H8Z4hY,9,7,uses,2.9024999141693115,3.1624999046325684,True,2.1700481309897685e-13,0.25,2.968049678105385,3.2345771687388063,2.8825,3.2425,3.1625,3.5025,0.3600000000000003,0.33999999999999986 --HwX2H8Z4hY/9,-HwX2H8Z4hY,9,8,when,3.242500066757202,3.442500114440918,True,4.379272010128499e-13,0.3087109625339508,3.333607512728239,3.547610849410154,3.2425,3.6825,3.4425,3.9025,0.43999999999999995,0.45999999999999996 --HwX2H8Z4hY/9,-HwX2H8Z4hY,9,9,he,3.502500057220459,3.5625,True,1.9151127623844022e-13,0.25,3.6091286554749216,3.6789170759396757,3.5025,3.9625,3.5625,4.022500000000001,0.45999999999999996,0.46000000000000085 --HwX2H8Z4hY/9,-HwX2H8Z4hY,9,10,turns,3.6424999237060547,3.9024999141693115,True,2.0098356572767484e-12,1.416806936264038,3.750671620423674,3.986732770438924,3.6425,4.062500000000001,3.9025,4.2625,0.4200000000000008,0.3600000000000003 --HwX2H8Z4hY/9,-HwX2H8Z4hY,9,11,around,3.9625000953674316,4.262499809265137,True,3.172354393066179e-11,4.0,4.042443095688754,4.331695960114718,3.9625,4.3025,4.2625,4.5425,0.3400000000000003,0.28000000000000025 --HwX2H8Z4hY/9,-HwX2H8Z4hY,9,12,anything,4.302499771118164,5.002500057220459,True,4.246567507359966e-12,2.993561267852783,4.397334396251662,5.0187542042154245,4.3025,4.562500000000001,5.0025,5.1225000000000005,0.2600000000000007,0.1200000000000001 --HwX2H8Z4hY/9,-HwX2H8Z4hY,9,13,which,5.202499866485596,5.482500076293945,True,1.0097850507151396e-11,4.0,5.1998952268885485,5.481770232068269,5.1825,5.202500000000001,5.482500000000001,5.482500000000001,0.020000000000000462,0.0 --HwX2H8Z4hY/9,-HwX2H8Z4hY,9,14,he,5.542500019073486,5.602499961853027,True,3.1471665009295824e-13,0.25,5.541826700619963,5.601893321673665,5.5425,5.5425,5.602500000000001,5.602500000000001,0.0,0.0 --HwX2H8Z4hY/9,-HwX2H8Z4hY,9,15,doesn't,5.662499904632568,6.002500057220459,True,4.0290708269719033e-11,4.0,5.664100729682788,6.0016396736273805,5.6625000000000005,5.702500000000001,6.0025,6.0025,0.040000000000000036,0.0 --HwX2H8Z4hY/9,-HwX2H8Z4hY,9,16,like,6.042500019073486,6.182499885559082,True,2.3577168863087028e-12,1.662041187286377,6.0421210584664955,6.251301613627984,6.0425,6.0425,6.1825,6.322500000000001,0.0,0.14000000000000057 --HwX2H8Z4hY/9,-HwX2H8Z4hY,9,17,that,6.242499828338623,6.402500152587891,True,9.430432129642341e-12,4.0,6.31569748562974,6.490365143363123,6.242500000000001,6.402500000000001,6.402500000000001,6.602500000000001,0.16000000000000014,0.20000000000000018 --HwX2H8Z4hY/9,-HwX2H8Z4hY,9,18,the,6.462500095367432,6.602499961853027,True,3.4823832706365465e-10,4.0,6.546923966814362,6.670741888996065,6.4625,6.6625000000000005,6.602500000000001,6.7625,0.20000000000000018,0.15999999999999925 --HwX2H8Z4hY/9,-HwX2H8Z4hY,9,19,teacher,6.662499904632568,7.0625,True,3.151389912914304e-11,4.0,6.7149365146030195,7.083825396014788,6.6625000000000005,6.782500000000001,7.062500000000001,7.1225000000000005,0.1200000000000001,0.05999999999999961 --HwX2H8Z4hY/9,-HwX2H8Z4hY,9,20,is,7.162499904632568,7.262499809265137,True,2.1730292912303106e-11,4.0,7.167127941420237,7.250665423256899,7.1625000000000005,7.1825,7.2225,7.2625,0.019999999999999574,0.040000000000000036 --HwX2H8Z4hY/9,-HwX2H8Z4hY,9,21,doing,7.322500228881836,7.582499980926514,True,2.088004595612869e-11,4.0,7.323569851270532,7.58443002944152,7.322500000000001,7.322500000000001,7.5825000000000005,7.602500000000001,0.0,0.020000000000000462 --NFrJFQijFE/1,-NFrJFQijFE,1,0,Structural,0.0024999999441206455,0.7225000262260437,True,3.124166550461105e-11,0.801537275314331,0.029607444381030804,0.6871020932567873,0.0025000000000000005,0.10250000000000001,0.4825,0.9225,0.1,0.44 --NFrJFQijFE/1,-NFrJFQijFE,1,1,mounts,1.122499942779541,1.7825000286102295,True,3.382181687494601e-11,0.8677337765693665,0.7741501022267345,1.168869413851003,0.5425,1.0425,0.9025,1.4625,0.5,0.5599999999999999 --NFrJFQijFE/1,-NFrJFQijFE,1,2,inside,1.8424999713897705,2.242500066757202,True,3.242017765359151e-11,0.8317732214927673,1.259193099460418,1.646948133757638,0.9824999999999999,1.5625,1.3625,1.9425,0.5800000000000001,0.5799999999999998 --NFrJFQijFE/1,-NFrJFQijFE,1,3,have,2.382499933242798,2.7825000286102295,True,3.251355781830334e-11,0.8341690301895142,1.7308771690731846,1.958774697749872,1.4625,2.0225,1.6824999999999999,2.2625,0.56,0.5800000000000003 --NFrJFQijFE/1,-NFrJFQijFE,1,4,to,3.0625,3.122499942779541,True,3.055768832416206e-11,0.7839891314506531,2.040202773527604,2.1314457321513656,1.7625,2.3625,1.8425,2.4425,0.5999999999999999,0.5999999999999999 --NFrJFQijFE/1,-NFrJFQijFE,1,5,be,3.1624999046325684,3.2225000858306885,True,2.7543876901514608e-11,0.7066667079925537,2.2165689766668426,2.3095375530237123,1.9224999999999999,2.5225,2.0025,2.6225,0.6000000000000001,0.6200000000000001 --NFrJFQijFE/1,-NFrJFQijFE,1,6,properly,3.242500066757202,3.6624999046325684,True,3.094473635667505e-11,0.7939192652702332,2.398161975532348,2.939312401374726,2.0825,2.7025,2.5825,3.2225,0.6200000000000001,0.6400000000000001 --NFrJFQijFE/1,-NFrJFQijFE,1,7,stress,3.7825000286102295,4.042500019073486,True,4.0694180664102575e-11,1.0440514087677002,3.024703822620534,3.3952124304109335,2.6625,3.3025,3.0825,3.6825,0.6400000000000001,0.6000000000000001 --NFrJFQijFE/1,-NFrJFQijFE,1,8,analyzed,4.0625,4.482500076293945,True,5.706426650653462e-11,1.4640429019927979,3.4734230005814695,3.95665797695199,3.1625,3.7625,3.6625,4.202500000000001,0.6000000000000001,0.5400000000000005 --NFrJFQijFE/1,-NFrJFQijFE,1,9,so,4.502500057220459,4.5625,True,3.726018105165707e-11,0.955948531627655,4.019371413642997,4.09926351081791,3.7625,4.2625,3.8425,4.322500000000001,0.5,0.48000000000000087 --NFrJFQijFE/1,-NFrJFQijFE,1,10,we,4.582499980926514,4.682499885559082,True,4.315695370515904e-11,1.107236385345459,4.158343759812449,4.2382602103512115,3.9225,4.3825,4.0025,4.4625,0.4600000000000004,0.45999999999999996 --NFrJFQijFE/1,-NFrJFQijFE,1,11,make,4.702499866485596,4.862500190734863,True,5.602865393861123e-11,1.437473177909851,4.297877403832084,4.498025124451961,4.062500000000001,4.5025,4.2625,4.6825,0.4399999999999995,0.41999999999999993 --NFrJFQijFE/1,-NFrJFQijFE,1,12,sure,4.922500133514404,5.0625,True,5.5529952164290464e-11,1.4246784448623657,4.5595462645139255,4.759348019483343,4.322500000000001,4.742500000000001,4.5425,4.9225,0.41999999999999993,0.3799999999999999 --NFrJFQijFE/1,-NFrJFQijFE,1,13,all,5.082499980926514,5.182499885559082,True,4.774074538471673e-11,1.2248382568359375,4.817843713841208,4.9557359749111045,4.6425,4.9625,4.782500000000001,5.102500000000001,0.3200000000000003,0.3200000000000003 --NFrJFQijFE/1,-NFrJFQijFE,1,14,that,5.202499866485596,5.34250020980835,True,5.2850689102879045e-11,1.3559391498565674,5.012945479106424,5.209031399250358,4.8425,5.1425,5.062500000000001,5.322500000000001,0.2999999999999998,0.2599999999999998 --NFrJFQijFE/1,-NFrJFQijFE,1,15,happens,5.362500190734863,5.642499923706055,True,5.486522347553091e-11,1.4076241254806519,5.265253840657979,5.6252282574922905,5.1425,5.362500000000001,5.5825000000000005,5.6425,0.22000000000000064,0.05999999999999961 --NFrJFQijFE/2,-NFrJFQijFE,2,0,So,1.122499942779541,1.2424999475479126,True,2.0999696732503133e-14,0.3740757703781128,0.7017702038054376,0.8164313921794365,0.6625,0.8225,0.7224999999999999,0.9624999999999999,0.16000000000000003,0.24 --NFrJFQijFE/2,-NFrJFQijFE,2,1,we,1.2825000286102295,1.3825000524520874,True,1.8122491829137936e-14,0.3228229880332947,0.9301739611043676,1.0355676938406366,0.7825,1.1225,0.8825,1.2425,0.3400000000000001,0.36 --NFrJFQijFE/2,-NFrJFQijFE,2,2,coordinate,1.6425000429153442,2.0824999809265137,True,2.99360789792185e-14,0.5332630276679993,1.1385153786376387,1.8848721368518628,0.9624999999999999,1.3425,1.6824999999999999,2.0425,0.3800000000000001,0.3600000000000001 --NFrJFQijFE/2,-NFrJFQijFE,2,3,with,2.1024999618530273,2.242500066757202,True,6.905049177840378e-14,1.2300232648849487,1.955838283594859,2.1544054792982386,1.7625,2.1025,1.9825,2.2625,0.3400000000000001,0.28000000000000025 --NFrJFQijFE/2,-NFrJFQijFE,2,4,all,2.262500047683716,2.362499952316284,True,5.794130230945757e-14,1.0321309566497803,2.2032026778324427,2.3225781228227205,2.0625,2.3025,2.2025,2.4225,0.2400000000000002,0.21999999999999975 --NFrJFQijFE/2,-NFrJFQijFE,2,5,the,2.382499933242798,2.4825000762939453,True,5.4333795763365084e-14,0.9678690433502197,2.3595980088641553,2.4785183487033846,2.2425,2.4625,2.3625,2.5825,0.21999999999999975,0.2200000000000002 --NFrJFQijFE/2,-NFrJFQijFE,2,6,proper,2.5625,2.7825000286102295,True,4.613511653327011e-14,0.8218227624893188,2.5235697929220096,2.7911478799564198,2.3825,2.6425,2.6825,2.9025,0.26000000000000023,0.21999999999999975 --NFrJFQijFE/2,-NFrJFQijFE,2,7,technical,2.802500009536743,3.242500066757202,True,2.8803697572693174e-14,0.5130914449691772,2.826699438084622,3.324501218236374,2.7225,2.9425,3.2025,3.5625,0.21999999999999975,0.3599999999999999 --NFrJFQijFE/2,-NFrJFQijFE,2,8,fields,3.622499942779541,3.9625000953674316,True,3.771829203136345e-12,4.0,3.567640087175455,3.9341314603260984,3.3425,3.6225,3.8825,3.9625,0.28000000000000025,0.08000000000000007 --NFrJFQijFE/2,-NFrJFQijFE,2,9,to,4.102499961853027,4.162499904632568,True,2.0974448035598198e-13,3.736259937286377,4.002873380071735,4.076475277349137,3.9025,4.1025,3.9625,4.1625000000000005,0.20000000000000018,0.20000000000000062 --NFrJFQijFE/2,-NFrJFQijFE,2,10,get,4.182499885559082,4.322500228881836,True,2.997963680149811e-14,0.5340389609336853,4.131802025449857,4.282693539325499,4.1025,4.242500000000001,4.2625,4.3825,0.14000000000000057,0.1200000000000001 --NFrJFQijFE/2,-NFrJFQijFE,2,11,ready,4.34250020980835,4.642499923706055,True,1.2902478564724706e-12,4.0,4.348985787804194,4.638174202884239,4.3425,4.4225,4.6225000000000005,4.6425,0.08000000000000007,0.019999999999999574 --NFrJFQijFE/2,-NFrJFQijFE,2,12,for,4.702499866485596,4.802499771118164,True,3.9598769955347807e-14,0.7053883075714111,4.69689650444899,4.800728795198717,4.6625000000000005,4.702500000000001,4.782500000000001,4.822500000000001,0.040000000000000036,0.040000000000000036 --NFrJFQijFE/2,-NFrJFQijFE,2,13,the,4.822500228881836,4.962500095367432,True,2.13347828986743e-12,4.0,4.832524953971189,4.960742471002819,4.822500000000001,4.8425,4.9625,4.9625,0.019999999999999574,0.0 --NFrJFQijFE/2,-NFrJFQijFE,2,14,instrument,4.982500076293945,5.582499980926514,True,5.864949639226152e-14,1.0447462797164917,4.981819918289069,5.583200022323766,4.982500000000001,4.982500000000001,5.5825000000000005,5.5825000000000005,0.0,0.0 --NFrJFQijFE/2,-NFrJFQijFE,2,15,to,6.0625,6.142499923706055,True,2.7822413291430856e-14,0.4956114590167999,6.008112967011355,6.1294094160023525,5.7625,6.062500000000001,6.0825000000000005,6.142500000000001,0.3000000000000007,0.0600000000000005 --NFrJFQijFE/2,-NFrJFQijFE,2,16,arrive,6.202499866485596,6.502500057220459,True,1.3836344179771198e-12,4.0,6.202900777167125,6.502181568618448,6.202500000000001,6.202500000000001,6.5025,6.5025,0.0,0.0 --NFrJFQijFE/2,-NFrJFQijFE,2,17,here,6.542500019073486,6.682499885559082,True,7.368213569662607e-13,4.0,6.542190924116508,6.682470262173858,6.5425,6.5425,6.6825,6.6825,0.0,0.0 --THoVjtIkeU/12,-THoVjtIkeU,12,0,What,0.0024999999441206455,0.8025000095367432,True,5.184272455771577e-11,4.0,0.0025000003549047693,0.8035597524626871,0.0025000000000000005,0.0025000000000000005,0.8025,0.8025,0.0,0.0 --THoVjtIkeU/12,-THoVjtIkeU,12,1,ever,1.6425000429153442,1.9225000143051147,True,4.004269246911385e-13,4.0,1.6529561096015108,1.911600849839455,1.6425,1.7225,1.8825,1.9224999999999999,0.07999999999999985,0.039999999999999813 --THoVjtIkeU/12,-THoVjtIkeU,12,2,we,2.002500057220459,2.0625,True,3.836271849234213e-14,0.6021820306777954,2.0016582942541135,2.061671197113673,2.0025,2.0025,2.0625,2.0625,0.0,0.0 --THoVjtIkeU/12,-THoVjtIkeU,12,3,turn,2.1424999237060547,2.302500009536743,True,1.717639139068043e-15,0.25,2.1415002094996507,2.301430511112869,2.1425,2.1425,2.3025,2.3025,0.0,0.0 --THoVjtIkeU/12,-THoVjtIkeU,12,4,our,2.322499990463257,2.442500114440918,True,6.326280374124166e-14,0.9930402636528015,2.3216422600531423,2.441643863547024,2.3225,2.3225,2.4425,2.4425,0.0,0.0 --THoVjtIkeU/12,-THoVjtIkeU,12,5,attention,2.4825000762939453,2.882499933242798,True,1.9333507962838092e-15,0.25,2.4818262028628437,2.882207397831878,2.4825,2.4825,2.8825,2.8825,0.0,0.0 --THoVjtIkeU/12,-THoVjtIkeU,12,6,to,2.922499895095825,3.0625,True,6.509613540480602e-14,1.0218181610107422,2.9226896623999803,3.0626401735658586,2.9225,2.9225,3.0625,3.0625,0.0,0.0 --THoVjtIkeU/12,-THoVjtIkeU,12,7,is,3.182499885559082,3.2825000286102295,True,3.3738997381495273e-13,4.0,3.1823176206620607,3.2825267449727344,3.1825,3.1825,3.2825,3.2825,0.0,0.0 --THoVjtIkeU/12,-THoVjtIkeU,12,8,what,3.322499990463257,3.502500057220459,True,1.615317071995779e-14,0.25355735421180725,3.3225591942568835,3.5025797752496106,3.3225000000000002,3.3225000000000002,3.5025,3.5025,0.0,0.0 --THoVjtIkeU/12,-THoVjtIkeU,12,9,grows,3.5225000381469727,3.882499933242798,True,3.4992076239619835e-14,0.5492728352546692,3.522784014159437,3.8827429304851,3.5225,3.5225,3.8825,3.8825,0.0,0.0 --THoVjtIkeU/12,-THoVjtIkeU,12,10,and,4.362500190734863,4.482500076293945,True,9.108250991537309e-14,1.4297280311584473,4.362460354649206,4.482600317036873,4.362500000000001,4.362500000000001,4.482500000000001,4.482500000000001,0.0,0.0 --THoVjtIkeU/12,-THoVjtIkeU,12,11,so,4.542500019073486,4.642499923706055,True,1.8818568665174285e-12,4.0,4.542616593028849,4.642609848982019,4.5425,4.5425,4.6425,4.6425,0.0,0.0 --THoVjtIkeU/12,-THoVjtIkeU,12,12,if,4.682499885559082,4.78249979019165,True,6.370618144341603e-14,1.0,4.73088135814891,4.8068325905395515,4.6825,4.7625,4.7625,4.822500000000001,0.08000000000000007,0.0600000000000005 --THoVjtIkeU/12,-THoVjtIkeU,12,13,we,4.882500171661377,4.962500095367432,True,6.87291274782155e-14,1.078845500946045,4.882564385938244,4.962677005890677,4.8825,4.8825,4.9625,4.9625,0.0,0.0 --THoVjtIkeU/12,-THoVjtIkeU,12,14,believe,5.022500038146973,5.522500038146973,True,2.0615089225527877e-13,3.235963821411133,5.0245719541936245,5.522680156939918,5.022500000000001,5.022500000000001,5.522500000000001,5.522500000000001,0.0,0.0 --THoVjtIkeU/12,-THoVjtIkeU,12,15,that,5.582499980926514,5.762499809265137,True,2.316116514818555e-15,0.25,5.582652937970199,5.762661710917487,5.5825000000000005,5.5825000000000005,5.7625,5.7625,0.0,0.0 --THoVjtIkeU/12,-THoVjtIkeU,12,16,anything,5.78249979019165,6.122499942779541,True,1.0723705621683722e-14,0.25,5.7857325380603175,6.128300725814943,5.782500000000001,5.8025,6.1225000000000005,6.1225000000000005,0.019999999999999574,0.0 --THoVjtIkeU/12,-THoVjtIkeU,12,17,is,6.182499885559082,6.262499809265137,True,5.072557499909147e-13,4.0,6.186674312374733,6.2654187095178235,6.1825,6.1825,6.242500000000001,6.2625,0.0,0.019999999999999574 --THoVjtIkeU/12,-THoVjtIkeU,12,18,"possible,",6.302499771118164,6.742499828338623,True,4.263187974298463e-15,0.25,6.30960288496603,6.754539570207679,6.3025,6.3025,6.742500000000001,6.742500000000001,0.0,0.0 --THoVjtIkeU/12,-THoVjtIkeU,12,19,if,6.78249979019165,6.84250020980835,True,1.6299522766650282e-14,0.25585463643074036,6.813844945293333,6.877896626746542,6.782500000000001,6.782500000000001,6.8425,6.8425,0.0,0.0 --THoVjtIkeU/12,-THoVjtIkeU,12,20,we,6.902500152587891,7.042500019073486,True,8.570621968205516e-13,4.0,6.945868750376086,7.086394513895723,6.902500000000001,6.902500000000001,7.0425,7.0425,0.0,0.0 --THoVjtIkeU/12,-THoVjtIkeU,12,21,believe,7.5625,8.142499923706055,True,4.034537461061749e-13,4.0,7.495042199965977,8.16664224609275,7.142500000000001,7.562500000000001,8.0825,8.1425,0.41999999999999993,0.0600000000000005 --THoVjtIkeU/12,-THoVjtIkeU,12,22,that,8.542499542236328,8.802499771118164,True,9.425311009100823e-14,1.4794970750808716,8.552403409813959,8.814869143102763,8.5425,8.5825,8.8025,8.862499999999999,0.03999999999999915,0.05999999999999872 --THoVjtIkeU/12,-THoVjtIkeU,12,23,social,8.90250015258789,9.542499542236328,True,5.2791052779221914e-12,4.0,8.926572150764354,9.554650222126032,8.8425,9.0825,9.282499999999999,9.6825,0.2400000000000002,0.40000000000000036 --THoVjtIkeU/12,-THoVjtIkeU,12,24,justice,9.602499961853027,10.082500457763672,True,3.2318182418417107e-12,4.0,9.622228193294516,10.075158284652437,9.4625,9.782499999999999,9.8825,10.1225,0.3199999999999985,0.2400000000000002 --THoVjtIkeU/12,-THoVjtIkeU,12,25,can,10.182499885559082,10.322500228881836,True,9.062416344695484e-14,1.4225332736968994,10.163757654882376,10.305245554736647,10.022499999999999,10.1825,10.1225,10.3225,0.16000000000000014,0.1999999999999993 --THoVjtIkeU/12,-THoVjtIkeU,12,26,be,10.422499656677246,10.482500076293945,True,1.1201589785944654e-12,4.0,10.406784621799975,10.467071219758102,10.2625,10.4225,10.3225,10.4825,0.16000000000000014,0.16000000000000014 --THoVjtIkeU/12,-THoVjtIkeU,12,27,achieved,10.522500038146973,10.942500114440918,True,2.057594986591433e-14,0.3229820132255554,10.510673160622034,10.934793906175887,10.4225,10.522499999999999,10.942499999999999,10.942499999999999,0.09999999999999964,0.0 --THoVjtIkeU/12,-THoVjtIkeU,12,28,and,10.982500076293945,11.082500457763672,True,7.772953694541382e-15,0.25,10.975281306995331,11.075634516296919,10.9825,10.9825,11.0825,11.0825,0.0,0.0 --THoVjtIkeU/12,-THoVjtIkeU,12,29,if,11.102499961853027,11.162500381469727,True,1.2482614429403481e-14,0.25,11.096370572360204,11.156537360099648,11.1025,11.1025,11.1625,11.1625,0.0,0.0 --THoVjtIkeU/12,-THoVjtIkeU,12,30,we,11.182499885559082,11.242500305175781,True,1.2027428749131208e-13,1.8879531621932983,11.177150273118796,11.237494385446567,11.1825,11.1825,11.2425,11.2425,0.0,0.0 --THoVjtIkeU/12,-THoVjtIkeU,12,31,believe,11.322500228881836,11.822500228881836,True,1.71007942507094e-13,2.6843225955963135,11.317170351965828,11.81544774843011,11.3225,11.3225,11.8225,11.8225,0.0,0.0 --THoVjtIkeU/12,-THoVjtIkeU,12,32,in,11.842499732971191,11.962499618530273,True,1.5597131875974557e-13,2.448291778564453,11.874989445701733,11.986233154258349,11.8425,11.942499999999999,11.9625,12.0425,0.09999999999999964,0.08000000000000007 --THoVjtIkeU/12,-THoVjtIkeU,12,33,"youth,",12.102499961853027,12.40250015258789,True,3.8225936223887716e-14,0.6000349521636963,12.07514111375613,12.372758250652677,12.0625,12.1025,12.362499999999999,12.4025,0.03999999999999915,0.040000000000000924 --THoVjtIkeU/12,-THoVjtIkeU,12,34,they,12.882499694824219,13.042499542236328,True,3.4154286115885973e-14,0.5361220240592957,12.580522630946723,13.026778540456233,12.4025,12.9025,12.9825,13.0425,0.5,0.0600000000000005 --THoVjtIkeU/12,-THoVjtIkeU,12,35,will,13.0625,13.202500343322754,True,1.877775482306797e-15,0.25,13.049451388170713,13.195483131860904,13.022499999999999,13.0625,13.1825,13.2225,0.040000000000000924,0.040000000000000924 --THoVjtIkeU/12,-THoVjtIkeU,12,36,believe,13.242500305175781,13.542499542236328,True,3.5739823372928775e-14,0.5610103011131287,13.23451659139245,13.54107337938477,13.2225,13.2425,13.5425,13.5425,0.019999999999999574,0.0 --THoVjtIkeU/12,-THoVjtIkeU,12,37,in,13.602499961853027,13.662500381469727,True,4.70323768402307e-15,0.25,13.59477173018874,13.655624982027442,13.5825,13.6025,13.6425,13.6625,0.019999999999999574,0.019999999999999574 --THoVjtIkeU/12,-THoVjtIkeU,12,38,themselves.,13.682499885559082,14.682499885559082,True,1.3947767975850713e-14,0.25,13.682050784224838,14.477877429780559,13.6825,13.6825,14.1425,14.7225,0.0,0.5800000000000001 --THoVjtIkeU/2,-THoVjtIkeU,2,0,I,0.042500000447034836,0.0625,True,3.5587171095174605e-14,0.5238187909126282,0.042747574508858015,0.06274757450885804,0.0425,0.0425,0.0625,0.0625,0.0,0.0 --THoVjtIkeU/2,-THoVjtIkeU,2,1,think,0.16249999403953552,0.3824999928474426,True,2.8180750918579967e-13,4.0,0.16252283449036006,0.38258277339076985,0.1625,0.1625,0.3825,0.3825,0.0,0.0 --THoVjtIkeU/2,-THoVjtIkeU,2,2,social,0.6825000047683716,1.4424999952316284,True,2.6086730974157757e-13,3.8397881984710693,0.6959264616025735,1.4393716808823362,0.6825,0.8025,1.4025,1.4425,0.12,0.039999999999999813 --THoVjtIkeU/2,-THoVjtIkeU,2,3,justice,1.462499976158142,1.7625000476837158,True,5.4383574195609324e-14,0.8004889488220215,1.462500073806679,1.7625047152212947,1.4625,1.4625,1.7625,1.7625,0.0,0.0 --THoVjtIkeU/2,-THoVjtIkeU,2,4,is,1.8025000095367432,1.8825000524520874,True,4.2815872917413567e-13,4.0,1.8025460129344417,1.8825969079606335,1.8025,1.8025,1.8825,1.8825,0.0,0.0 --THoVjtIkeU/2,-THoVjtIkeU,2,5,extremely,1.9424999952316284,2.362499952316284,True,7.994530737279529e-15,0.25,1.9425053363639069,2.362500000000592,1.9425,1.9425,2.3625,2.3625,0.0,0.0 --THoVjtIkeU/2,-THoVjtIkeU,2,6,important,2.382499933242798,2.822499990463257,True,5.668493222011316e-14,0.8343633413314819,2.3825001908451227,2.8223862620997116,2.3825,2.3825,2.8225,2.8225,0.0,0.0 --THoVjtIkeU/2,-THoVjtIkeU,2,7,for,2.862499952316284,2.9825000762939453,True,4.5019671042305365e-13,4.0,2.8625263658238085,2.98251959707777,2.8625,2.8625,2.9825,2.9825,0.0,0.0 --THoVjtIkeU/2,-THoVjtIkeU,2,8,young,3.0625,3.242500066757202,True,8.062027404714435e-15,0.25,3.0776871893499806,3.257933224930891,3.0625,3.1025,3.2425,3.2825,0.040000000000000036,0.040000000000000036 --THoVjtIkeU/2,-THoVjtIkeU,2,9,people.,3.322499990463257,3.702500104904175,True,7.919095338249776e-14,1.1656365394592285,3.3220047688676053,3.702550181798884,3.3225000000000002,3.3225000000000002,3.7025,3.7025,0.0,0.0 --THoVjtIkeU/6,-THoVjtIkeU,6,0,You,0.0024999999441206455,0.10249999910593033,True,7.510342987706448e-15,0.4623764753341675,0.008626349453761577,0.16667783381217036,0.0025000000000000005,0.0625,0.10250000000000001,0.5425,0.06,0.43999999999999995 --THoVjtIkeU/6,-THoVjtIkeU,6,1,know,0.12250000238418579,0.5425000190734863,True,6.107723236777041e-16,0.25,0.1987221878267382,0.5696078762787643,0.1225,0.5824999999999999,0.5425,0.7224999999999999,0.4599999999999999,0.17999999999999994 --THoVjtIkeU/6,-THoVjtIkeU,6,2,that,0.5824999809265137,0.7425000071525574,True,1.469799013943153e-14,0.9048861265182495,0.6074026626126879,0.7695639834093579,0.5824999999999999,0.7424999999999999,0.7424999999999999,0.9225,0.16000000000000003,0.18000000000000005 --THoVjtIkeU/6,-THoVjtIkeU,6,3,I,0.7825000286102295,0.8025000095367432,True,1.0772212982734786e-11,4.0,0.8124906763620903,0.8324906763620635,0.7825,0.9824999999999999,0.8025,1.0025,0.19999999999999996,0.19999999999999996 --THoVjtIkeU/6,-THoVjtIkeU,6,4,think,0.9225000143051147,1.3224999904632568,True,5.037423183120761e-14,3.101304531097412,0.9372821593564936,1.3304404827120164,0.9025,1.0425,1.3225,1.3825,0.14,0.06000000000000005 --THoVjtIkeU/6,-THoVjtIkeU,6,5,listening,1.3825000524520874,1.8825000524520874,True,9.660665720352419e-15,0.5947617292404175,1.3928878982518418,1.8981742756703237,1.3825,1.4825,1.8825,1.9224999999999999,0.09999999999999987,0.039999999999999813 --THoVjtIkeU/6,-THoVjtIkeU,6,6,to,1.9424999952316284,2.002500057220459,True,1.2283348234496012e-14,0.756227970123291,1.942528648184741,2.0025308908655695,1.9425,1.9425,2.0025,2.0025,0.0,0.0 --THoVjtIkeU/6,-THoVjtIkeU,6,7,young,2.0625,2.262500047683716,True,1.2662656576298303e-15,0.25,2.0621304027330667,2.2621369025721645,2.0625,2.0625,2.2625,2.2625,0.0,0.0 --THoVjtIkeU/6,-THoVjtIkeU,6,8,"people,",2.302500009536743,2.5625,True,1.7007364483748177e-14,1.0470634698867798,2.3024999785176608,2.5634430580912624,2.3025,2.3025,2.5625,2.5625,0.0,0.0 --THoVjtIkeU/6,-THoVjtIkeU,6,9,taking,2.622499942779541,3.0225000381469727,True,2.2397052067786236e-14,1.3788810968399048,2.6227230997220414,3.0213912292627607,2.6225,2.6225,3.0225,3.0225,0.0,0.0 --THoVjtIkeU/6,-THoVjtIkeU,6,10,in,3.0425000190734863,3.1024999618530273,True,1.287970262804335e-14,0.7929427027702332,3.0563697916002726,3.123298588516466,3.0425,3.0825,3.1025,3.1625,0.040000000000000036,0.06000000000000005 --THoVjtIkeU/6,-THoVjtIkeU,6,11,what,3.2225000858306885,3.382499933242798,True,1.399858132353782e-16,0.25,3.2090641191027367,3.368759455696855,3.1625,3.2225,3.3225000000000002,3.3825,0.06000000000000005,0.05999999999999961 --THoVjtIkeU/6,-THoVjtIkeU,6,12,they,3.422499895095825,3.5625,True,1.5478470013954165e-14,0.952936589717865,3.422107918188843,3.5624991299962057,3.4225,3.4225,3.5625,3.5625,0.0,0.0 --THoVjtIkeU/6,-THoVjtIkeU,6,13,have,3.6024999618530273,3.742500066757202,True,9.16368692624285e-15,0.5641651153564453,3.6024997152443112,3.749687033398412,3.6025,3.6025,3.7425,3.7625,0.0,0.020000000000000018 --THoVjtIkeU/6,-THoVjtIkeU,6,14,to,3.7825000286102295,3.862499952316284,True,1.177859367793065e-14,0.7251526117324829,3.7825058915301977,3.8625039279875057,3.7825,3.7825,3.8625,3.8625,0.0,0.0 --THoVjtIkeU/6,-THoVjtIkeU,6,15,say,3.942500114440918,4.122499942779541,True,1.6323537844770836e-13,4.0,3.942500199874739,4.122500127971544,3.9425,3.9425,4.1225000000000005,4.1225000000000005,0.0,0.0 --THoVjtIkeU/6,-THoVjtIkeU,6,16,because,4.162499904632568,4.482500076293945,True,1.3337907980772584e-13,4.0,4.166683924893797,4.48249963454062,4.1625000000000005,4.1825,4.482500000000001,4.482500000000001,0.019999999999999574,0.0 --THoVjtIkeU/6,-THoVjtIkeU,6,17,what,4.542500019073486,4.942500114440918,True,7.24388929238982e-17,0.25,4.554594493809835,4.895420128655968,4.522500000000001,4.6425,4.702500000000001,4.942500000000001,0.11999999999999922,0.2400000000000002 --THoVjtIkeU/6,-THoVjtIkeU,6,18,we,5.002500057220459,5.0625,True,2.4732789465553226e-14,1.522681474685669,4.958055151596716,5.01805986357333,4.8825,5.0025,4.942500000000001,5.062500000000001,0.1200000000000001,0.1200000000000001 --THoVjtIkeU/6,-THoVjtIkeU,6,19,have,5.082499980926514,5.222499847412109,True,1.3268368778088669e-14,0.8168710470199585,5.043438433626083,5.2030129096654605,5.0025,5.0825000000000005,5.1825,5.2225,0.08000000000000007,0.040000000000000036 --THoVjtIkeU/6,-THoVjtIkeU,6,20,seen,5.242499828338623,5.422500133514404,True,3.088271961293812e-14,1.901303768157959,5.242158090563371,5.422237301298598,5.242500000000001,5.242500000000001,5.4225,5.4225,0.0,0.0 --THoVjtIkeU/6,-THoVjtIkeU,6,21,all,5.482500076293945,5.682499885559082,True,1.7910698016940577e-14,1.1026774644851685,5.482469297811507,5.681582380617955,5.482500000000001,5.482500000000001,5.6825,5.6825,0.0,0.0 --THoVjtIkeU/6,-THoVjtIkeU,6,22,around,5.702499866485596,5.962500095367432,True,4.47852407828124e-14,2.757216691970825,5.702103166805097,5.957460999624755,5.702500000000001,5.702500000000001,5.9225,5.9625,0.0,0.040000000000000036 --THoVjtIkeU/6,-THoVjtIkeU,6,23,the,5.982500076293945,6.082499980926514,True,1.5442178252054344e-15,0.25,5.980183708565806,6.080183708652749,5.942500000000001,5.982500000000001,6.0425,6.0825000000000005,0.040000000000000036,0.040000000000000036 --THoVjtIkeU/6,-THoVjtIkeU,6,24,world,6.102499961853027,6.322500228881836,True,1.8824873148341357e-15,0.25,6.102498364639328,6.324249512896174,6.102500000000001,6.102500000000001,6.322500000000001,6.322500000000001,0.0,0.0 --THoVjtIkeU/6,-THoVjtIkeU,6,25,is,6.402500152587891,6.522500038146973,True,3.4449125409924397e-13,4.0,6.402505356574926,6.5225017704465404,6.402500000000001,6.402500000000001,6.522500000000001,6.522500000000001,0.0,0.0 --THoVjtIkeU/6,-THoVjtIkeU,6,26,the,6.582499980926514,6.682499885559082,True,4.761372435105153e-14,2.9313530921936035,6.582500199985874,6.682500449272542,6.5825000000000005,6.5825000000000005,6.6825,6.6825,0.0,0.0 --THoVjtIkeU/6,-THoVjtIkeU,6,27,power,6.742499828338623,7.042500019073486,True,2.462818089656732e-14,1.516241192817688,6.74240651506444,7.042512615514087,6.742500000000001,6.742500000000001,7.0425,7.0425,0.0,0.0 --THoVjtIkeU/6,-THoVjtIkeU,6,28,of,7.082499980926514,7.142499923706055,True,2.6027791033556014e-12,4.0,7.083613699835981,7.143614692086718,7.0825000000000005,7.0825000000000005,7.142500000000001,7.142500000000001,0.0,0.0 --THoVjtIkeU/6,-THoVjtIkeU,6,29,youth.,7.242499828338623,7.522500038146973,True,5.518415246790441e-14,3.3974287509918213,7.2424925780003235,7.522504128690015,7.242500000000001,7.242500000000001,7.522500000000001,7.522500000000001,0.0,0.0 --UuX1xuaiiE/1,-UuX1xuaiiE,1,0,^And,0.4625000059604645,0.5625,True,7.444570879352151e-15,0.25,0.43347005061479676,0.5584540097468289,0.1825,0.4625,0.5225,0.5625,0.28,0.040000000000000036 --UuX1xuaiiE/1,-UuX1xuaiiE,1,1,all,0.5824999809265137,0.7825000286102295,True,4.728579723958792e-13,4.0,0.6187218539498627,0.7942601619890411,0.5824999999999999,0.6625,0.7825,0.8225,0.08000000000000007,0.040000000000000036 --UuX1xuaiiE/1,-UuX1xuaiiE,1,2,of,0.8424999713897705,0.9024999737739563,True,2.301460346083861e-13,2.2389814853668213,0.8424948712648224,0.9027736800678561,0.8424999999999999,0.8424999999999999,0.9025,0.9025,0.0,0.0 --UuX1xuaiiE/1,-UuX1xuaiiE,1,3,them,0.9424999952316284,1.122499942779541,True,1.480158904514431e-14,0.25,0.9432060795990252,1.113068420763404,0.9425,0.9425,1.1025,1.1225,0.0,0.020000000000000018 --UuX1xuaiiE/1,-UuX1xuaiiE,1,4,are,1.2024999856948853,1.3224999904632568,True,2.4575976561962143e-13,2.3908801078796387,1.1923363969861287,1.3174479199245037,1.1225,1.2025,1.2825,1.3225,0.07999999999999985,0.040000000000000036 --UuX1xuaiiE/1,-UuX1xuaiiE,1,5,really,1.3825000524520874,1.662500023841858,True,2.800404426037649e-15,0.25,1.3814252978084791,1.6624772229432363,1.3825,1.3825,1.6625,1.6625,0.0,0.0 --UuX1xuaiiE/1,-UuX1xuaiiE,1,6,being,1.6825000047683716,1.9225000143051147,True,1.952734679413603e-14,0.25,1.6824843176111908,1.9214195095315,1.6824999999999999,1.6824999999999999,1.9025,1.9224999999999999,0.0,0.019999999999999796 --UuX1xuaiiE/1,-UuX1xuaiiE,1,7,able,2.5625,2.762500047683716,True,9.968488843626125e-14,0.9697869420051575,2.3964615747960076,2.7372177674963947,2.0225,2.5625,2.7225,2.7625,0.54,0.040000000000000036 --UuX1xuaiiE/1,-UuX1xuaiiE,1,8,to,2.7825000286102295,2.8424999713897705,True,1.889153675887264e-14,0.25,2.782500876058673,2.842501166223785,2.7825,2.7825,2.8425,2.8425,0.0,0.0 --UuX1xuaiiE/1,-UuX1xuaiiE,1,9,explore,2.882499933242798,3.5225000381469727,True,4.779727503546882e-13,4.0,2.9052813661038304,3.531178920856283,2.8825,2.9825,3.5225,3.5825,0.10000000000000009,0.06000000000000005 --UuX1xuaiiE/1,-UuX1xuaiiE,1,10,^these,3.622499942779541,4.242499828338623,True,6.823929984446642e-13,4.0,3.627667145170375,4.240710937512301,3.6225,3.6225,4.242500000000001,4.242500000000001,0.0,0.0 --UuX1xuaiiE/1,-UuX1xuaiiE,1,11,different,4.262499809265137,4.802499771118164,True,2.766109756069217e-14,0.26910167932510376,4.382878667595825,4.964671088009417,4.2625,4.522500000000001,4.8025,5.1825,0.2600000000000007,0.3799999999999999 --UuX1xuaiiE/1,-UuX1xuaiiE,1,12,areas,4.902500152587891,5.182499885559082,True,3.5131094675055e-14,0.34177374839782715,5.074588703285389,5.393802822040885,4.902500000000001,5.322500000000001,5.1825,5.6425,0.41999999999999993,0.45999999999999996 --UuX1xuaiiE/1,-UuX1xuaiiE,1,13,in,5.542500019073486,5.862500190734863,True,1.8041015729941545e-12,4.0,5.605517378896713,5.7680139174769876,5.242500000000001,5.8025,5.562500000000001,5.862500000000001,0.5599999999999996,0.2999999999999998 --UuX1xuaiiE/1,-UuX1xuaiiE,1,14,depth,5.962500095367432,6.34250020980835,True,3.677016915774878e-13,3.577195167541504,5.942366997981639,6.342105138567985,5.8425,6.062500000000001,6.3425,6.3425,0.22000000000000064,0.0 --UuX1xuaiiE/1,-UuX1xuaiiE,1,15,^in,6.382500171661377,6.582499980926514,True,7.172436472871468e-13,4.0,6.382663094054936,6.584390946636888,6.3825,6.3825,6.5825000000000005,6.602500000000001,0.0,0.020000000000000462 --UuX1xuaiiE/1,-UuX1xuaiiE,1,16,a,6.682499885559082,6.702499866485596,True,1.4643733274588566e-12,4.0,6.68250055881938,6.702500558819382,6.6825,6.6825,6.702500000000001,6.702500000000001,0.0,0.0 --UuX1xuaiiE/1,-UuX1xuaiiE,1,17,way,6.762499809265137,6.922500133514404,True,1.0279050424418304e-13,1.0,6.762495012667477,6.939677273518233,6.7625,6.7625,6.9225,6.9625,0.0,0.040000000000000036 --UuX1xuaiiE/1,-UuX1xuaiiE,1,18,that,7.022500038146973,7.202499866485596,True,1.8719922801561234e-14,0.25,7.021126903366722,7.195559932352289,7.022500000000001,7.022500000000001,7.1825,7.202500000000001,0.0,0.020000000000000462 --UuX1xuaiiE/1,-UuX1xuaiiE,1,19,really,7.222499847412109,7.522500038146973,True,4.071806385580511e-15,0.25,7.2194584454033,7.522500219334755,7.202500000000001,7.2225,7.522500000000001,7.522500000000001,0.019999999999999574,0.0 --UuX1xuaiiE/1,-UuX1xuaiiE,1,20,wasn't,7.5625,7.802499771118164,True,2.0166210281530317e-12,4.0,7.562499676953594,7.801666052689677,7.562500000000001,7.562500000000001,7.8025,7.8025,0.0,0.0 --UuX1xuaiiE/1,-UuX1xuaiiE,1,21,available,7.84250020980835,8.322500228881836,True,4.036739475674067e-14,0.3927152156829834,7.842499475900292,8.322500361921357,7.8425,7.8425,8.3225,8.3225,0.0,0.0 --UuX1xuaiiE/1,-UuX1xuaiiE,1,22,^before,8.362500190734863,8.702500343322754,True,3.3737571655638454e-13,3.28216814994812,8.362539013059672,8.702503611878011,8.362499999999999,8.362499999999999,8.7025,8.7025,0.0,0.0 --UuX1xuaiiE/1,-UuX1xuaiiE,1,23,the,8.742500305175781,8.842499732971191,True,2.0222062888683272e-14,0.25,8.74366559409698,8.844477233896045,8.7425,8.7425,8.8425,8.8425,0.0,0.0 --UuX1xuaiiE/1,-UuX1xuaiiE,1,24,center,8.862500190734863,9.302499771118164,True,2.695884422816708e-13,2.6226978302001953,8.86645495473147,9.305803311848454,8.862499999999999,8.862499999999999,9.3025,9.3025,0.0,0.0 --UuX1xuaiiE/1,-UuX1xuaiiE,1,25,was,9.442500114440918,9.602499961853027,True,3.3444106587853656e-14,0.32536181807518005,9.447406086810131,9.607217398306826,9.442499999999999,9.442499999999999,9.6025,9.6025,0.0,0.0 --UuX1xuaiiE/1,-UuX1xuaiiE,1,26,here,9.922499656677246,10.102499961853027,True,9.340148446335128e-12,4.0,9.927156903525098,10.156147021362736,9.9225,9.942499999999999,10.1025,10.2425,0.019999999999999574,0.14000000000000057 --UuX1xuaiiE/0,-UuX1xuaiiE,0,0,^it's,0.0625,0.18250000476837158,True,5.385001797773847e-13,4.0,0.03084138853451605,0.18886906847383023,0.0025000000000000005,0.0825,0.14250000000000002,0.2425,0.08,0.09999999999999998 --UuX1xuaiiE/0,-UuX1xuaiiE,0,1,amazing,0.30250000953674316,0.8025000095367432,True,2.427161661759658e-13,4.0,0.2978772205761982,0.7982895129975586,0.2425,0.3025,0.7224999999999999,0.8025,0.06,0.08000000000000007 --UuX1xuaiiE/0,-UuX1xuaiiE,0,2,to,0.8824999928474426,0.9624999761581421,True,5.4123535080802254e-14,1.0,0.8823922464530151,0.962499782349916,0.8825,0.8825,0.9624999999999999,0.9624999999999999,0.0,0.0 --UuX1xuaiiE/0,-UuX1xuaiiE,0,3,see,1.0625,1.2424999475479126,True,3.0656412738222505e-13,4.0,1.0624987865229019,1.2425008786156162,1.0625,1.0625,1.2425,1.2425,0.0,0.0 --UuX1xuaiiE/0,-UuX1xuaiiE,0,4,their,1.3224999904632568,1.5225000381469727,True,7.977060365105054e-16,0.25,1.3222094811963274,1.5226780527244042,1.3225,1.3225,1.5225,1.5225,0.0,0.0 --UuX1xuaiiE/0,-UuX1xuaiiE,0,5,enthusiasm,1.5625,2.322499990463257,True,1.264410261605023e-13,2.336156129837036,1.55597757995693,2.3073898823403156,1.5425,1.5625,2.2225,2.3225,0.020000000000000018,0.09999999999999964 --UuX1xuaiiE/0,-UuX1xuaiiE,0,6,and,2.442500114440918,2.5425000190734863,True,3.3708023419493256e-15,0.25,2.4114640999737245,2.5267290614733597,2.3025,2.4425,2.4625,2.5425,0.13999999999999968,0.08000000000000007 --UuX1xuaiiE/0,-UuX1xuaiiE,0,7,their,2.5824999809265137,2.9825000762939453,True,1.4151743673944915e-14,0.261471152305603,2.5825076917084684,2.9839370714614866,2.5825,2.5825,2.9825,2.9825,0.0,0.0 --UuX1xuaiiE/0,-UuX1xuaiiE,0,8,passion,3.122499942779541,3.502500057220459,True,6.910157649427136e-17,0.25,3.1188937037274393,3.5345878746530324,3.0825,3.1225,3.5025,3.5625,0.040000000000000036,0.06000000000000005 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--UuX1xuaiiE/3,-UuX1xuaiiE,3,4,become,1.722499966621399,2.0425000190734863,True,1.1037502509192443e-11,0.6594774723052979,1.7086218803776163,2.042267428813497,1.6025,1.7225,2.0425,2.0425,0.11999999999999988,0.0 --UuX1xuaiiE/3,-UuX1xuaiiE,3,5,a,2.622499942779541,2.6424999237060547,True,2.320204575342877e-12,0.25,2.6157081677890304,2.6357081677890317,2.6225,2.6225,2.6425,2.6425,0.0,0.0 --UuX1xuaiiE/3,-UuX1xuaiiE,3,6,human,2.702500104904175,2.9024999141693115,True,2.8239372645844085e-12,0.25,2.707741696294927,2.923241916792613,2.7025,2.7625,2.9025,3.0625,0.06000000000000005,0.16000000000000014 --UuX1xuaiiE/3,-UuX1xuaiiE,3,7,rights,2.9825000762939453,3.4825000762939453,True,2.520619477031083e-11,1.5060398578643799,3.020026811992114,3.50541435590898,2.9825,3.2425,3.4825,3.5825,0.26000000000000023,0.10000000000000009 --UuX1xuaiiE/3,-UuX1xuaiiE,3,8,lawyer,3.622499942779541,4.002500057220459,True,1.673673873103798e-11,1.0,3.636799554936652,4.012098400623447,3.6225,3.6825,4.0025,4.022500000000001,0.06000000000000005,0.020000000000000462 --UuX1xuaiiE/6,-UuX1xuaiiE,6,0,I,0.5824999809265137,0.6025000214576721,True,1.787539005704275e-10,4.0,0.270109773646166,0.2901097736461649,0.0225,0.5824999999999999,0.0425,0.6024999999999999,0.5599999999999999,0.5599999999999999 --UuX1xuaiiE/6,-UuX1xuaiiE,6,1,ended,0.6225000023841858,0.8025000095367432,True,2.451882826545043e-13,0.36168426275253296,0.5396114880489867,0.7337382133486879,0.5225,0.6224999999999999,0.7224999999999999,0.8025,0.09999999999999998,0.08000000000000007 --UuX1xuaiiE/6,-UuX1xuaiiE,6,2,up,0.8424999713897705,0.9225000143051147,True,9.941535442092864e-13,1.466504454612732,0.7558957635136302,0.8178524341981249,0.7424999999999999,0.8424999999999999,0.8025,0.9225,0.09999999999999998,0.12 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--UuX1xuaiiE/6,-UuX1xuaiiE,6,7,the,1.8224999904632568,1.9824999570846558,True,2.22696115563005e-13,0.32850542664527893,1.8241144657810688,1.9721595686699893,1.8225,1.8225,1.9224999999999999,2.0025,0.0,0.08000000000000007 --UuX1xuaiiE/6,-UuX1xuaiiE,6,8,US,2.1624999046325684,2.242500066757202,True,7.930261482214096e-12,4.0,2.1214027566976656,2.197309546467254,1.9625,2.1625,2.0225,2.2425,0.20000000000000018,0.2200000000000002 --UuX1xuaiiE/6,-UuX1xuaiiE,6,9,government,2.262500047683716,2.7225000858306885,True,1.3203499606856146e-14,0.25,2.2378999774402657,2.7214863527895146,2.1625,2.2625,2.7225,2.7225,0.10000000000000009,0.0 --UuX1xuaiiE/6,-UuX1xuaiiE,6,10,as,2.8424999713897705,2.9024999141693115,True,7.30077456823075e-12,4.0,2.842739371428413,2.902744261495768,2.8425,2.8425,2.9025,2.9025,0.0,0.0 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--UuX1xuaiiE/6,-UuX1xuaiiE,6,15,in,5.722499847412109,5.802499771118164,True,6.507028531450854e-13,0.959870457649231,5.719573747226648,5.80167959979051,5.7225,5.7225,5.8025,5.822500000000001,0.0,0.020000000000000462 --UuX1xuaiiE/6,-UuX1xuaiiE,6,16,war,5.882500171661377,6.002500057220459,True,2.1248417522018448e-12,3.1344151496887207,5.878821325527894,5.999303897122543,5.8825,5.8825,6.0025,6.0025,0.0,0.0 --UuX1xuaiiE/6,-UuX1xuaiiE,6,17,crimes,6.042500019073486,6.34250020980835,True,1.829281355298501e-13,0.2698425352573395,6.033983176986125,6.344507453138877,6.022500000000001,6.0425,6.3425,6.3425,0.019999999999999574,0.0 --UuX1xuaiiE/6,-UuX1xuaiiE,6,18,and,6.382500171661377,6.482500076293945,True,1.405874928191858e-13,0.25,6.384966204069522,6.485061293202971,6.3825,6.3825,6.482500000000001,6.482500000000001,0.0,0.0 --UuX1xuaiiE/6,-UuX1xuaiiE,6,19,human,6.502500057220459,6.702499866485596,True,7.051110455062737e-13,1.040129542350769,6.505737929966874,6.709886966565923,6.5025,6.5025,6.702500000000001,6.7225,0.0,0.019999999999999574 --UuX1xuaiiE/6,-UuX1xuaiiE,6,20,rights,6.722499847412109,6.982500076293945,True,4.419648241132945e-12,4.0,6.7350518605513106,7.002116245068988,6.7225,6.782500000000001,6.982500000000001,7.022500000000001,0.0600000000000005,0.040000000000000036 --UuX1xuaiiE/6,-UuX1xuaiiE,6,21,issues,7.042500019073486,7.34250020980835,True,1.0247198922730405e-11,4.0,7.047294136122448,7.364531168340181,7.0425,7.0425,7.3425,7.562500000000001,0.0,0.22000000000000064 --a55Q6RWvTA/3,-a55Q6RWvTA,3,0,And,0.02250000089406967,0.8224999904632568,True,1.8799320281905063e-14,0.25,0.119519558806842,0.8420489822368266,0.0225,0.7625,0.8225,0.9225,0.74,0.09999999999999998 --a55Q6RWvTA/3,-a55Q6RWvTA,3,1,if,1.0425000190734863,1.122499942779541,True,1.864498572895501e-12,4.0,1.0396889744500983,1.1189426038956152,1.0425,1.0425,1.1025,1.1225,0.0,0.020000000000000018 --a55Q6RWvTA/3,-a55Q6RWvTA,3,2,you,1.1825000047683716,1.3825000524520874,True,8.737685922022287e-12,4.0,1.1823567191989515,1.3813940509165903,1.1824999999999999,1.1824999999999999,1.3825,1.3825,0.0,0.0 --a55Q6RWvTA/3,-a55Q6RWvTA,3,3,clip,1.4424999952316284,1.6825000047683716,True,4.2130695091478765e-13,1.162251591682434,1.4420208862780637,1.6970771282427792,1.4425,1.4425,1.6824999999999999,1.7425,0.0,0.06000000000000005 --a55Q6RWvTA/3,-a55Q6RWvTA,3,4,"coupons,",1.7625000476837158,2.5425000190734863,True,1.3545874491538434e-12,3.736875057220459,1.7613384775974255,2.544447333196721,1.7625,1.7625,2.5425,2.5825,0.0,0.040000000000000036 --a55Q6RWvTA/3,-a55Q6RWvTA,3,5,if,2.5824999809265137,2.742500066757202,True,1.0346320154785982e-12,2.854219913482666,2.591940711601199,2.7392036510285633,2.5825,2.7025,2.7225,2.7825,0.1200000000000001,0.06000000000000005 --a55Q6RWvTA/3,-a55Q6RWvTA,3,6,you,2.802500009536743,2.9825000762939453,True,4.206752676240433e-13,1.1605089902877808,2.805593026690063,2.980874186453363,2.8025,2.8425,2.9825,2.9825,0.03999999999999959,0.0 --a55Q6RWvTA/3,-a55Q6RWvTA,3,7,don't,3.0425000190734863,3.242500066757202,True,6.30838103976572e-10,4.0,3.0425001275429757,3.2477120612251564,3.0425,3.0425,3.2425,3.2825,0.0,0.040000000000000036 --a55Q6RWvTA/3,-a55Q6RWvTA,3,8,go,3.3424999713897705,3.442500114440918,True,1.436209983406156e-12,3.962045431137085,3.342501925342056,3.44250103576293,3.3425,3.3425,3.4425,3.4425,0.0,0.0 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--aqamKhZ1Ec/0,-aqamKhZ1Ec,0,4,very,3.262500047683716,3.502500057220459,True,4.024087920523334e-13,0.6636766195297241,3.2628512483329692,3.5029909181345595,3.2625,3.2625,3.5025,3.5025,0.0,0.0 --aqamKhZ1Ec/0,-aqamKhZ1Ec,0,5,serious,3.6424999237060547,4.102499961853027,True,1.2576761463864439e-13,0.25,3.604995371759258,4.081283859552203,3.5425,3.6425,4.0425,4.1025,0.10000000000000009,0.05999999999999961 --aqamKhZ1Ec/0,-aqamKhZ1Ec,0,6,tribal,4.162499904632568,4.582499980926514,True,6.287949761568656e-12,4.0,4.164219364401541,4.584062047007865,4.1625000000000005,4.1625000000000005,4.5825000000000005,4.5825000000000005,0.0,0.0 --aqamKhZ1Ec/0,-aqamKhZ1Ec,0,7,warfare,4.722499847412109,5.202499866485596,True,1.5909093432821958e-13,0.26238226890563965,4.706837861170518,5.205690278227914,4.6425,4.7225,5.202500000000001,5.202500000000001,0.08000000000000007,0.0 --aqamKhZ1Ec/0,-aqamKhZ1Ec,0,8,in,6.142499923706055,6.202499866485596,True,1.019524534240368e-10,4.0,6.1186756160246425,6.21318732554233,6.062500000000001,6.1825,6.202500000000001,6.2625,0.11999999999999922,0.05999999999999961 --aqamKhZ1Ec/0,-aqamKhZ1Ec,0,9,Kenya,7.082499980926514,8.0024995803833,True,6.063326381776368e-13,1.0,7.055643839797694,8.001751852174415,6.3425,7.482500000000001,8.0025,8.0025,1.1400000000000006,0.0 --aqamKhZ1Ec/0,-aqamKhZ1Ec,0,10,following,8.162500381469727,9.282500267028809,True,1.3233601497616987e-12,2.1825644969940186,8.167307698703715,9.274023163387671,8.1625,8.1625,9.2025,9.282499999999999,0.0,0.0799999999999983 --aqamKhZ1Ec/0,-aqamKhZ1Ec,0,11,a,9.40250015258789,9.422499656677246,True,3.7868968377763323e-11,4.0,9.40242807987088,9.422428079870883,9.4025,9.4025,9.4225,9.4225,0.0,0.0 --aqamKhZ1Ec/0,-aqamKhZ1Ec,0,12,disputed,9.462499618530273,9.90250015258789,True,2.7071137757676833e-13,0.4464733600616455,9.47686688744534,9.925606046827598,9.4625,9.5025,9.9025,9.9825,0.03999999999999915,0.08000000000000007 --aqamKhZ1Ec/0,-aqamKhZ1Ec,0,13,election.,10.022500038146973,10.802499771118164,True,3.659902676061977e-12,4.0,10.029209911460025,10.806518969512238,10.022499999999999,10.022499999999999,10.8025,10.862499999999999,0.0,0.05999999999999872 --dxfTGcXJoc/1,-dxfTGcXJoc,1,0,For,0.5625,0.7425000071525574,True,2.275428977183136e-12,4.0,0.3649672540175232,0.656470491487688,0.0225,0.5625,0.5824999999999999,0.7424999999999999,0.54,0.16000000000000003 --dxfTGcXJoc/1,-dxfTGcXJoc,1,1,the,0.8025000095367432,0.9424999952316284,True,3.523209827181739e-13,2.672248363494873,0.7190080419087704,0.8384369833953639,0.6425,0.8025,0.7424999999999999,0.9425,0.16000000000000003,0.20000000000000007 --dxfTGcXJoc/1,-dxfTGcXJoc,1,2,10th,1.002500057220459,1.0625,True,7.89121092892287e-16,0.25,0.9201663747546199,0.991584920117422,0.8025,1.0025,0.9025,1.0825,0.19999999999999996,0.18000000000000005 --dxfTGcXJoc/1,-dxfTGcXJoc,1,3,straight,1.0824999809265137,1.462499976158142,True,5.292460907187473e-15,0.25,1.0590410591480313,1.4525213757665048,0.9225,1.1225,1.4025,1.4625,0.20000000000000007,0.05999999999999983 --dxfTGcXJoc/1,-dxfTGcXJoc,1,4,"year,",1.5824999809265137,1.7625000476837158,True,4.7748890480642583e-14,0.36216092109680176,1.5743957871409902,1.7569251246340676,1.4825,1.5825,1.6824999999999999,1.7625,0.10000000000000009,0.08000000000000007 --dxfTGcXJoc/1,-dxfTGcXJoc,1,5,some,2.262500047683716,2.5425000190734863,True,1.943253283981372e-12,4.0,2.2612920543236856,2.5424015098644395,2.2625,2.2625,2.5425,2.5425,0.0,0.0 --dxfTGcXJoc/1,-dxfTGcXJoc,1,6,of,2.5824999809265137,2.6624999046325684,True,3.9846300087589825e-13,3.022221565246582,2.5853655723810456,2.6652560546039608,2.5825,2.6025,2.6625,2.6625,0.020000000000000018,0.0 --dxfTGcXJoc/1,-dxfTGcXJoc,1,7,Kentucky’s,2.762500047683716,3.262500047683716,True,1.15754682315089e-12,4.0,2.750634717027689,3.2556658742957265,2.7225,2.7625,3.2425,3.2625,0.040000000000000036,0.020000000000000018 --dxfTGcXJoc/1,-dxfTGcXJoc,1,8,best,3.422499895095825,3.762500047683716,True,8.019150258111243e-14,0.608228325843811,3.4022852380664403,3.72717692242951,3.2825,3.4225,3.7025,3.7625,0.13999999999999968,0.06000000000000005 --dxfTGcXJoc/1,-dxfTGcXJoc,1,9,and,3.922499895095825,4.022500038146973,True,1.6227658797339332e-14,0.25,3.9223628956324568,4.022449556910346,3.9225,3.9225,4.022500000000001,4.022500000000001,0.0,0.0 --dxfTGcXJoc/1,-dxfTGcXJoc,1,10,most,4.082499980926514,4.262499809265137,True,9.945570164952497e-14,0.7543414831161499,4.082499603629278,4.262509829162647,4.0825000000000005,4.0825000000000005,4.2625,4.2625,0.0,0.0 --dxfTGcXJoc/1,-dxfTGcXJoc,1,11,innovative,4.442500114440918,5.122499942779541,True,1.133854512017085e-12,4.0,4.4410250441935455,5.11803027501793,4.442500000000001,4.442500000000001,5.102500000000001,5.1225000000000005,0.0,0.019999999999999574 --dxfTGcXJoc/1,-dxfTGcXJoc,1,12,biotech,5.162499904632568,5.502500057220459,True,1.5729797564305315e-13,1.193057656288147,5.155285740506763,5.500234169729445,5.1225000000000005,5.1625000000000005,5.4625,5.5025,0.040000000000000036,0.040000000000000036 --dxfTGcXJoc/1,-dxfTGcXJoc,1,13,companies,5.542500019073486,6.022500038146973,True,8.639043798906731e-13,4.0,5.54199486653639,6.021684045459382,5.5425,5.5425,6.022500000000001,6.022500000000001,0.0,0.0 --dxfTGcXJoc/1,-dxfTGcXJoc,1,14,and,6.082499980926514,6.182499885559082,True,4.0721878045166596e-14,0.30886316299438477,6.081297587982795,6.181694894313973,6.0825000000000005,6.0825000000000005,6.1825,6.1825,0.0,0.0 --dxfTGcXJoc/1,-dxfTGcXJoc,1,15,technologies,6.222499847412109,6.922500133514404,True,2.050334592862066e-13,1.555116891860962,6.222158853837142,6.937339063734151,6.2225,6.2225,6.9225,6.9625,0.0,0.040000000000000036 --dxfTGcXJoc/1,-dxfTGcXJoc,1,16,were,6.942500114440918,7.482500076293945,True,3.483278661169098e-14,0.26419615745544434,7.130313396095074,7.4978267357210475,6.942500000000001,7.322500000000001,7.4625,7.522500000000001,0.3799999999999999,0.0600000000000005 --dxfTGcXJoc/1,-dxfTGcXJoc,1,17,on,7.502500057220459,7.702499866485596,True,1.5179640530660343e-11,4.0,7.540963992421254,7.71163558566263,7.5025,7.6825,7.702500000000001,7.782500000000001,0.17999999999999972,0.08000000000000007 --dxfTGcXJoc/1,-dxfTGcXJoc,1,18,display,7.84250020980835,8.40250015258789,True,7.89802034537046e-13,4.0,7.842515193459164,8.403630710839492,7.8425,7.8425,8.4025,8.4025,0.0,0.0 --dxfTGcXJoc/1,-dxfTGcXJoc,1,19,at,8.662500381469727,8.72249984741211,True,2.0993258435071053e-15,0.25,8.662467828886165,8.7226922086402,8.6625,8.6625,8.7225,8.7225,0.0,0.0 --dxfTGcXJoc/1,-dxfTGcXJoc,1,20,the,8.822500228881836,8.942500114440918,True,1.2593050246253318e-13,0.9551448225975037,8.822210482336128,8.942231664275779,8.8225,8.8225,8.942499999999999,8.942499999999999,0.0,0.0 --dxfTGcXJoc/1,-dxfTGcXJoc,1,21,annual,9.082500457763672,9.382499694824219,True,5.38172479670751e-13,4.0,9.082499874861758,9.382500529056607,9.0825,9.0825,9.3825,9.3825,0.0,0.0 --dxfTGcXJoc/1,-dxfTGcXJoc,1,22,BIO,9.662500381469727,9.90250015258789,True,6.07335223778982e-11,4.0,9.578064211583579,9.880240503537104,9.442499999999999,9.6625,9.8225,9.9025,0.22000000000000064,0.08000000000000007 --dxfTGcXJoc/1,-dxfTGcXJoc,1,23,International,9.922499656677246,10.682499885559082,True,7.311739511376911e-14,0.5545733571052551,9.908699669202857,10.700666650198874,9.8825,9.942499999999999,10.6825,10.7425,0.05999999999999872,0.0600000000000005 --dxfTGcXJoc/1,-dxfTGcXJoc,1,24,"Convention,",10.72249984741211,11.262499809265137,True,1.0889742883476994e-13,0.8259541392326355,10.747097081493896,11.267687896899911,10.7225,10.8025,11.2625,11.3025,0.08000000000000007,0.040000000000000924 --dxfTGcXJoc/1,-dxfTGcXJoc,1,25,which,11.322500228881836,12.082500457763672,True,4.037281915573489e-14,0.30621564388275146,11.364414611412695,12.082394236045653,11.3225,11.7425,12.0825,12.0825,0.41999999999999993,0.0 --dxfTGcXJoc/1,-dxfTGcXJoc,1,26,I,12.382499694824219,12.40250015258789,True,1.2588138864622067e-10,4.0,12.382510769537037,12.402510769537036,12.3825,12.3825,12.4025,12.4025,0.0,0.0 --dxfTGcXJoc/1,-dxfTGcXJoc,1,27,and,12.482500076293945,12.642499923706055,True,1.533161313562511e-14,0.25,12.48280965262064,12.642572691239474,12.4825,12.4825,12.6425,12.6425,0.0,0.0 --dxfTGcXJoc/1,-dxfTGcXJoc,1,28,other,12.702500343322754,12.962499618530273,True,9.549927173927233e-14,0.7243331670761108,12.702509718675014,12.962495484432637,12.7025,12.7025,12.9625,12.9625,0.0,0.0 --dxfTGcXJoc/1,-dxfTGcXJoc,1,29,state,12.982500076293945,13.242500305175781,True,6.808946852523978e-14,0.5164380669593811,12.98288355950477,13.242183987541857,12.9825,12.9825,13.2425,13.2425,0.0,0.0 --dxfTGcXJoc/1,-dxfTGcXJoc,1,30,officials,13.262499809265137,13.702500343322754,True,2.7725016360957873e-14,0.25,13.26382449943722,13.702492000013828,13.2625,13.2825,13.7025,13.7025,0.02000000000000135,0.0 --dxfTGcXJoc/1,-dxfTGcXJoc,1,31,attended,13.72249984741211,14.162500381469727,True,7.640498070381543e-15,0.25,13.724172197793889,14.162500196491765,13.7225,13.7225,14.1625,14.1625,0.0,0.0 --dxfTGcXJoc/1,-dxfTGcXJoc,1,32,this,14.22249984741211,14.362500190734863,True,1.377583214601935e-13,1.0448552370071411,14.222454748006289,14.362454751756776,14.2225,14.2225,14.362499999999999,14.362499999999999,0.0,0.0 --dxfTGcXJoc/1,-dxfTGcXJoc,1,33,week,14.422499656677246,14.6225004196167,True,4.912310792512531e-13,3.725839376449585,14.422499999645678,14.622500000213078,14.4225,14.4225,14.6225,14.6225,0.0,0.0 --dxfTGcXJoc/1,-dxfTGcXJoc,1,34,in,14.662500381469727,14.882499694824219,True,1.148558245039899e-12,4.0,14.664907397502905,14.88327589515385,14.6625,14.6625,14.8825,14.8825,0.0,0.0 --dxfTGcXJoc/1,-dxfTGcXJoc,1,35,Chicago.,14.962499618530273,15.522500038146973,True,7.882481017733312e-13,4.0,14.962501636791323,15.51671348154772,14.9625,14.9625,15.5025,15.522499999999999,0.0,0.019999999999999574 --dxfTGcXJoc/0,-dxfTGcXJoc,0,0,This,0.20250000059604645,0.6625000238418579,True,1.436269511187623e-15,0.25,0.18800400140906554,0.6712783209637588,0.0225,0.3825,0.6625,0.7025,0.36,0.040000000000000036 --dxfTGcXJoc/0,-dxfTGcXJoc,0,1,is,0.7225000262260437,0.8025000095367432,True,1.321620655796163e-12,4.0,0.7296080131653702,0.8073423085081691,0.7224999999999999,0.7825,0.8025,0.8424999999999999,0.06000000000000005,0.039999999999999925 --dxfTGcXJoc/0,-dxfTGcXJoc,0,2,Governor,0.9024999737739563,1.2424999475479126,True,1.0927341930616619e-12,4.0,0.887471538448594,1.2277552870491857,0.8624999999999999,0.9025,1.2025,1.2425,0.040000000000000036,0.040000000000000036 --dxfTGcXJoc/0,-dxfTGcXJoc,0,3,Steve,1.2825000286102295,1.5625,True,7.474941753895722e-14,0.2840318977832794,1.281864992925297,1.5529176310112593,1.2825,1.2825,1.5425,1.5625,0.0,0.020000000000000018 --dxfTGcXJoc/0,-dxfTGcXJoc,0,4,Beshear,1.6024999618530273,1.9824999570846558,True,7.465651361004966e-13,2.8367886543273926,1.60314666497837,2.0731438341617148,1.6025,1.6025,1.9825,2.7625,0.0,0.7800000000000002 --dxfTGcXJoc/0,-dxfTGcXJoc,0,5,...,nan,nan,False,0.0,nan,nan,nan,nan,nan,nan,nan,nan,nan --dxfTGcXJoc/0,-dxfTGcXJoc,0,6,About,2.0824999809265137,2.8424999713897705,True,3.1875823053133245e-13,1.21121346950531,2.23390625717333,2.906884357988618,2.0825,2.9425,2.8425,3.3825,0.8599999999999999,0.54 --dxfTGcXJoc/0,-dxfTGcXJoc,0,7,Kentucky,2.942500114440918,4.482500076293945,True,1.9611760132542955e-12,4.0,3.0234051678294898,4.527675130658362,2.9425,3.4225,4.482500000000001,4.862500000000001,0.48,0.3799999999999999 --dxfTGcXJoc/0,-dxfTGcXJoc,0,8,Our,4.78249979019165,5.002500057220459,True,2.0286934025032233e-12,4.0,4.766380309692605,4.975474037119736,4.6225000000000005,4.9225,4.862500000000001,5.0425,0.2999999999999998,0.17999999999999972 --dxfTGcXJoc/0,-dxfTGcXJoc,0,9,state,5.142499923706055,5.482500076293945,True,2.2418547053482119e-13,0.8518571257591248,5.102480756287364,5.457607935480797,4.982500000000001,5.1425,5.3825,5.482500000000001,0.15999999999999925,0.10000000000000053 --dxfTGcXJoc/0,-dxfTGcXJoc,0,10,is,5.542500019073486,5.622499942779541,True,2.1595016898821873e-13,0.8205647468566895,5.542502282433472,5.62249050879839,5.5425,5.5425,5.6225000000000005,5.6225000000000005,0.0,0.0 --dxfTGcXJoc/0,-dxfTGcXJoc,0,11,home,5.702499866485596,5.902500152587891,True,7.612381997543563e-14,0.2892543375492096,5.6969075990261855,5.905562707339487,5.6425,5.702500000000001,5.862500000000001,5.902500000000001,0.0600000000000005,0.040000000000000036 --dxfTGcXJoc/0,-dxfTGcXJoc,0,12,to,5.922500133514404,6.042500019073486,True,7.356884334586491e-14,0.27954596281051636,5.937102992383272,6.056635431575253,5.9225,5.9225,6.0425,6.0425,0.0,0.0 --dxfTGcXJoc/0,-dxfTGcXJoc,0,13,more,6.222499847412109,6.622499942779541,True,6.24342970986097e-13,2.372370481491089,6.277575214162152,6.631543457001568,6.2225,6.322500000000001,6.6225000000000005,6.6625000000000005,0.10000000000000053,0.040000000000000036 --dxfTGcXJoc/0,-dxfTGcXJoc,0,14,than,6.802499771118164,7.102499961853027,True,9.57974747705509e-14,0.3640100359916687,6.803191204364817,7.107020835049525,6.8025,6.8025,7.102500000000001,7.142500000000001,0.0,0.040000000000000036 --dxfTGcXJoc/0,-dxfTGcXJoc,0,15,"1,500",nan,nan,False,0.0,nan,nan,nan,nan,nan,nan,nan,nan,nan --dxfTGcXJoc/0,-dxfTGcXJoc,0,16,bioscience,7.28249979019165,8.0625,True,5.816785312966199e-13,2.210254669189453,7.267452880689412,8.062370269304813,7.1825,7.282500000000001,8.0625,8.0625,0.10000000000000053,0.0 --dxfTGcXJoc/0,-dxfTGcXJoc,0,17,and,8.102499961853027,8.342499732971191,True,8.574386453673657e-14,0.32580846548080444,8.103254544239489,8.342748976407043,8.1025,8.1025,8.3425,8.3425,0.0,0.0 --dxfTGcXJoc/0,-dxfTGcXJoc,0,18,lifescience,8.462499618530273,9.0625,True,9.144152449125365e-13,3.474583387374878,8.440910172928174,9.06317123654407,8.3825,8.4625,9.0625,9.0625,0.08000000000000007,0.0 --dxfTGcXJoc/0,-dxfTGcXJoc,0,19,companies,9.102499961853027,10.102499961853027,True,1.1046472981127153e-12,4.0,9.103525367338998,10.10579297477803,9.1025,9.1025,10.1025,10.1225,0.0,0.02000000000000135 --dxfTGcXJoc/0,-dxfTGcXJoc,0,20,and,10.22249984741211,10.362500190734863,True,6.748803447510776e-14,0.2564401924610138,10.222497809790337,10.356745416243506,10.2225,10.2225,10.3425,10.362499999999999,0.0,0.019999999999999574 --dxfTGcXJoc/0,-dxfTGcXJoc,0,21,more,10.442500114440918,10.602499961853027,True,2.3733483711305126e-13,0.9018219113349915,10.414533955030066,10.579202864997653,10.3825,10.442499999999999,10.5625,10.6025,0.05999999999999872,0.03999999999999915 --dxfTGcXJoc/0,-dxfTGcXJoc,0,22,than,10.72249984741211,10.962499618530273,True,6.653097669138963e-13,2.5280356407165527,10.7225013520628,10.963060296230047,10.7225,10.7225,10.9625,10.9625,0.0,0.0 --dxfTGcXJoc/0,-dxfTGcXJoc,0,23,"100,000",nan,nan,False,0.0,nan,nan,nan,nan,nan,nan,nan,nan,nan --dxfTGcXJoc/0,-dxfTGcXJoc,0,24,people,11.102499961853027,11.5024995803833,True,1.0843516568600359e-13,0.41203057765960693,11.102483038622685,11.502500341848476,11.1025,11.1025,11.5025,11.5025,0.0,0.0 --dxfTGcXJoc/0,-dxfTGcXJoc,0,25,who,11.5625,11.702500343322754,True,1.174416358433461e-12,4.0,11.576823297591739,11.714007237913536,11.5625,11.6225,11.7025,11.7425,0.0600000000000005,0.03999999999999915 --dxfTGcXJoc/0,-dxfTGcXJoc,0,26,work,11.90250015258789,12.162500381469727,True,7.076656020075026e-14,0.2688978910446167,11.905745763990348,12.163903512245955,11.9025,11.9025,12.1625,12.1625,0.0,0.0 --dxfTGcXJoc/0,-dxfTGcXJoc,0,27,for,12.262499809265137,12.40250015258789,True,6.21533965787513e-13,2.36169695854187,12.262508738077944,12.402008549180124,12.2625,12.2625,12.4025,12.4025,0.0,0.0 --dxfTGcXJoc/0,-dxfTGcXJoc,0,28,these,12.5024995803833,12.72249984741211,True,5.1970743247115037e-14,0.25,12.50070802564183,12.722592853346624,12.5025,12.5025,12.7225,12.7225,0.0,0.0 --dxfTGcXJoc/0,-dxfTGcXJoc,0,29,"firms,",12.822500228881836,13.202500343322754,True,1.987435586383538e-14,0.25,12.810238807852192,13.202497205526639,12.7825,12.8225,13.2025,13.2025,0.03999999999999915,0.0 --dxfTGcXJoc/0,-dxfTGcXJoc,0,30,in,13.22249984741211,13.962499618530273,True,3.6057056862839887e-13,1.370091438293457,13.324914664363726,13.96804775045872,13.2225,13.942499999999999,13.9625,14.0425,0.7199999999999989,0.08000000000000007 --dxfTGcXJoc/0,-dxfTGcXJoc,0,31,areas,14.182499885559082,14.522500038146973,True,1.2572369089813157e-13,0.47772330045700073,14.18246398667518,14.522510488364302,14.1825,14.1825,14.522499999999999,14.522499999999999,0.0,0.0 --dxfTGcXJoc/0,-dxfTGcXJoc,0,32,from,14.5625,14.822500228881836,True,8.391539314822356e-15,0.25,14.562750522345475,14.823092307045739,14.5625,14.5625,14.8225,14.8225,0.0,0.0 --dxfTGcXJoc/0,-dxfTGcXJoc,0,33,nutrigenomics,15.182499885559082,16.122499465942383,True,1.1121746969558477e-12,4.0,15.177670019934878,16.099262169106762,15.1425,15.1825,16.0225,16.122500000000002,0.03999999999999915,0.10000000000000142 --dxfTGcXJoc/0,-dxfTGcXJoc,0,34,and,16.262500762939453,16.38249969482422,True,4.261740564398195e-14,0.25,16.258652767187964,16.38099827413018,16.262500000000003,16.282500000000002,16.3825,16.3825,0.019999999999999574,0.0 --dxfTGcXJoc/0,-dxfTGcXJoc,0,35,pharmaceuticals,16.422500610351562,17.262500762939453,True,5.213513540151815e-13,1.9810242652893066,16.4224417108849,17.25543344328825,16.422500000000003,16.422500000000003,17.2225,17.262500000000003,0.0,0.0400000000000027 --dxfTGcXJoc/0,-dxfTGcXJoc,0,36,to,17.642499923706055,17.74250030517578,True,4.542984640820008e-13,1.7262375354766846,17.642496491416676,17.742499915475133,17.642500000000002,17.642500000000002,17.742500000000003,17.742500000000003,0.0,0.0 --dxfTGcXJoc/0,-dxfTGcXJoc,0,37,nanotechnology,17.782499313354492,18.762500762939453,True,2.8901043342376143e-13,1.0981781482696533,17.782588215090776,18.763284028765124,17.782500000000002,17.782500000000002,18.762500000000003,18.762500000000003,0.0,0.0 --dxfTGcXJoc/0,-dxfTGcXJoc,0,38,and,18.822500228881836,18.922500610351562,True,1.1881575943657827e-14,0.25,18.822476509585076,18.922488605782018,18.8225,18.8225,18.922500000000003,18.922500000000003,0.0,0.0 --dxfTGcXJoc/0,-dxfTGcXJoc,0,39,medical,18.9424991607666,19.262500762939453,True,1.1681875898474775e-13,0.4438864290714264,18.942492184714514,19.2624987997749,18.942500000000003,18.942500000000003,19.262500000000003,19.262500000000003,0.0,0.0 --dxfTGcXJoc/0,-dxfTGcXJoc,0,40,devices.,19.282499313354492,19.802499771118164,True,1.4210033974157432e-12,4.0,19.282502277797803,19.802471720501764,19.282500000000002,19.282500000000002,19.802500000000002,19.802500000000002,0.0,0.0 --dxfTGcXJoc/2,-dxfTGcXJoc,2,0,An,0.5625,0.6424999833106995,True,3.528646423450396e-14,2.5437161922454834,0.5517457553728019,0.6400199589743981,0.5625,0.5625,0.6425,0.6425,0.0,0.0 --dxfTGcXJoc/2,-dxfTGcXJoc,2,1,estimated,0.762499988079071,1.2625000476837158,True,3.06941976074501e-15,0.25,0.7624537774900568,1.2747010779553254,0.7625,0.7625,1.2625,1.3025,0.0,0.040000000000000036 --dxfTGcXJoc/2,-dxfTGcXJoc,2,2,"20,000",nan,nan,False,0.0,nan,nan,nan,nan,nan,nan,nan,nan,nan --dxfTGcXJoc/2,-dxfTGcXJoc,2,3,biotech,1.502500057220459,2.1424999237060547,True,5.178755102704102e-13,4.0,1.5016645351351747,2.145477612250111,1.5025,1.5025,2.1425,2.1625,0.0,0.020000000000000018 --dxfTGcXJoc/2,-dxfTGcXJoc,2,4,"scientists,",2.362499952316284,3.2825000286102295,True,3.88290907673422e-13,4.0,2.3601136758402634,3.177040551962975,2.3625,2.3625,2.9225,3.2825,0.0,0.3600000000000003 --dxfTGcXJoc/2,-dxfTGcXJoc,2,5,executives,3.3424999713897705,4.502500057220459,True,4.8946347734439566e-14,3.5284242630004883,3.3090474232848885,4.504003094828398,3.1825,3.4425,4.5025,4.5425,0.2599999999999998,0.040000000000000036 --dxfTGcXJoc/2,-dxfTGcXJoc,2,6,and,4.742499828338623,4.862500190734863,True,7.208249534101149e-15,0.5196253657341003,4.737240676908777,4.860440843264866,4.742500000000001,4.742500000000001,4.862500000000001,4.862500000000001,0.0,0.0 --dxfTGcXJoc/2,-dxfTGcXJoc,2,7,industry,5.042500019073486,5.442500114440918,True,6.4237835225287344e-15,0.46307510137557983,5.040880535443564,5.443378707143529,5.0425,5.0425,5.442500000000001,5.442500000000001,0.0,0.0 --dxfTGcXJoc/2,-dxfTGcXJoc,2,8,experts,5.582499980926514,6.022500038146973,True,3.06460179498938e-14,2.209197759628296,5.5703212329533915,6.014850126754625,5.482500000000001,5.5825000000000005,5.9625,6.022500000000001,0.09999999999999964,0.0600000000000005 --dxfTGcXJoc/2,-dxfTGcXJoc,2,9,from,6.422500133514404,6.582499980926514,True,9.360125936930621e-16,0.25,6.38109006975023,6.616702439780006,6.022500000000001,6.5025,6.5825000000000005,6.702500000000001,0.47999999999999954,0.1200000000000001 --dxfTGcXJoc/2,-dxfTGcXJoc,2,10,more,6.622499942779541,6.882500171661377,True,9.563321136515576e-14,4.0,6.664792178092532,6.8927378471517535,6.6225000000000005,6.7625,6.8825,6.9225,0.13999999999999968,0.040000000000000036 --dxfTGcXJoc/2,-dxfTGcXJoc,2,11,than,7.002500057220459,7.28249979019165,True,5.0399656372152393e-14,3.6331899166107178,7.0024999794329315,7.282500014929406,7.0025,7.0025,7.282500000000001,7.282500000000001,0.0,0.0 --dxfTGcXJoc/2,-dxfTGcXJoc,2,12,50,nan,nan,False,0.0,nan,nan,nan,nan,nan,nan,nan,nan,nan --dxfTGcXJoc/2,-dxfTGcXJoc,2,13,nations,7.362500190734863,7.742499828338623,True,3.6337700731715276e-15,0.261949747800827,7.369429892315447,7.749385730355412,7.362500000000001,7.4225,7.742500000000001,7.782500000000001,0.05999999999999961,0.040000000000000036 --dxfTGcXJoc/2,-dxfTGcXJoc,2,14,were,8.0625,8.22249984741211,True,1.6512727735737767e-14,1.190362811088562,8.062279727477186,8.222492308029125,8.0625,8.0625,8.2225,8.2225,0.0,0.0 --dxfTGcXJoc/2,-dxfTGcXJoc,2,15,at,8.382499694824219,8.462499618530273,True,2.5949011040230733e-15,0.25,8.382462737272258,8.46255610150032,8.3825,8.3825,8.4625,8.4625,0.0,0.0 --dxfTGcXJoc/2,-dxfTGcXJoc,2,16,the,8.522500038146973,8.642499923706055,True,1.0026508991150445e-15,0.25,8.527928748031597,8.648442775581263,8.5025,8.5625,8.6425,8.6825,0.0600000000000005,0.03999999999999915 --dxfTGcXJoc/2,-dxfTGcXJoc,2,17,BIO,8.662500381469727,8.942500114440918,True,7.251367041549717e-12,4.0,8.685797706798342,8.935314419747938,8.6625,8.8225,8.9025,8.9625,0.16000000000000014,0.0600000000000005 --dxfTGcXJoc/2,-dxfTGcXJoc,2,18,conference,9.0024995803833,9.5625,True,1.2436561925687623e-13,4.0,9.002366312686632,9.553113604517561,9.0025,9.0025,9.522499999999999,9.5625,0.0,0.040000000000000924 --dxfTGcXJoc/2,-dxfTGcXJoc,2,19,to,9.602499961853027,9.702500343322754,True,4.1949855590119045e-14,3.024064064025879,9.602500040663637,9.702500020830492,9.6025,9.6025,9.7025,9.7025,0.0,0.0 --dxfTGcXJoc/2,-dxfTGcXJoc,2,20,learn,9.802499771118164,10.0625,True,2.779141040325369e-16,0.25,9.80226629806537,10.062706163218133,9.8025,9.8025,10.0625,10.0625,0.0,0.0 --dxfTGcXJoc/2,-dxfTGcXJoc,2,21,about,10.202500343322754,10.442500114440918,True,1.123129689158944e-14,0.8096371293067932,10.18387034190013,10.433185442440921,10.1225,10.2025,10.4025,10.442499999999999,0.08000000000000007,0.03999999999999915 --dxfTGcXJoc/2,-dxfTGcXJoc,2,22,the,10.462499618530273,10.5625,True,2.2475309865299534e-15,0.25,10.462392739534936,10.562392741067562,10.4625,10.4625,10.5625,10.5625,0.0,0.0 --dxfTGcXJoc/2,-dxfTGcXJoc,2,23,latest,10.582500457763672,10.90250015258789,True,3.027837854573112e-15,0.25,10.582967332999607,10.903517748664571,10.5825,10.5825,10.9025,10.9025,0.0,0.0 --dxfTGcXJoc/2,-dxfTGcXJoc,2,24,scientific,10.922499656677246,11.442500114440918,True,9.800098143140554e-16,0.25,10.925212631979305,11.448081060031368,10.9225,10.9625,11.442499999999999,11.522499999999999,0.040000000000000924,0.08000000000000007 --dxfTGcXJoc/2,-dxfTGcXJoc,2,25,"advances,",11.5024995803833,12.042499542236328,True,3.089713950183218e-14,2.2273004055023193,11.505574248933469,12.04758122048326,11.5025,11.5425,12.0425,12.0625,0.040000000000000924,0.019999999999999574 --dxfTGcXJoc/2,-dxfTGcXJoc,2,26,and,12.082500457763672,12.6225004196167,True,2.6814522011229386e-14,1.9329943656921387,12.084524282799858,12.62267486373147,12.0825,12.0825,12.6225,12.6225,0.0,0.0 --dxfTGcXJoc/2,-dxfTGcXJoc,2,27,to,12.682499885559082,12.742500305175781,True,4.186913927947634e-15,0.30182453989982605,12.68249796092688,12.742535934060587,12.6825,12.6825,12.7425,12.7425,0.0,0.0 --dxfTGcXJoc/2,-dxfTGcXJoc,2,28,exchange,12.862500190734863,13.362500190734863,True,4.882353388631832e-15,0.3519571125507355,12.839402800312625,13.350664314337655,12.7825,12.862499999999999,13.3225,13.362499999999999,0.0799999999999983,0.03999999999999915 --dxfTGcXJoc/2,-dxfTGcXJoc,2,29,ideas,13.482500076293945,13.882499694824219,True,3.945389344004943e-14,2.8441362380981445,13.482486191160033,13.882548812984396,13.4825,13.4825,13.8825,13.8825,0.0,0.0 --dxfTGcXJoc/2,-dxfTGcXJoc,2,30,and,13.922499656677246,14.282500267028809,True,2.3429222700387803e-14,1.6889562606811523,13.922678087539742,14.282500215590204,13.9225,13.9225,14.2825,14.2825,0.0,0.0 --dxfTGcXJoc/2,-dxfTGcXJoc,2,31,establish,14.322500228881836,14.762499809265137,True,1.651188557322996e-15,0.25,14.322500022955364,14.773487639175407,14.3225,14.3225,14.7625,14.8425,0.0,0.08000000000000007 --dxfTGcXJoc/2,-dxfTGcXJoc,2,32,business,14.822500228881836,15.242500305175781,True,8.650353789394286e-14,4.0,14.832761792509285,15.240279039373075,14.8225,14.862499999999999,15.2025,15.2425,0.03999999999999915,0.03999999999999915 --dxfTGcXJoc/2,-dxfTGcXJoc,2,33,relationships.,15.262499809265137,16.022499084472656,True,2.0376777268147532e-15,0.25,15.26250556174122,16.02250089371535,15.2625,15.2625,16.0225,16.0225,0.0,0.0 --dxfTGcXJoc/6,-dxfTGcXJoc,6,0,Kentucky’s,0.42250001430511475,0.9225000143051147,True,5.297549725280515e-12,4.0,0.4224967278309293,0.9225000000223426,0.4225,0.4225,0.9225,0.9225,0.0,0.0 --dxfTGcXJoc/6,-dxfTGcXJoc,6,1,participation,0.9424999952316284,1.7825000286102295,True,3.977016199002703e-14,0.8985112905502319,0.9465664649478172,1.7885813004286177,0.9425,0.9824999999999999,1.7825,1.8425,0.039999999999999925,0.06000000000000005 --dxfTGcXJoc/6,-dxfTGcXJoc,6,2,at,1.8424999713897705,1.9225000143051147,True,2.1943811513974038e-15,0.25,1.8533036193237216,1.9368632112892796,1.8425,1.9025,1.9224999999999999,2.0025,0.06000000000000005,0.08000000000000007 --dxfTGcXJoc/6,-dxfTGcXJoc,6,3,the,2.0225000381469727,2.1624999046325684,True,1.865988171812806e-15,0.25,2.020929687527187,2.151507239832155,1.9825,2.0225,2.0825,2.1625,0.040000000000000036,0.08000000000000007 --dxfTGcXJoc/6,-dxfTGcXJoc,6,4,annual,2.3424999713897705,2.682499885559082,True,2.7859146738661023e-13,4.0,2.308788690749572,2.6643921880715054,2.1625,2.3425,2.6225,2.6825,0.17999999999999972,0.06000000000000005 --dxfTGcXJoc/6,-dxfTGcXJoc,6,5,BIO,2.742500066757202,2.942500114440918,True,1.0218228173319854e-11,4.0,2.739909203795047,2.971583070334784,2.7425,2.7425,2.9425,3.0425,0.0,0.10000000000000009 --dxfTGcXJoc/6,-dxfTGcXJoc,6,6,International,2.9825000762939453,3.7225000858306885,True,4.252274124179681e-14,0.9606992602348328,3.0381234983409264,3.7414172328758766,2.9825,3.1225,3.7225,3.7625,0.14000000000000012,0.040000000000000036 --dxfTGcXJoc/6,-dxfTGcXJoc,6,7,Convention,3.802500009536743,4.882500171661377,True,1.806679534709782e-13,4.0,3.7986267028834164,4.640981911105811,3.7625,3.8025,4.322500000000001,4.8825,0.040000000000000036,0.5599999999999996 --dxfTGcXJoc/6,-dxfTGcXJoc,6,8,is,4.902500152587891,4.962500095367432,True,1.016744997961764e-15,0.25,4.882875855533999,4.9563961056449015,4.862500000000001,4.902500000000001,4.9225,4.9625,0.040000000000000036,0.040000000000000036 --dxfTGcXJoc/6,-dxfTGcXJoc,6,9,the,5.0625,5.162499904632568,True,1.3455526298201959e-13,3.0399529933929443,5.055186037952798,5.159575162330058,4.9625,5.062500000000001,5.1225000000000005,5.1625000000000005,0.10000000000000053,0.040000000000000036 --dxfTGcXJoc/6,-dxfTGcXJoc,6,10,primary,5.202499866485596,5.702499866485596,True,1.5114196718723875e-14,0.3414689898490906,5.2024999401486784,5.710515431236941,5.202500000000001,5.202500000000001,5.702500000000001,5.742500000000001,0.0,0.040000000000000036 --dxfTGcXJoc/6,-dxfTGcXJoc,6,11,means,5.802499771118164,6.142499923706055,True,4.23735550228628e-14,0.957328736782074,5.802486364345739,6.142863221968487,5.8025,5.8025,6.142500000000001,6.142500000000001,0.0,0.0 --dxfTGcXJoc/6,-dxfTGcXJoc,6,12,by,6.262499809265137,6.382500171661377,True,7.462917436806826e-12,4.0,6.262499999696703,6.382500000022064,6.2625,6.2625,6.3825,6.3825,0.0,0.0 --dxfTGcXJoc/6,-dxfTGcXJoc,6,13,which,6.422500133514404,6.682499885559082,True,4.42622826411776e-14,1.0,6.449507150222789,6.7000271550535855,6.4225,6.482500000000001,6.6825,6.7225,0.0600000000000005,0.040000000000000036 --dxfTGcXJoc/6,-dxfTGcXJoc,6,14,our,7.002500057220459,7.162499904632568,True,5.836931144583696e-14,1.3187144994735718,6.956397673938863,7.150806240348821,6.7225,7.022500000000001,7.102500000000001,7.1625000000000005,0.3000000000000007,0.05999999999999961 --dxfTGcXJoc/6,-dxfTGcXJoc,6,15,high-tech,7.222499847412109,7.662499904632568,True,1.0861458217201192e-12,4.0,7.2149935824394245,7.665882070120274,7.1625000000000005,7.2225,7.6625000000000005,7.702500000000001,0.05999999999999961,0.040000000000000036 --dxfTGcXJoc/6,-dxfTGcXJoc,6,16,companies,7.762499809265137,8.202500343322754,True,2.5332166919689314e-13,4.0,7.762376133681743,8.20258015845541,7.7625,7.7625,8.202499999999999,8.202499999999999,0.0,0.0 --dxfTGcXJoc/6,-dxfTGcXJoc,6,17,and,8.282500267028809,8.40250015258789,True,5.609055226036587e-14,1.2672313451766968,8.25984785590537,8.380906738814469,8.2225,8.282499999999999,8.362499999999999,8.4025,0.05999999999999872,0.040000000000000924 --dxfTGcXJoc/6,-dxfTGcXJoc,6,18,institutions,8.422499656677246,9.142499923706055,True,5.389259832399695e-15,0.25,8.422248950513739,9.142531347225114,8.4225,8.4225,9.1425,9.1425,0.0,0.0 --dxfTGcXJoc/6,-dxfTGcXJoc,6,19,can,9.242500305175781,9.5024995803833,True,2.1174656893472666e-15,0.25,9.282007274928727,9.511500731685478,9.1625,9.362499999999999,9.4825,9.5625,0.1999999999999993,0.08000000000000007 --dxfTGcXJoc/6,-dxfTGcXJoc,6,20,reach,9.5625,9.822500228881836,True,1.6722176960737127e-14,0.3777974247932434,9.569936347326685,9.826579649667691,9.5625,9.6425,9.8225,9.8825,0.08000000000000007,0.0600000000000005 --dxfTGcXJoc/6,-dxfTGcXJoc,6,21,out,9.882499694824219,10.1225004196167,True,3.801270076161413e-14,0.8588057160377502,9.905369645603065,10.128871358968683,9.8825,10.022499999999999,10.1225,10.1625,0.1399999999999988,0.03999999999999915 --dxfTGcXJoc/6,-dxfTGcXJoc,6,22,to,10.262499809265137,10.342499732971191,True,1.2812964393909415e-13,2.8947815895080566,10.262491452605754,10.342524144191376,10.2625,10.2625,10.3425,10.3425,0.0,0.0 --dxfTGcXJoc/6,-dxfTGcXJoc,6,23,the,10.422499656677246,10.522500038146973,True,1.0252761232240962e-14,0.25,10.420831128496536,10.52083710974172,10.4225,10.4225,10.522499999999999,10.522499999999999,0.0,0.0 --dxfTGcXJoc/6,-dxfTGcXJoc,6,24,global,10.542499542236328,10.90250015258789,True,4.665796625468767e-14,1.0541247129440308,10.54248245260101,10.903017817334318,10.5425,10.5425,10.9025,10.9025,0.0,0.0 --dxfTGcXJoc/6,-dxfTGcXJoc,6,25,scientific,10.942500114440918,11.582500457763672,True,1.1520418035607539e-14,0.260276198387146,10.943268176515302,11.582229395041422,10.942499999999999,10.942499999999999,11.5825,11.5825,0.0,0.0 --dxfTGcXJoc/6,-dxfTGcXJoc,6,26,community.,11.602499961853027,12.102499961853027,True,2.5937306230745805e-13,4.0,11.612190715637311,12.102458094905488,11.6025,11.6425,12.1025,12.1025,0.040000000000000924,0.0 --egA8-b7-3M/26,-egA8-b7-3M,26,0,We're,0.0024999999441206455,0.5824999809265137,True,2.7304946498274418e-11,4.0,0.04607508111870628,0.5898032740548333,0.0025000000000000005,0.5225,0.5824999999999999,0.6625,0.52,0.08000000000000007 --egA8-b7-3M/26,-egA8-b7-3M,26,1,updating,0.6025000214576721,1.1425000429153442,True,1.190343722028142e-12,4.0,0.6201202747881431,1.1412705985929916,0.6024999999999999,0.7025,1.1225,1.1624999999999999,0.10000000000000009,0.039999999999999813 --egA8-b7-3M/26,-egA8-b7-3M,26,2,it,1.2024999856948853,1.2625000476837158,True,6.882085098200777e-15,0.25,1.2068630134194995,1.2669326558135239,1.2025,1.2425,1.2625,1.3025,0.040000000000000036,0.040000000000000036 --egA8-b7-3M/26,-egA8-b7-3M,26,3,all,1.3224999904632568,1.5225000381469727,True,3.317236825397911e-14,1.0,1.3240528697525118,1.5232767925449109,1.3225,1.3225,1.5225,1.5225,0.0,0.0 --egA8-b7-3M/26,-egA8-b7-3M,26,4,the,1.5824999809265137,1.6825000047683716,True,1.9559788579532342e-15,0.25,1.5769041980110663,1.6835013931160456,1.5625,1.5825,1.6824999999999999,1.6824999999999999,0.020000000000000018,0.0 --egA8-b7-3M/26,-egA8-b7-3M,26,5,time,1.7024999856948853,1.9824999570846558,True,4.720274798845024e-16,0.25,1.7062997103515074,1.984997575047607,1.7025,1.7425,1.9825,2.0225,0.040000000000000036,0.040000000000000036 --egA8-b7-3M/26,-egA8-b7-3M,26,6,and,2.0225000381469727,2.5625,True,6.023966183732812e-15,0.25,2.0364141891598666,2.5625021914273565,2.0225,2.1825,2.5625,2.5625,0.16000000000000014,0.0 --egA8-b7-3M/26,-egA8-b7-3M,26,7,looking,2.5824999809265137,2.942500114440918,True,5.855222312859884e-14,1.7650902271270752,2.582682866295387,2.9398393089929113,2.5825,2.5825,2.9025,2.9425,0.0,0.040000000000000036 --egA8-b7-3M/26,-egA8-b7-3M,26,8,forward,3.002500057220459,3.3424999713897705,True,3.392760824073946e-15,0.25,2.999731412922151,3.3424460140552243,3.0025,3.0025,3.3425,3.3425,0.0,0.0 --egA8-b7-3M/26,-egA8-b7-3M,26,9,to,3.382499933242798,3.4625000953674316,True,1.8818388687613652e-14,0.5672910809516907,3.3825160972871147,3.462510902065862,3.3825,3.3825,3.4625,3.4625,0.0,0.0 --egA8-b7-3M/26,-egA8-b7-3M,26,10,your,3.5225000381469727,3.742500066757202,True,6.742193371796993e-15,0.25,3.522994713898922,3.743594339737526,3.5225,3.5225,3.7425,3.7425,0.0,0.0 --egA8-b7-3M/26,-egA8-b7-3M,26,11,comments,3.7825000286102295,4.302499771118164,True,6.467650850647266e-14,1.9497103691101074,3.78386669880374,4.305125915713463,3.7825,3.7825,4.3025,4.3025,0.0,0.0 --egA8-b7-3M/26,-egA8-b7-3M,26,12,on,4.462500095367432,4.5625,True,3.0199590658058773e-12,4.0,4.438194697536424,4.541530148943003,4.3425,4.4625,4.482500000000001,4.562500000000001,0.1200000000000001,0.08000000000000007 --egA8-b7-3M/26,-egA8-b7-3M,26,13,our,4.602499961853027,4.742499828338623,True,1.3194816766981532e-11,4.0,4.597614970972109,4.7378090732319125,4.5425,4.602500000000001,4.6825,4.742500000000001,0.0600000000000005,0.0600000000000005 --egA8-b7-3M/26,-egA8-b7-3M,26,14,videos.,4.882500171661377,5.242499828338623,True,7.06815682371964e-12,4.0,4.839578380641243,5.242501309845208,4.7225,4.8825,5.242500000000001,5.242500000000001,0.16000000000000014,0.0 --egA8-b7-3M/17,-egA8-b7-3M,17,0,As,0.6225000023841858,0.6825000047683716,True,6.329900796228638e-13,4.0,0.6225000000896067,0.682500000365255,0.6224999999999999,0.6224999999999999,0.6825,0.6825,0.0,0.0 --egA8-b7-3M/17,-egA8-b7-3M,17,1,you,0.7825000286102295,0.9424999952316284,True,1.412991631252053e-13,4.0,0.7823893755411854,0.9310866364147513,0.7825,0.7825,0.8825,0.9425,0.0,0.06000000000000005 --egA8-b7-3M/17,-egA8-b7-3M,17,2,have,0.9624999761581421,1.1024999618530273,True,5.60062928109048e-15,0.25,0.9529266344489182,1.098373411090721,0.9225,0.9624999999999999,1.0625,1.1225,0.039999999999999925,0.06000000000000005 --egA8-b7-3M/17,-egA8-b7-3M,17,3,more,1.1825000047683716,1.3424999713897705,True,7.51511771243012e-16,0.25,1.1824028515775171,1.3425010470509353,1.1824999999999999,1.1824999999999999,1.3425,1.3425,0.0,0.0 --egA8-b7-3M/17,-egA8-b7-3M,17,4,"experience,",1.3825000524520874,2.122499942779541,True,1.3858544574505555e-13,4.0,1.3873374469946451,2.1217125144118096,1.3825,1.4625,2.1225,2.1225,0.07999999999999985,0.0 --egA8-b7-3M/17,-egA8-b7-3M,17,5,you,3.2225000858306885,3.3424999713897705,True,3.083890429264255e-14,1.0576536655426025,3.213691251973658,3.354710556297301,3.2225,3.2225,3.3225000000000002,3.3825,0.0,0.05999999999999961 --egA8-b7-3M/17,-egA8-b7-3M,17,6,have,3.362499952316284,3.5425000190734863,True,3.8175747827697004e-14,1.3092786073684692,3.377375456438648,3.5414414297293204,3.3625,3.4025,3.5425,3.5425,0.040000000000000036,0.0 --egA8-b7-3M/17,-egA8-b7-3M,17,7,more,3.6624999046325684,3.802500009536743,True,4.685770594101265e-15,0.25,3.6478162339869873,3.7964527218527744,3.5825,3.6625,3.7625,3.8025,0.08000000000000007,0.040000000000000036 --egA8-b7-3M/17,-egA8-b7-3M,17,8,times,3.8424999713897705,4.182499885559082,True,1.295994798836738e-14,0.4444754421710968,3.8424998444900877,4.182500874910728,3.8425,3.8425,4.1825,4.1825,0.0,0.0 --egA8-b7-3M/17,-egA8-b7-3M,17,9,"exhibiting,",4.222499847412109,4.882500171661377,True,6.736042387940622e-14,2.3101987838745117,4.223205191074807,4.882471799434598,4.2225,4.2225,4.8825,4.8825,0.0,0.0 --egA8-b7-3M/17,-egA8-b7-3M,17,10,you,5.242499828338623,5.34250020980835,True,1.6752002473117609e-15,0.25,5.242488668737627,5.3432239190882544,5.242500000000001,5.242500000000001,5.3425,5.3425,0.0,0.0 --egA8-b7-3M/17,-egA8-b7-3M,17,11,get,5.402500152587891,5.522500038146973,True,2.7476793355765e-14,0.9423463940620422,5.402500228003155,5.522500551047494,5.402500000000001,5.402500000000001,5.522500000000001,5.522500000000001,0.0,0.0 --egA8-b7-3M/17,-egA8-b7-3M,17,12,to,5.582499980926514,5.642499923706055,True,4.209141343033008e-15,0.25,5.582587451647595,5.642588721621551,5.5825000000000005,5.5825000000000005,5.6425,5.6425,0.0,0.0 --egA8-b7-3M/17,-egA8-b7-3M,17,13,know,5.702499866485596,5.922500133514404,True,6.87243773174473e-14,2.3569769859313965,5.683751382141159,5.890393221205199,5.6625000000000005,5.702500000000001,5.822500000000001,5.9225,0.040000000000000036,0.09999999999999964 --egA8-b7-3M/17,-egA8-b7-3M,17,14,more,5.942500114440918,6.102499961853027,True,3.703195011110858e-15,0.25,5.942366821871721,6.103246214752875,5.942500000000001,5.942500000000001,6.102500000000001,6.102500000000001,0.0,0.0 --egA8-b7-3M/17,-egA8-b7-3M,17,15,people.,6.182499885559082,6.542500019073486,True,1.1336075036571386e-13,3.8878297805786133,6.182499922873765,6.542499989348836,6.1825,6.1825,6.5425,6.5425,0.0,0.0 --egA8-b7-3M/18,-egA8-b7-3M,18,0,It,0.5824999809265137,0.6825000047683716,True,5.045397490099392e-14,1.2702128887176514,0.4498708134808255,0.6283878986425523,0.0825,0.5824999999999999,0.6024999999999999,0.6825,0.4999999999999999,0.08000000000000007 --egA8-b7-3M/18,-egA8-b7-3M,18,1,becomes,0.7024999856948853,1.122499942779541,True,1.2237954891819707e-14,0.30809876322746277,0.6740202091094792,1.123904883788223,0.6625,0.7025,1.1225,1.1425,0.040000000000000036,0.020000000000000018 --egA8-b7-3M/18,-egA8-b7-3M,18,2,easier,1.1825000047683716,1.7424999475479126,True,5.1457912231397604e-15,0.25,1.2593575459889583,1.7659632994273018,1.1824999999999999,1.3825,1.7425,1.8225,0.20000000000000018,0.08000000000000007 --egA8-b7-3M/18,-egA8-b7-3M,18,3,at,1.8424999713897705,1.9824999570846558,True,1.3661030043733008e-13,3.439256429672241,1.8446638169367537,1.9840793573308473,1.8425,1.8425,1.9825,1.9825,0.0,0.0 --egA8-b7-3M/18,-egA8-b7-3M,18,4,each,2.182499885559082,2.362499952316284,True,2.2053683545694182e-14,0.555216372013092,2.175812096254957,2.353765489008425,2.0625,2.1825,2.3225,2.3625,0.1200000000000001,0.040000000000000036 --egA8-b7-3M/18,-egA8-b7-3M,18,5,one,2.4825000762939453,2.6024999618530273,True,8.226489693445582e-14,2.0710742473602295,2.465061924003497,2.5964168548924764,2.3625,2.4825,2.5625,2.6025,0.1200000000000001,0.040000000000000036 --egA8-b7-3M/18,-egA8-b7-3M,18,6,of,2.622499942779541,2.682499885559082,True,2.7406403223782273e-14,0.6899747252464294,2.6223798933822544,2.68237989421122,2.6225,2.6225,2.6825,2.6825,0.0,0.0 --egA8-b7-3M/18,-egA8-b7-3M,18,7,these,2.702500104904175,2.882499933242798,True,2.363750047882111e-15,0.25,2.702441638482025,2.882768890312429,2.7025,2.7025,2.8825,2.8825,0.0,0.0 --egA8-b7-3M/18,-egA8-b7-3M,18,8,conferences,2.942500114440918,3.6024999618530273,True,9.357525334024314e-14,2.3558201789855957,2.940330155669175,3.593531353090126,2.9025,2.9425,3.5825,3.6025,0.040000000000000036,0.020000000000000018 --egA8-b7-3M/18,-egA8-b7-3M,18,9,to,4.102499961853027,4.202499866485596,True,2.403003740002879e-13,4.0,4.10248789549808,4.202500336033287,4.1025,4.1025,4.202500000000001,4.202500000000001,0.0,0.0 --egA8-b7-3M/18,-egA8-b7-3M,18,10,connect,4.222499847412109,4.582499980926514,True,2.2258525589086836e-13,4.0,4.226862793204726,4.588976822861837,4.2225,4.2625,4.5825000000000005,4.6425,0.040000000000000036,0.05999999999999961 --egA8-b7-3M/18,-egA8-b7-3M,18,11,with,4.622499942779541,4.78249979019165,True,3.549643396124941e-15,0.25,4.643047295040439,4.802463991137171,4.6225000000000005,4.6625000000000005,4.782500000000001,4.822500000000001,0.040000000000000036,0.040000000000000036 --egA8-b7-3M/18,-egA8-b7-3M,18,12,people,4.882500171661377,5.162499904632568,True,1.767017623530414e-14,0.4448586106300354,4.882395800547012,5.162499794327169,4.8825,4.8825,5.1625000000000005,5.1625000000000005,0.0,0.0 --egA8-b7-3M/18,-egA8-b7-3M,18,13,that,5.202499866485596,5.362500190734863,True,5.594892829864539e-17,0.25,5.2024996957554865,5.3532616793556365,5.202500000000001,5.202500000000001,5.3425,5.362500000000001,0.0,0.020000000000000462 --egA8-b7-3M/18,-egA8-b7-3M,18,14,you've,5.382500171661377,5.602499961853027,True,1.3271654608626449e-11,4.0,5.382502593463899,5.602570477903483,5.3825,5.3825,5.602500000000001,5.602500000000001,0.0,0.0 --egA8-b7-3M/18,-egA8-b7-3M,18,15,met,5.682499885559082,5.882500171661377,True,1.9963176077497646e-13,4.0,5.679981733714091,5.879140283703421,5.6825,5.6825,5.8825,5.8825,0.0,0.0 --egA8-b7-3M/18,-egA8-b7-3M,18,16,or,6.422500133514404,6.482500076293945,True,7.505055469236507e-14,1.8894484043121338,6.397987073919746,6.459058711645056,6.4225,6.4225,6.482500000000001,6.482500000000001,0.0,0.0 --egA8-b7-3M/18,-egA8-b7-3M,18,17,that,6.522500038146973,6.662499904632568,True,7.683182416404072e-17,0.25,6.51310953711065,6.660509407784024,6.522500000000001,6.522500000000001,6.6625000000000005,6.6825,0.0,0.019999999999999574 --egA8-b7-3M/18,-egA8-b7-3M,18,18,you're,6.682499885559082,6.862500190734863,True,3.4061416881447926e-12,4.0,6.681564351164622,6.866491034969756,6.6825,6.702500000000001,6.862500000000001,6.8825,0.020000000000000462,0.019999999999999574 --egA8-b7-3M/18,-egA8-b7-3M,18,19,doing,6.902500152587891,7.142499923706055,True,2.8987788325317634e-14,0.7297871112823486,6.902497657128809,7.133894547298574,6.902500000000001,6.902500000000001,7.102500000000001,7.142500000000001,0.0,0.040000000000000036 --egA8-b7-3M/18,-egA8-b7-3M,18,20,business,7.182499885559082,7.5625,True,2.4658436913443244e-14,0.620792806148529,7.175063793795647,7.562567369568958,7.142500000000001,7.1825,7.562500000000001,7.562500000000001,0.03999999999999915,0.0 --egA8-b7-3M/18,-egA8-b7-3M,18,21,with.,7.622499942779541,7.882500171661377,True,1.9961424874148648e-11,4.0,7.622509877955194,7.882500128054946,7.6225000000000005,7.6225000000000005,7.8825,7.8825,0.0,0.0 --egA8-b7-3M/16,-egA8-b7-3M,16,0,"Third,",0.48249998688697815,0.762499988079071,True,1.2783299267217496e-14,0.45957401394844055,0.4823735110546779,0.765816467639421,0.4825,0.4825,0.7625,0.8225,0.0,0.06000000000000005 --egA8-b7-3M/16,-egA8-b7-3M,16,1,another,0.8424999713897705,1.2825000286102295,True,4.566552146731233e-14,1.6417269706726074,0.8410692456432085,1.2830330828196779,0.8225,0.8424999999999999,1.2825,1.3025,0.019999999999999907,0.020000000000000018 --egA8-b7-3M/16,-egA8-b7-3M,16,2,big,1.3224999904632568,1.4824999570846558,True,1.7119000038064505e-14,0.6154473423957825,1.3225007758015552,1.4825008899204788,1.3225,1.3225,1.4825,1.4825,0.0,0.0 --egA8-b7-3M/16,-egA8-b7-3M,16,3,benefit,1.5625,1.962499976158142,True,4.657146047385048e-14,1.674296498298645,1.5624781565144765,1.962500288652209,1.5625,1.5625,1.9625,1.9625,0.0,0.0 --egA8-b7-3M/16,-egA8-b7-3M,16,4,of,2.0225000381469727,2.1024999618530273,True,2.248744234171953e-14,0.808448851108551,2.022781738748026,2.097683776003884,2.0225,2.0225,2.0825,2.1025,0.0,0.020000000000000018 --egA8-b7-3M/16,-egA8-b7-3M,16,5,exhibiting,2.122499942779541,2.7225000858306885,True,2.7815540466096834e-14,1.0,2.1197486749478904,2.722499622656068,2.1025,2.1225,2.7225,2.7225,0.020000000000000018,0.0 --egA8-b7-3M/16,-egA8-b7-3M,16,6,is,2.822499990463257,2.882499933242798,True,7.896127192852029e-14,2.8387465476989746,2.822455644522566,2.8825844839545818,2.8225,2.8225,2.8825,2.8825,0.0,0.0 --egA8-b7-3M/16,-egA8-b7-3M,16,7,connecting,2.922499895095825,3.4825000762939453,True,5.372833745970066e-15,0.25,2.9224863158974808,3.4838534184456353,2.9225,2.9225,3.4625,3.5225,0.0,0.06000000000000005 --egA8-b7-3M/16,-egA8-b7-3M,16,8,with,3.502500057220459,3.6624999046325684,True,8.081755225572461e-16,0.25,3.5063061035173675,3.66635899435173,3.5025,3.5425,3.6625,3.7025,0.040000000000000036,0.040000000000000036 --egA8-b7-3M/16,-egA8-b7-3M,16,9,existing,3.742500066757202,4.302499771118164,True,7.100570131868267e-14,2.552734851837158,3.743222429243274,4.303965535822457,3.7425,3.7425,4.3025,4.3025,0.0,0.0 --egA8-b7-3M/16,-egA8-b7-3M,16,10,clients.,4.362500190734863,4.822500228881836,True,1.5700299133697415e-13,4.0,4.359248951566402,4.822504151992989,4.322500000000001,4.362500000000001,4.822500000000001,4.822500000000001,0.040000000000000036,0.0 --egA8-b7-3M/13,-egA8-b7-3M,13,0,What,0.24250000715255737,0.6225000023841858,True,1.5400974069637363e-16,0.25,0.2141840485714987,0.6218597133402548,0.0225,0.4225,0.6224999999999999,0.6224999999999999,0.39999999999999997,0.0 --egA8-b7-3M/13,-egA8-b7-3M,13,1,are,0.6424999833106995,0.7425000071525574,True,8.498745056231133e-14,2.449159622192383,0.6421815628124172,0.742500011758617,0.6425,0.6425,0.7424999999999999,0.7424999999999999,0.0,0.0 --egA8-b7-3M/13,-egA8-b7-3M,13,2,you,0.762499988079071,0.862500011920929,True,8.022830108047295e-15,0.25,0.7653580882059453,0.8659613972267409,0.7625,0.7825,0.8624999999999999,0.8825,0.020000000000000018,0.020000000000000018 --egA8-b7-3M/13,-egA8-b7-3M,13,3,doing,0.9024999737739563,1.122499942779541,True,2.871552483101579e-14,0.827521026134491,0.9025000213152364,1.1225003642958045,0.9025,0.9025,1.1225,1.1225,0.0,0.0 --egA8-b7-3M/13,-egA8-b7-3M,13,4,that's,1.1425000429153442,1.3624999523162842,True,1.606225569217301e-11,4.0,1.1429115027852526,1.3625002174895329,1.1425,1.1425,1.3625,1.3625,0.0,0.0 --egA8-b7-3M/13,-egA8-b7-3M,13,5,"different?""",1.3825000524520874,1.7825000286102295,True,1.846142698078406e-14,0.5320194959640503,1.4034251715517392,2.3733903913393863,1.3825,1.4224999999999999,1.7825,2.4425,0.039999999999999813,0.6599999999999999 --egA8-b7-3M/13,-egA8-b7-3M,13,6,They,1.8025000095367432,2.4625000953674316,True,1.3074539687669626e-14,0.3767807185649872,2.441006479437174,2.718606976840083,1.8025,2.5025,2.4825,2.7425,0.7,0.26000000000000023 --egA8-b7-3M/13,-egA8-b7-3M,13,7,always,2.502500057220459,2.7825000286102295,True,5.6516907988432216e-14,1.6286983489990234,2.7741362125960785,3.0562366014397764,2.5025,2.8025,2.7825,3.0825,0.30000000000000027,0.2999999999999998 --egA8-b7-3M/13,-egA8-b7-3M,13,8,want,2.802500009536743,2.9825000762939453,True,3.4700659636314676e-14,1.0,3.1022008047455936,3.3186257301717013,2.8025,3.2025,2.9825,3.4425,0.3999999999999999,0.45999999999999996 --egA8-b7-3M/13,-egA8-b7-3M,13,9,an,3.0625,3.122499942779541,True,3.821534492391525e-14,1.1012858152389526,3.4092592789422267,3.47028094392638,3.0625,3.4625,3.1225,3.5225,0.3999999999999999,0.3999999999999999 --egA8-b7-3M/13,-egA8-b7-3M,13,10,answer.,3.202500104904175,3.5625,True,1.833897183417532e-12,4.0,3.5131397249203156,3.9093662996538545,3.2025,3.5625,3.5625,4.0025,0.3599999999999999,0.4400000000000004 --egA8-b7-3M/1,-egA8-b7-3M,1,0,I,0.0024999999441206455,0.02250000089406967,True,3.349408424224709e-12,4.0,0.00807213853936062,0.02807213853936155,0.0025000000000000005,0.0825,0.0225,0.10250000000000001,0.08,0.08000000000000002 --egA8-b7-3M/1,-egA8-b7-3M,1,1,started,0.042500000447034836,0.30250000953674316,True,2.7094884495759697e-13,0.8343841433525085,0.08285976140362887,0.392640622001406,0.0425,0.6224999999999999,0.3025,1.6225,0.58,1.32 --egA8-b7-3M/1,-egA8-b7-3M,1,2,a,0.6225000023841858,0.6424999833106995,True,1.6140776215589625e-11,4.0,0.7018397959792573,0.7218397959792763,0.6224999999999999,1.7625,0.6425,1.7825,1.1400000000000001,1.1400000000000001 --egA8-b7-3M/1,-egA8-b7-3M,1,3,successful,0.762499988079071,1.622499942779541,True,4.594923345892926e-14,0.25,0.8340952262394151,1.6983804921435448,0.7025,1.8425,1.6225,2.7025,1.1400000000000001,1.08 --egA8-b7-3M/1,-egA8-b7-3M,1,4,Legal,1.8424999713897705,2.382499933242798,True,9.063408118632765e-13,2.791066884994507,1.909492493181274,2.4335311441149527,1.8425,2.7825,2.3825,3.1025,0.9400000000000002,0.7200000000000002 --egA8-b7-3M/1,-egA8-b7-3M,1,5,Nurse,2.4625000953674316,2.702500104904175,True,3.247291487356446e-13,1.0,2.5228978831850655,2.7700245247650632,2.4625,3.2025,2.7025,3.4625,0.7400000000000002,0.7599999999999998 --egA8-b7-3M/1,-egA8-b7-3M,1,6,Consulting,2.7825000286102295,3.4825000762939453,True,9.766556053475428e-13,3.007600784301758,2.8444628086268335,3.550414946085584,2.7825,3.5425,3.4625,4.562500000000001,0.7599999999999998,1.100000000000001 --egA8-b7-3M/1,-egA8-b7-3M,1,7,Business,3.5425000190734863,3.9825000762939453,True,1.635268933068354e-13,0.5035793781280518,3.6237951499738292,4.086650313197705,3.5425,4.702500000000001,3.9825,5.402500000000001,1.1600000000000006,1.4200000000000008 --egA8-b7-3M/1,-egA8-b7-3M,1,8,in,4.002500057220459,4.5625,True,9.467710767934942e-14,0.2915571630001068,4.122795613570893,4.643007217848893,4.0025,5.6225000000000005,4.562500000000001,5.6825,1.62,1.1199999999999992 --egA8-b7-3M/1,-egA8-b7-3M,1,9,1989.,nan,nan,False,0.0,nan,nan,nan,nan,nan,nan,nan,nan,nan --egA8-b7-3M/1,-egA8-b7-3M,1,10,I,4.702499866485596,4.722499847412109,True,3.378953340000754e-14,0.25,4.822565464327348,4.842565464327365,4.702500000000001,6.3825,4.7225,6.402500000000001,1.6799999999999997,1.6800000000000006 --egA8-b7-3M/1,-egA8-b7-3M,1,11,mentor,4.802499771118164,5.102499961853027,True,1.5290421923400133e-14,0.25,4.9231409745934025,5.229286423895843,4.8025,6.482500000000001,5.102500000000001,6.8425,1.6800000000000006,1.7399999999999993 --egA8-b7-3M/1,-egA8-b7-3M,1,12,nurses,5.142499923706055,5.402500152587891,True,3.649005231277317e-15,0.25,5.285193221719072,5.554316901085585,5.1425,6.902500000000001,5.402500000000001,7.3025,1.7600000000000007,1.8999999999999995 --egA8-b7-3M/1,-egA8-b7-3M,1,13,who,5.622499942779541,5.722499847412109,True,1.0704910807617096e-13,0.32965660095214844,5.754514660120223,5.858585417759601,5.6225000000000005,7.402500000000001,5.7225,7.522500000000001,1.7800000000000002,1.8000000000000007 --egA8-b7-3M/1,-egA8-b7-3M,1,14,want,6.382500171661377,6.682499885559082,True,5.1592024923052815e-12,4.0,6.4705962452594825,6.762408602745925,6.3825,7.562500000000001,6.6825,7.7625,1.1800000000000006,1.08 --egA8-b7-3M/1,-egA8-b7-3M,1,15,to,6.762499809265137,6.84250020980835,True,2.8021755922591485e-12,4.0,6.843815901061743,6.922242147418595,6.7625,7.8425,6.8425,7.902500000000001,1.08,1.0600000000000005 --egA8-b7-3M/1,-egA8-b7-3M,1,16,become,6.942500114440918,7.462500095367432,True,5.2748408939373714e-12,4.0,7.017877169431938,7.522635350083966,6.942500000000001,7.9225,7.4625,8.2425,0.9799999999999995,0.7799999999999994 --egA8-b7-3M/1,-egA8-b7-3M,1,17,Legal,7.5625,7.902500152587891,True,1.0792557711240824e-13,0.33235567808151245,7.620066755669658,7.950217895020635,7.562500000000001,8.3225,7.902500000000001,8.5425,0.7599999999999989,0.6399999999999997 --egA8-b7-3M/1,-egA8-b7-3M,1,18,Nurse,7.962500095367432,8.242500305175781,True,1.0314321011867245e-12,3.1762843132019043,8.00911242193168,8.283288744907443,7.9625,8.5825,8.2425,8.782499999999999,0.6199999999999992,0.5399999999999991 --egA8-b7-3M/1,-egA8-b7-3M,1,19,Consultants.,8.382499694824219,9.5024995803833,True,3.968895958411656e-12,4.0,8.410315918310687,9.492776884061083,8.3225,8.8225,9.4625,9.5025,0.5,0.03999999999999915 --egA8-b7-3M/6,-egA8-b7-3M,6,0,First,0.5224999785423279,0.8025000095367432,True,2.200081683132425e-15,0.25,0.4853864311485953,0.8069054596275058,0.2025,0.5225,0.8025,0.8624999999999999,0.31999999999999995,0.05999999999999994 --egA8-b7-3M/6,-egA8-b7-3M,6,1,exhibiting,0.8424999713897705,1.5625,True,3.04314916094086e-14,1.037160038948059,0.8581546005495158,1.5735363871558865,0.8424999999999999,1.0425,1.5625,1.6025,0.20000000000000007,0.040000000000000036 --egA8-b7-3M/6,-egA8-b7-3M,6,2,is,1.6425000429153442,1.722499966621399,True,2.2094691798802552e-13,4.0,1.6424968655880368,1.7224987665687466,1.6425,1.6425,1.7225,1.7225,0.0,0.0 --egA8-b7-3M/6,-egA8-b7-3M,6,3,a,1.8025000095367432,1.8224999904632568,True,1.2546567951243759e-11,4.0,1.8023980684775633,1.8223980684775658,1.8025,1.8025,1.8225,1.8225,0.0,0.0 --egA8-b7-3M/6,-egA8-b7-3M,6,4,wonderful,1.9424999952316284,2.4625000953674316,True,2.6952779811077916e-14,0.9185992479324341,1.8748230106996233,2.4290915945601004,1.8425,1.9425,2.3825,2.4625,0.09999999999999987,0.08000000000000007 --egA8-b7-3M/6,-egA8-b7-3M,6,5,opportunity,2.5425000190734863,3.202500104904175,True,1.6584008946381006e-14,0.5652128458023071,2.505562645229575,3.206492567731367,2.4625,2.5425,3.2025,3.2225,0.08000000000000007,0.020000000000000018 --egA8-b7-3M/6,-egA8-b7-3M,6,6,to,3.2825000286102295,3.382499933242798,True,4.802218396700829e-14,1.636682391166687,3.282497056715122,3.3825000470074538,3.2825,3.2825,3.3825,3.3825,0.0,0.0 --egA8-b7-3M/6,-egA8-b7-3M,6,7,network,3.4825000762939453,3.922499895095825,True,2.825085780274513e-14,0.9628400802612305,3.4783378131246514,3.9006160511864714,3.4225,3.4825,3.8625,3.9225,0.06000000000000005,0.06000000000000005 --egA8-b7-3M/6,-egA8-b7-3M,6,8,with,3.9625000953674316,4.122499942779541,True,5.249891572357314e-15,0.25,3.9591645135049784,4.119164923234471,3.9225,3.9625,4.0825000000000005,4.1225000000000005,0.040000000000000036,0.040000000000000036 --egA8-b7-3M/6,-egA8-b7-3M,6,9,other,4.262499809265137,4.502500057220459,True,3.9747078648148457e-14,1.354651927947998,4.241709003588393,4.488159328074618,4.1225000000000005,4.2625,4.442500000000001,4.5025,0.13999999999999968,0.05999999999999961 --egA8-b7-3M/6,-egA8-b7-3M,6,10,legal,4.602499961853027,4.922500133514404,True,2.4844702846676253e-14,0.8467521667480469,4.572833735083782,4.898411272791733,4.482500000000001,4.602500000000001,4.8425,4.9225,0.1200000000000001,0.08000000000000007 --egA8-b7-3M/6,-egA8-b7-3M,6,11,vendors.,4.962500095367432,5.442500114440918,True,5.481644191297416e-14,1.8682429790496826,4.962452113281357,5.442494524553728,4.9625,4.9625,5.442500000000001,5.442500000000001,0.0,0.0 --egA8-b7-3M/9,-egA8-b7-3M,9,0,"Secondly,",0.5625,1.0824999809265137,True,1.8873178844400207e-13,1.530295729637146,0.5556694643132206,1.0816803932159271,0.5625,0.5625,1.0825,1.0825,0.0,0.0 --egA8-b7-3M/9,-egA8-b7-3M,9,1,another,1.122499942779541,1.5824999809265137,True,1.2623711483691208e-13,1.0235695838928223,1.1289479746884983,1.585168118194489,1.1225,1.1225,1.5825,1.5825,0.0,0.0 --egA8-b7-3M/9,-egA8-b7-3M,9,2,goal,1.6825000047683716,1.8825000524520874,True,1.2042343305266462e-13,0.9764304161071777,1.6824995293756553,1.8825667309258272,1.6824999999999999,1.6824999999999999,1.8825,1.8825,0.0,0.0 --egA8-b7-3M/9,-egA8-b7-3M,9,3,of,1.9824999570846558,2.0425000190734863,True,9.055312055750164e-12,4.0,1.9823969628656442,2.0423972940717987,1.9825,1.9825,2.0425,2.0425,0.0,0.0 --egA8-b7-3M/9,-egA8-b7-3M,9,4,exhibiting,2.1024999618530273,2.622499942779541,True,2.0145135356413636e-14,0.25,2.102419345902239,2.6224487529212688,2.1025,2.1025,2.6225,2.6225,0.0,0.0 --egA8-b7-3M/9,-egA8-b7-3M,9,5,is,2.742500066757202,2.8424999713897705,True,2.4083781843819985e-12,4.0,2.742313009892268,2.8279796871804743,2.7425,2.7425,2.8025,2.8425,0.0,0.03999999999999959 --egA8-b7-3M/9,-egA8-b7-3M,9,6,building,2.862499952316284,3.2825000286102295,True,2.3681746938886833e-14,0.25,2.8559528332329007,3.282546562084778,2.8425,2.8625,3.2825,3.2825,0.020000000000000018,0.0 --egA8-b7-3M/9,-egA8-b7-3M,9,7,your,3.322499990463257,3.502500057220459,True,8.219796608502968e-15,0.25,3.322499735080081,3.5015646541237775,3.3225000000000002,3.3225000000000002,3.5025,3.5025,0.0,0.0 --egA8-b7-3M/9,-egA8-b7-3M,9,8,company,3.5225000381469727,3.9024999141693115,True,3.6006809513156046e-13,2.919543504714966,3.5224999329970728,3.9025043103914396,3.5225,3.5225,3.9025,3.9025,0.0,0.0 --egA8-b7-3M/9,-egA8-b7-3M,9,9,image.,4.042500019073486,4.302499771118164,True,5.5716044266033906e-15,0.25,4.064112624999909,4.345916642191695,4.0425,4.1025,4.3025,4.3825,0.05999999999999961,0.08000000000000007 --egA8-b7-3M/20,-egA8-b7-3M,20,0,Now,0.5824999809265137,0.7425000071525574,True,3.1301773916999134e-14,0.2761642634868622,0.4356619142255531,0.7065679669073096,0.0625,0.5824999999999999,0.6825,0.7424999999999999,0.5199999999999999,0.05999999999999994 --egA8-b7-3M/20,-egA8-b7-3M,20,1,you've,0.762499988079071,0.9624999761581421,True,1.005963715106084e-11,4.0,0.7493537559098281,0.9559724070717779,0.7424999999999999,0.7625,0.9425,0.9624999999999999,0.020000000000000018,0.019999999999999907 --egA8-b7-3M/20,-egA8-b7-3M,20,2,got,0.9825000166893005,1.1825000047683716,True,2.447966891585933e-14,0.25,0.9825000739198075,1.1663853893456297,0.9824999999999999,0.9824999999999999,1.1425,1.1824999999999999,0.0,0.039999999999999813 --egA8-b7-3M/20,-egA8-b7-3M,20,3,a,1.2024999856948853,1.222499966621399,True,5.193426851762828e-12,4.0,1.2024999656061082,1.2224999656061082,1.2025,1.2025,1.2225,1.2225,0.0,0.0 --egA8-b7-3M/20,-egA8-b7-3M,20,4,face,1.2424999475479126,1.5425000190734863,True,1.842966155119613e-13,1.6259825229644775,1.243189139356799,1.5429338149669567,1.2425,1.2425,1.5425,1.5425,0.0,0.0 --egA8-b7-3M/20,-egA8-b7-3M,20,5,that,1.6024999618530273,1.7825000286102295,True,4.151051823510308e-15,0.25,1.6025000546147912,1.782485139751137,1.6025,1.6025,1.7825,1.7825,0.0,0.0 --egA8-b7-3M/20,-egA8-b7-3M,20,6,you,1.8224999904632568,1.9225000143051147,True,2.3299396690012715e-15,0.25,1.8158877928657156,1.9213270670153828,1.8025,1.8225,1.9025,1.9224999999999999,0.020000000000000018,0.019999999999999796 --egA8-b7-3M/20,-egA8-b7-3M,20,7,can,1.962499976158142,2.0625,True,4.888492497086283e-13,4.0,1.9624941818187185,2.062500087680068,1.9625,1.9625,2.0625,2.0625,0.0,0.0 --egA8-b7-3M/20,-egA8-b7-3M,20,8,connect,2.1024999618530273,2.4625000953674316,True,1.8919876787221873e-13,1.6692323684692383,2.108301743869357,2.4709835100351327,2.1025,2.1425,2.4625,2.5225,0.040000000000000036,0.06000000000000005 --egA8-b7-3M/20,-egA8-b7-3M,20,9,with,2.5225000381469727,2.702500104904175,True,5.3128519548432e-15,0.25,2.5457953478717408,2.7183556023547792,2.5225,2.5825,2.7025,2.7425,0.06000000000000005,0.040000000000000036 --egA8-b7-3M/20,-egA8-b7-3M,20,10,a,2.7825000286102295,2.802500009536743,True,4.2030949033711185e-12,4.0,2.782499639676574,2.8024996396765736,2.7825,2.7825,2.8025,2.8025,0.0,0.0 --egA8-b7-3M/20,-egA8-b7-3M,20,11,"voice,",2.822499990463257,3.202500104904175,True,2.7150111586021763e-12,4.0,2.83914372742463,3.220260657530159,2.8225,2.8825,3.2025,3.2825,0.06000000000000005,0.08000000000000007 --egA8-b7-3M/20,-egA8-b7-3M,20,12,and,3.2825000286102295,4.022500038146973,True,1.7373433150013468e-13,1.5327953100204468,3.3491538445964393,4.026596308706412,3.2825,3.9425,4.022500000000001,4.062500000000001,0.6599999999999997,0.040000000000000036 --egA8-b7-3M/20,-egA8-b7-3M,20,13,that,4.122499942779541,4.28249979019165,True,4.251538560768285e-14,0.3750979006290436,4.110459146562859,4.271831829133859,4.0425,4.1225000000000005,4.2225,4.282500000000001,0.08000000000000007,0.0600000000000005 --egA8-b7-3M/20,-egA8-b7-3M,20,14,makes,4.302499771118164,4.502500057220459,True,9.645896006851146e-15,0.25,4.295467501888811,4.502881881025231,4.2625,4.3025,4.5025,4.5025,0.040000000000000036,0.0 --egA8-b7-3M/20,-egA8-b7-3M,20,15,you,4.542500019073486,4.682499885559082,True,3.1286988109871863e-14,0.27603378891944885,4.5424999966891395,4.682497906328179,4.5425,4.5425,4.6825,4.6825,0.0,0.0 --egA8-b7-3M/20,-egA8-b7-3M,20,16,closer,4.722499847412109,5.102499961853027,True,1.2777630245108113e-13,1.1273242235183716,4.722500016785279,5.102793700421638,4.7225,4.7225,5.102500000000001,5.102500000000001,0.0,0.0 --egA8-b7-3M/20,-egA8-b7-3M,20,17,to,5.202499866485596,5.302499771118164,True,9.8913234645049e-14,0.8726757764816284,5.202467187444825,5.302500007946147,5.202500000000001,5.202500000000001,5.3025,5.3025,0.0,0.0 --egA8-b7-3M/20,-egA8-b7-3M,20,18,that,5.362500190734863,5.5625,True,5.875642854202834e-13,4.0,5.356749432746811,5.56137750147641,5.322500000000001,5.362500000000001,5.562500000000001,5.562500000000001,0.040000000000000036,0.0 --egA8-b7-3M/20,-egA8-b7-3M,20,19,client.,5.582499980926514,6.002500057220459,True,8.170173522101254e-14,0.7208248972892761,5.582466544181751,6.002488319140519,5.5825000000000005,5.5825000000000005,6.0025,6.0025,0.0,0.0 --iRBcNs9oI8/3,-iRBcNs9oI8,3,0,"Well,",0.4424999952316284,0.6225000023841858,True,4.203285289272607e-12,1.5519766807556152,0.44251731066523176,0.6402426472765932,0.4425,0.4425,0.6224999999999999,0.7025,0.0,0.08000000000000007 --iRBcNs9oI8/3,-iRBcNs9oI8,3,1,it,0.9024999737739563,0.9825000166893005,True,1.378709565133876e-13,0.25,0.9026934341895801,0.9877443085068495,0.9025,0.9025,0.9824999999999999,1.0025,0.0,0.020000000000000018 --iRBcNs9oI8/3,-iRBcNs9oI8,3,2,is,1.162500023841858,1.2424999475479126,True,2.6363368546599222e-14,0.25,1.1766154327924332,1.258820351938083,1.1624999999999999,1.2225,1.2425,1.3025,0.06000000000000005,0.06000000000000005 --iRBcNs9oI8/3,-iRBcNs9oI8,3,3,the,1.9824999570846558,2.302500009536743,True,7.262065948587804e-12,2.681368589401245,1.9861770102307585,2.318400811512359,1.9825,1.9825,2.3025,2.5425,0.0,0.23999999999999977 --iRBcNs9oI8/3,-iRBcNs9oI8,3,4,secret,3.322499990463257,3.622499942779541,True,1.9209831208372163e-12,0.7092835307121277,3.1189257501802254,3.604293380599604,2.6225,3.3225000000000002,3.5825,3.6225,0.7000000000000002,0.040000000000000036 --iRBcNs9oI8/3,-iRBcNs9oI8,3,5,of,3.7225000858306885,4.102499961853027,True,2.4477631293401414e-12,0.9037861824035645,3.7260529538165423,4.095743694350303,3.7225,3.7225,4.1025,4.1025,0.0,0.0 --iRBcNs9oI8/3,-iRBcNs9oI8,3,6,power,4.402500152587891,4.902500152587891,True,4.5697900324936924e-11,4.0,4.409120587918154,4.902042298636173,4.402500000000001,4.402500000000001,4.902500000000001,4.902500000000001,0.0,0.0 --iRBcNs9oI8/3,-iRBcNs9oI8,3,7,pose,5.042500019073486,5.382500171661377,True,2.968922850621336e-12,1.096213698387146,5.047806403743758,5.364777216140973,5.0425,5.102500000000001,5.2225,5.3825,0.0600000000000005,0.16000000000000014 --iRBcNs9oI8/7,-iRBcNs9oI8,7,0,"Well,",0.10249999910593033,0.36250001192092896,True,2.920177391996931e-13,3.763028383255005,0.10136593814621651,0.3623925371058929,0.10250000000000001,0.10250000000000001,0.3625,0.3625,0.0,0.0 --iRBcNs9oI8/7,-iRBcNs9oI8,7,1,for,1.3224999904632568,1.4424999952316284,True,7.760179082444071e-14,1.0,0.9651913170585473,1.426231262055861,0.4425,1.3225,1.4025,1.4425,0.88,0.039999999999999813 --iRBcNs9oI8/7,-iRBcNs9oI8,7,2,"starters,",1.4824999570846558,1.9424999952316284,True,7.344413299097477e-14,0.9464231729507446,1.482722124857738,1.9316510145653845,1.4825,1.4825,1.8825,1.9425,0.0,0.05999999999999983 --iRBcNs9oI8/7,-iRBcNs9oI8,7,3,let's,1.9824999570846558,2.5625,True,5.298965259636912e-12,4.0,1.9825266210685708,2.562499980618171,1.9825,1.9825,2.5625,2.5625,0.0,0.0 --iRBcNs9oI8/7,-iRBcNs9oI8,7,4,look,2.622499942779541,2.882499933242798,True,8.900332185667048e-14,1.146923542022705,2.621435781036787,2.883659047511814,2.6225,2.6225,2.8825,2.9025,0.0,0.020000000000000018 --iRBcNs9oI8/7,-iRBcNs9oI8,7,5,at,2.9825000762939453,3.0625,True,3.4943981708874736e-14,0.45029863715171814,2.9829116244373175,3.062499663832645,2.9825,2.9825,3.0625,3.0625,0.0,0.0 --iRBcNs9oI8/7,-iRBcNs9oI8,7,6,the,3.1624999046325684,3.322499990463257,True,1.0356679977594624e-13,1.3345929384231567,3.156277465682998,3.3100716739224545,3.1225,3.1625,3.2425,3.3225000000000002,0.040000000000000036,0.08000000000000007 --iRBcNs9oI8/7,-iRBcNs9oI8,7,7,word,3.3424999713897705,3.682499885559082,True,3.161334693983363e-15,0.25,3.3424933417526446,3.682494353615535,3.3425,3.3425,3.6825,3.6825,0.0,0.0 --iRBcNs9oI8/7,-iRBcNs9oI8,7,8,"""power""",3.702500104904175,4.002500057220459,True,2.9010224534024506e-14,0.3738344609737396,3.7025010532407543,3.9910909636389107,3.7025,3.7025,3.9625,4.0025,0.0,0.04000000000000048 --iRBcNs9oI8/6,-iRBcNs9oI8,6,0,What,0.042500000447034836,0.2224999964237213,True,6.827441173182236e-13,1.0,0.05154200673577662,0.2727785157094661,0.0425,0.0825,0.2225,0.3025,0.04,0.07999999999999999 --iRBcNs9oI8/6,-iRBcNs9oI8,6,1,is,0.4625000059604645,0.6025000214576721,True,1.1234021118954399e-13,0.25,0.4747218729776408,0.5963319673877671,0.4625,0.5225,0.5425,0.6024999999999999,0.05999999999999994,0.05999999999999994 --iRBcNs9oI8/6,-iRBcNs9oI8,6,2,a,0.7425000071525574,0.762499988079071,True,2.809957263616783e-14,0.25,0.7333161148797499,0.7533161148798755,0.6825,0.7424999999999999,0.7025,0.7625,0.05999999999999994,0.05999999999999994 --iRBcNs9oI8/6,-iRBcNs9oI8,6,3,power,0.9825000166893005,1.722499966621399,True,3.0594309637782535e-12,4.0,0.9841119228812493,1.722488496427188,0.9824999999999999,0.9824999999999999,1.7225,1.7225,0.0,0.0 --iRBcNs9oI8/6,-iRBcNs9oI8,6,4,pose,2.1024999618530273,2.6024999618530273,True,4.7897163665822085e-12,4.0,2.1029123141162605,2.5993707527881207,2.0625,2.1025,2.5825,2.6025,0.040000000000000036,0.020000000000000018 --iRBcNs9oI8/9,-iRBcNs9oI8,9,0,Power,0.0024999999441206455,0.2224999964237213,True,8.225095646620991e-15,0.25,0.006262492974741897,0.22425165857230403,0.0025000000000000005,0.0225,0.2225,0.2225,0.019999999999999997,0.0 --iRBcNs9oI8/9,-iRBcNs9oI8,9,1,is,0.2824999988079071,0.3425000011920929,True,4.88303009138491e-11,4.0,0.2828602076691416,0.3461376424479182,0.28250000000000003,0.28250000000000003,0.3425,0.3425,0.0,0.0 --iRBcNs9oI8/9,-iRBcNs9oI8,9,2,similar,1.3025000095367432,1.722499966621399,True,1.3116465277459872e-14,0.25,1.1245273514934184,1.7144200210143659,0.4625,1.3025,1.7025,1.7425,0.84,0.040000000000000036 --iRBcNs9oI8/9,-iRBcNs9oI8,9,3,to,1.7424999475479126,1.8025000095367432,True,3.081003117563763e-12,4.0,1.7386692485023425,1.7996332226989926,1.7225,1.7625,1.7825,1.8225,0.040000000000000036,0.040000000000000036 --iRBcNs9oI8/9,-iRBcNs9oI8,9,4,strength,1.9225000143051147,2.5824999809265137,True,4.50202212749079e-13,1.0,1.8981114999728592,2.5831794475236496,1.8025,1.9425,2.5825,2.5825,0.1399999999999999,0.0 --iRBcNs9oI8/8,-iRBcNs9oI8,8,0,I've,0.08250000327825546,0.24250000715255737,True,1.9600367336114477e-12,4.0,0.08247995998981052,0.24164600371421696,0.0825,0.0825,0.2425,0.2425,0.0,0.0 --iRBcNs9oI8/8,-iRBcNs9oI8,8,1,drawn,0.32249999046325684,0.6625000238418579,True,1.3570146525573867e-12,4.0,0.3229530278849659,0.6657272327837613,0.3225,0.3225,0.6625,0.7025,0.0,0.040000000000000036 --iRBcNs9oI8/8,-iRBcNs9oI8,8,2,this,1.0225000381469727,1.3424999713897705,True,7.521722367133041e-14,0.3343006670475006,1.0222614949808086,1.342502502681455,1.0225,1.0225,1.3425,1.3425,0.0,0.0 --iRBcNs9oI8/8,-iRBcNs9oI8,8,3,man,1.5225000381469727,1.6825000047683716,True,7.045138262920872e-14,0.3131190240383148,1.5236198190614774,1.6824829413710227,1.5225,1.5425,1.6824999999999999,1.6824999999999999,0.020000000000000018,0.0 --iRBcNs9oI8/8,-iRBcNs9oI8,8,4,"here,",1.902500033378601,2.0824999809265137,True,2.3500652988829758e-14,0.25,1.894543622342994,2.0867907583195966,1.7025,1.9825,2.0425,2.2025,0.28,0.16000000000000014 --iRBcNs9oI8/8,-iRBcNs9oI8,8,5,and,2.122499942779541,2.262500047683716,True,2.832734047331087e-13,1.2590000629425049,2.1331121793088736,2.2719190723194225,2.1225,2.2825,2.2625,2.3825,0.16000000000000014,0.11999999999999966 --iRBcNs9oI8/8,-iRBcNs9oI8,8,6,if,2.322499990463257,2.382499933242798,True,5.582629085572333e-13,2.48118257522583,2.33868003750859,2.4031823336609714,2.2825,2.5625,2.3825,2.6425,0.2799999999999998,0.26000000000000023 --iRBcNs9oI8/8,-iRBcNs9oI8,8,7,you,2.4825000762939453,2.6424999237060547,True,9.512268766718665e-14,0.4227698743343353,2.5072316046245557,2.6582997433161406,2.4825,2.7425,2.6425,2.8425,0.26000000000000023,0.19999999999999973 --iRBcNs9oI8/8,-iRBcNs9oI8,8,8,can,2.742500066757202,2.8424999713897705,True,4.3768065343882667e-13,1.945258378982544,2.75386187499682,2.937324736774701,2.7425,2.8825,2.8425,4.0425,0.13999999999999968,1.2000000000000006 --iRBcNs9oI8/8,-iRBcNs9oI8,8,9,"tell,",2.882499933242798,4.082499980926514,True,2.2499873058440256e-13,1.0,2.980365531712314,4.098930060097728,2.8825,4.1225000000000005,4.0825000000000005,4.282500000000001,1.2400000000000007,0.20000000000000018 --iRBcNs9oI8/8,-iRBcNs9oI8,8,10,he,4.122499942779541,4.182499885559082,True,4.699343873564542e-14,0.25,4.143350252178951,4.2046936964374835,4.1025,4.402500000000001,4.1825,4.4625,0.3000000000000007,0.28000000000000025 --iRBcNs9oI8/8,-iRBcNs9oI8,8,11,has,4.222499847412109,4.34250020980835,True,1.2339205991609287e-13,0.5484122633934021,4.245734427287916,4.369364316926948,4.2225,4.522500000000001,4.3425,4.6825,0.3000000000000007,0.33999999999999986 --iRBcNs9oI8/8,-iRBcNs9oI8,8,12,a,4.402500152587891,4.422500133514404,True,4.446784954148519e-12,4.0,4.431854037932112,4.451854037932103,4.402500000000001,4.742500000000001,4.4225,4.7625,0.33999999999999986,0.33999999999999986 --iRBcNs9oI8/8,-iRBcNs9oI8,8,13,lot,4.522500038146973,4.682499885559082,True,2.9134436833541666e-14,0.25,4.5482175681919905,4.7054606013575935,4.522500000000001,4.8425,4.6825,4.9625,0.3199999999999994,0.28000000000000025 --iRBcNs9oI8/8,-iRBcNs9oI8,8,14,of,4.742499828338623,4.802499771118164,True,5.46444290031446e-15,0.25,4.767774255389696,4.82777455421578,4.742500000000001,5.062500000000001,4.8025,5.1225000000000005,0.3200000000000003,0.3200000000000003 --iRBcNs9oI8/8,-iRBcNs9oI8,8,15,big,4.84250020980835,4.962500095367432,True,2.147364317611755e-12,4.0,4.875985463534146,5.002288285727535,4.8425,5.202500000000001,4.9625,5.3425,0.3600000000000003,0.3799999999999999 --iRBcNs9oI8/8,-iRBcNs9oI8,8,16,"muscles,",5.0625,5.462500095367432,True,1.9685501397915563e-14,0.25,5.087760129561801,5.490328924230847,5.062500000000001,5.3825,5.4625,5.8025,0.3199999999999994,0.33999999999999986 --iRBcNs9oI8/8,-iRBcNs9oI8,8,17,he,5.682499885559082,5.802499771118164,True,2.0166227628765077e-12,4.0,5.678916934830031,5.797729507728853,5.6225000000000005,5.862500000000001,5.702500000000001,5.9225,0.2400000000000002,0.21999999999999975 --iRBcNs9oI8/8,-iRBcNs9oI8,8,18,looks,6.502500057220459,6.762499809265137,True,4.851144984850675e-13,2.156076669692993,6.49249963470516,6.761737275706995,6.5025,6.5025,6.7625,6.7625,0.0,0.0 --iRBcNs9oI8/8,-iRBcNs9oI8,8,19,very,7.202499866485596,7.402500152587891,True,6.853084722965863e-13,3.045832633972168,7.2021361104523285,7.402531057662287,7.202500000000001,7.202500000000001,7.402500000000001,7.402500000000001,0.0,0.0 --iRBcNs9oI8/8,-iRBcNs9oI8,8,20,strong,7.602499961853027,8.0024995803833,True,4.99631972350912e-14,0.25,7.602283377792524,8.002472983869318,7.602500000000001,7.602500000000001,8.0025,8.0025,0.0,0.0 --lzEya4AM_4/5,-lzEya4AM_4,5,0,If,0.5224999785423279,0.5824999809265137,True,3.035739655531458e-14,0.25,0.5224777847512705,0.5825087523727438,0.5225,0.5225,0.5824999999999999,0.5824999999999999,0.0,0.0 --lzEya4AM_4/5,-lzEya4AM_4,5,1,it,0.6625000238418579,0.7425000071525574,True,9.317088658748751e-14,0.5512282848358154,0.6439698113695347,0.7142330631919445,0.6224999999999999,0.6625,0.6825,0.7424999999999999,0.040000000000000036,0.05999999999999994 --lzEya4AM_4/5,-lzEya4AM_4,5,2,falls,0.762499988079071,1.0225000381469727,True,1.690241371345158e-13,1.0,0.7456461893744665,1.0056523214029987,0.7224999999999999,0.7625,0.9824999999999999,1.0225,0.040000000000000036,0.040000000000000036 --lzEya4AM_4/5,-lzEya4AM_4,5,3,into,1.0824999809265137,1.2625000476837158,True,9.029643623526679e-14,0.5342221260070801,1.06263615289812,1.2547635900885998,1.0225,1.0825,1.1624999999999999,1.2625,0.06000000000000005,0.10000000000000009 --lzEya4AM_4/5,-lzEya4AM_4,5,4,oh,1.2825000286102295,1.3424999713897705,True,5.106823641807916e-14,0.30213576555252075,1.3017148062167647,1.3783215908484356,1.1824999999999999,1.3825,1.2625,1.4625,0.20000000000000018,0.19999999999999996 --lzEya4AM_4/5,-lzEya4AM_4,5,5,any,1.3825000524520874,1.4824999570846558,True,2.4951281275484294e-13,1.4761962890625,1.416671421638377,1.5684959034922972,1.2825,1.5025,1.4625,1.7425,0.21999999999999997,0.28 --lzEya4AM_4/5,-lzEya4AM_4,5,6,of,1.6425000429153442,1.7424999475479126,True,2.3230219831082977e-11,4.0,1.6744825900566362,1.7571266553083897,1.6425,1.7825,1.7425,1.8425,0.1399999999999999,0.10000000000000009 --lzEya4AM_4/5,-lzEya4AM_4,5,7,those,1.8025000095367432,2.0425000190734863,True,3.8556565709266244e-13,2.281127691268921,1.813751078471044,2.042598142283778,1.8025,1.8625,2.0425,2.0425,0.06000000000000005,0.0 --lzEya4AM_4/5,-lzEya4AM_4,5,8,three,2.0824999809265137,2.2825000286102295,True,9.28581078132526e-14,0.5493777990341187,2.082500668233339,2.282500675241747,2.0825,2.0825,2.2825,2.2825,0.0,0.0 --lzEya4AM_4/5,-lzEya4AM_4,5,9,"categories,",2.322499990463257,2.9024999141693115,True,7.862823212618705e-14,0.4651893675327301,2.3225014444100087,2.9024997494292215,2.3225,2.3225,2.9025,2.9025,0.0,0.0 --lzEya4AM_4/5,-lzEya4AM_4,5,10,inducing,3.6424999237060547,4.202499866485596,True,1.9956248025615464e-12,4.0,3.6424999115902814,4.202500006501488,3.6425,3.6425,4.202500000000001,4.202500000000001,0.0,0.0 --lzEya4AM_4/5,-lzEya4AM_4,5,11,nausea,4.262499809265137,5.382500171661377,True,1.1790844993073146e-12,4.0,4.463467536769676,5.383299142343135,4.2625,5.022500000000001,5.3825,5.3825,0.7600000000000007,0.0 --lzEya4AM_4/5,-lzEya4AM_4,5,12,and,5.422500133514404,5.542500019073486,True,8.983205347125323e-13,4.0,5.424328417539918,5.544325310866087,5.4225,5.4225,5.5425,5.5425,0.0,0.0 --lzEya4AM_4/5,-lzEya4AM_4,5,13,vomiting,5.5625,5.982500076293945,True,5.396987652790675e-13,3.1930277347564697,5.576995124703589,5.9820157407403665,5.562500000000001,5.602500000000001,5.982500000000001,5.982500000000001,0.040000000000000036,0.0 --lzEya4AM_4/5,-lzEya4AM_4,5,14,would,6.022500038146973,6.382500171661377,True,4.5605273707840024e-14,0.2698151469230652,6.023217173328293,6.409607625661401,6.022500000000001,6.022500000000001,6.3825,6.4225,0.0,0.040000000000000036 --lzEya4AM_4/5,-lzEya4AM_4,5,15,be,6.402500152587891,6.462500095367432,True,7.951032101427113e-16,0.25,6.483258350281619,6.549422500484275,6.402500000000001,6.522500000000001,6.4625,6.602500000000001,0.1200000000000001,0.14000000000000057 --lzEya4AM_4/5,-lzEya4AM_4,5,16,your,6.502500057220459,6.642499923706055,True,8.889075456611217e-15,0.25,6.592861811750548,6.7463621054641605,6.482500000000001,6.642500000000001,6.6225000000000005,6.8025,0.16000000000000014,0.17999999999999972 --lzEya4AM_4/5,-lzEya4AM_4,5,17,next,6.682499885559082,6.822500228881836,True,8.763239699866032e-13,4.0,6.774462248977959,6.919159147895202,6.642500000000001,6.862500000000001,6.8025,7.0425,0.21999999999999975,0.2400000000000002 --lzEya4AM_4/5,-lzEya4AM_4,5,18,step.,6.862500190734863,7.102499961853027,True,8.070761398602799e-13,4.0,6.9531891126610725,7.268405006346323,6.862500000000001,7.0825000000000005,7.102500000000001,7.522500000000001,0.21999999999999975,0.41999999999999993 --lzEya4AM_4/6,-lzEya4AM_4,6,0,If,0.6225000023841858,0.7024999856948853,True,3.9581296682085487e-13,4.0,0.6218706464646045,0.7023365326741986,0.6224999999999999,0.6224999999999999,0.7025,0.7025,0.0,0.0 --lzEya4AM_4/6,-lzEya4AM_4,6,1,the,0.7425000071525574,0.8424999713897705,True,7.399572254029266e-15,0.4287492334842682,0.7424768243763704,0.8424768481110348,0.7424999999999999,0.7424999999999999,0.8424999999999999,0.8424999999999999,0.0,0.0 --lzEya4AM_4/6,-lzEya4AM_4,6,2,product,0.862500011920929,1.2424999475479126,True,1.7258508058543183e-14,1.0,0.8624984023485787,1.2425003773706746,0.8624999999999999,0.8624999999999999,1.2425,1.2425,0.0,0.0 --lzEya4AM_4/6,-lzEya4AM_4,6,3,or,1.2825000286102295,1.6024999618530273,True,2.486088049834245e-13,4.0,1.282676981052881,1.6025512390288499,1.2825,1.2825,1.6025,1.6025,0.0,0.0 --lzEya4AM_4/6,-lzEya4AM_4,6,4,poison,1.662500023841858,2.1024999618530273,True,4.366728604144471e-14,2.530189037322998,1.6673157302049542,2.0989654347339073,1.6625,1.7225,2.0625,2.1025,0.05999999999999983,0.040000000000000036 --lzEya4AM_4/6,-lzEya4AM_4,6,5,is,2.202500104904175,2.262500047683716,True,8.725329588346858e-15,0.5055668354034424,2.180319198328119,2.2460606071930846,2.1425,2.2025,2.2225,2.2625,0.06000000000000005,0.040000000000000036 --lzEya4AM_4/6,-lzEya4AM_4,6,6,some,2.2825000286102295,2.442500114440918,True,2.255789346007446e-15,0.25,2.278221478596384,2.4349226931964756,2.2625,2.2825,2.4225,2.4425,0.020000000000000018,0.020000000000000018 --lzEya4AM_4/6,-lzEya4AM_4,6,7,type,2.4625000953674316,2.682499885559082,True,1.0200491167879078e-13,4.0,2.462554132308005,2.682496700492244,2.4625,2.4625,2.6825,2.6825,0.0,0.0 --lzEya4AM_4/6,-lzEya4AM_4,6,8,of,2.702500104904175,2.762500047683716,True,5.058627467109146e-14,2.9310920238494873,2.7039424007353188,2.7639755466185556,2.7025,2.7025,2.7625,2.7625,0.0,0.0 --lzEya4AM_4/6,-lzEya4AM_4,6,9,petroleum,2.882499933242798,3.3424999713897705,True,4.413881640828038e-13,4.0,2.8775856658907264,3.3593962724351547,2.8225,2.8825,3.3425,3.4225,0.06000000000000005,0.08000000000000007 --lzEya4AM_4/6,-lzEya4AM_4,6,10,product,3.4024999141693115,3.822499990463257,True,5.6658426865127676e-14,3.2829272747039795,3.4179361032192093,3.8208257166363166,3.4025,3.4425,3.8225000000000002,3.8225000000000002,0.040000000000000036,0.0 --lzEya4AM_4/6,-lzEya4AM_4,6,11,or,4.222499847412109,4.302499771118164,True,2.7757481439760236e-14,1.608336091041565,4.12428872001621,4.2612516688364535,3.8825,4.2225,4.242500000000001,4.3025,0.3400000000000003,0.05999999999999961 --lzEya4AM_4/6,-lzEya4AM_4,6,12,corrosive,4.362500190734863,4.84250020980835,True,4.3797563774490567e-13,4.0,4.329747394910065,4.842412625596829,4.3025,4.362500000000001,4.8425,4.8425,0.0600000000000005,0.0 --lzEya4AM_4/6,-lzEya4AM_4,6,13,"product,",4.862500190734863,5.262499809265137,True,3.187660435632379e-14,1.8470081090927124,4.862499669555491,5.262370885994928,4.862500000000001,4.862500000000001,5.2625,5.2625,0.0,0.0 --lzEya4AM_4/6,-lzEya4AM_4,6,14,you,5.802499771118164,5.902500152587891,True,1.5641947796290719e-15,0.25,5.53509435686845,5.867162990568692,5.322500000000001,5.8025,5.862500000000001,5.902500000000001,0.47999999999999954,0.040000000000000036 --lzEya4AM_4/6,-lzEya4AM_4,6,15,would,5.922500133514404,6.122499942779541,True,1.0120089614679573e-14,0.5863826274871826,5.922112572905214,6.122047150371503,5.9225,5.9225,6.1225000000000005,6.1225000000000005,0.0,0.0 --lzEya4AM_4/6,-lzEya4AM_4,6,16,not,6.142499923706055,6.262499809265137,True,6.352139781784071e-15,0.368058443069458,6.142500764751273,6.2625701809161365,6.142500000000001,6.142500000000001,6.2625,6.2625,0.0,0.0 --lzEya4AM_4/6,-lzEya4AM_4,6,17,attempt,6.302499771118164,6.822500228881836,True,1.9684304540361092e-15,0.25,6.318155035522648,6.821948412854423,6.3025,6.4625,6.822500000000001,6.822500000000001,0.16000000000000014,0.0 --lzEya4AM_4/6,-lzEya4AM_4,6,18,to,7.182499885559082,7.28249979019165,True,1.797134727002988e-14,1.0413036346435547,7.182534654775597,7.28252803343239,7.1825,7.1825,7.282500000000001,7.282500000000001,0.0,0.0 --lzEya4AM_4/6,-lzEya4AM_4,6,19,induce,7.382500171661377,7.922500133514404,True,4.838478183106891e-14,2.803532123565674,7.414923567572577,7.934817600865357,7.3825,7.5025,7.9225,7.9625,0.1200000000000001,0.040000000000000036 --lzEya4AM_4/6,-lzEya4AM_4,6,20,vomiting,7.962500095367432,8.382499694824219,True,8.089727889307174e-13,4.0,7.989677049757497,8.384180167319787,7.9625,8.0025,8.3825,8.3825,0.03999999999999915,0.0 --lzEya4AM_4/6,-lzEya4AM_4,6,21,and,8.602499961853027,8.702500343322754,True,7.461027882484355e-15,0.4323101341724396,8.558395721540947,8.70051005570173,8.4225,8.6025,8.6825,8.7025,0.17999999999999972,0.02000000000000135 --lzEya4AM_4/6,-lzEya4AM_4,6,22,"nausea,",8.72249984741211,9.142499923706055,True,1.0365191344119395e-11,4.0,8.722975493432113,9.139562814034488,8.7225,8.7225,9.1225,9.1425,0.0,0.019999999999999574 --lzEya4AM_4/6,-lzEya4AM_4,6,23,as,9.642499923706055,9.702500343322754,True,8.344037537733745e-14,4.0,9.641942999273425,9.701962157826868,9.6425,9.6425,9.7025,9.7025,0.0,0.0 --lzEya4AM_4/6,-lzEya4AM_4,6,24,as,9.762499809265137,9.822500228881836,True,5.40865399342727e-12,4.0,9.762383360924126,9.822383364858918,9.7625,9.7625,9.8225,9.8225,0.0,0.0 --lzEya4AM_4/6,-lzEya4AM_4,6,25,the,9.842499732971191,9.942500114440918,True,6.742547008052472e-15,0.39067959785461426,9.842500125440687,9.942500469035092,9.8425,9.8425,9.942499999999999,9.942499999999999,0.0,0.0 --lzEya4AM_4/6,-lzEya4AM_4,6,26,product,10.0024995803833,10.342499732971191,True,2.207761392052001e-14,1.2792307138442993,9.999605801336743,10.338683442149089,9.9625,10.0025,10.282499999999999,10.3425,0.03999999999999915,0.0600000000000005 --lzEya4AM_4/6,-lzEya4AM_4,6,27,burned,10.362500190734863,10.682499885559082,True,1.995170183038096e-14,1.156050205230713,10.362784650428713,10.68227166700739,10.362499999999999,10.362499999999999,10.6825,10.6825,0.0,0.0 --lzEya4AM_4/6,-lzEya4AM_4,6,28,on,10.702500343322754,10.782500267028809,True,2.3671003850610217e-13,4.0,10.702523528497984,10.782508642676058,10.7025,10.7025,10.782499999999999,10.782499999999999,0.0,0.0 --lzEya4AM_4/6,-lzEya4AM_4,6,29,the,10.822500228881836,10.922499656677246,True,9.76079348504735e-15,0.5655641555786133,10.823841751296246,10.923854219050918,10.8225,10.8425,10.9225,10.942499999999999,0.019999999999999574,0.019999999999999574 --lzEya4AM_4/6,-lzEya4AM_4,6,30,way,11.0024995803833,11.1225004196167,True,9.980518066729852e-15,0.5782955288887024,10.97704504414781,11.089484271552267,10.942499999999999,11.0025,11.0625,11.1225,0.0600000000000005,0.0600000000000005 --lzEya4AM_4/6,-lzEya4AM_4,6,31,down,11.142499923706055,11.382499694824219,True,1.0334919192959893e-14,0.5988304018974304,11.139335546006153,11.392634807234638,11.1025,11.1425,11.3825,11.4225,0.040000000000000924,0.03999999999999915 --lzEya4AM_4/6,-lzEya4AM_4,6,32,it,11.422499656677246,11.822500228881836,True,4.624125230265992e-15,0.26793307065963745,11.473483985557554,11.813451673400056,11.4225,11.7225,11.7625,11.8225,0.3000000000000007,0.0600000000000005 --lzEya4AM_4/6,-lzEya4AM_4,6,33,could,11.842499732971191,12.022500038146973,True,3.321526835517517e-15,0.25,11.841404836972417,12.022500039924171,11.8225,11.8425,12.022499999999999,12.022499999999999,0.019999999999999574,0.0 --lzEya4AM_4/6,-lzEya4AM_4,6,34,cause,12.0625,12.322500228881836,True,5.640726550264078e-15,0.3268374502658844,12.06249996265842,12.322485847197163,12.0625,12.0625,12.3225,12.3225,0.0,0.0 --lzEya4AM_4/6,-lzEya4AM_4,6,35,damage,12.362500190734863,12.702500343322754,True,1.301325600690283e-14,0.7540197372436523,12.362499995548271,12.702500000019468,12.362499999999999,12.362499999999999,12.7025,12.7025,0.0,0.0 --lzEya4AM_4/6,-lzEya4AM_4,6,36,and,12.742500305175781,12.842499732971191,True,3.552262157300055e-16,0.25,12.742469306485088,12.842550373760359,12.7425,12.7425,12.8425,12.8425,0.0,0.0 --lzEya4AM_4/6,-lzEya4AM_4,6,37,burning,12.882499694824219,13.482500076293945,True,1.0955535659435203e-13,4.0,12.882500009396367,13.474533767589687,12.8825,12.8825,13.4825,13.4825,0.0,0.0 --lzEya4AM_4/6,-lzEya4AM_4,6,38,on,13.5625,13.6225004196167,True,6.547006318156912e-14,3.793494939804077,13.558178654761617,13.618923926660116,13.5625,13.5625,13.6225,13.6225,0.0,0.0 --lzEya4AM_4/6,-lzEya4AM_4,6,39,the,13.642499923706055,13.762499809265137,True,5.965204543566466e-15,0.3456384837627411,13.653632540597108,13.769364286143006,13.6425,13.7025,13.7625,13.8025,0.0600000000000005,0.040000000000000924 --lzEya4AM_4/6,-lzEya4AM_4,6,40,way,13.822500228881836,13.982500076293945,True,1.5995148253318027e-14,0.9267978668212891,13.822149170618747,13.981798894446957,13.8225,13.8225,13.9825,13.9825,0.0,0.0 --lzEya4AM_4/6,-lzEya4AM_4,6,41,back,14.022500038146973,14.182499885559082,True,3.619833416573879e-15,0.25,14.022029813684714,14.182729174722772,14.022499999999999,14.022499999999999,14.1825,14.1825,0.0,0.0 --lzEya4AM_4/6,-lzEya4AM_4,6,42,up.,14.202500343322754,14.542499542236328,True,1.867283073430921e-16,0.25,14.203948102653264,14.521972037563804,14.2025,14.2025,14.2825,14.7025,0.0,0.41999999999999993 --mJ2ud6oKI8/1,-mJ2ud6oKI8,1,0,There,0.0024999999441206455,0.48249998688697815,True,8.852508309731277e-11,1.0036022663116455,0.0698258865699199,0.5209542854210507,0.0025000000000000005,0.2225,0.3025,0.8225,0.22,0.52 --mJ2ud6oKI8/1,-mJ2ud6oKI8,1,1,are,0.5024999976158142,0.6025000214576721,True,8.811709695244474e-11,0.9989769458770752,0.6773580062375331,0.9126256507986633,0.4025,1.0225,0.6024999999999999,1.2825,0.6199999999999999,0.68 --mJ2ud6oKI8/1,-mJ2ud6oKI8,1,2,a,0.6225000023841858,0.6424999833106995,True,8.820733726766505e-11,1.0,1.0689133910196154,1.0889133910215332,0.7224999999999999,1.4825,0.7424999999999999,1.5025,0.76,0.76 --mJ2ud6oKI8/1,-mJ2ud6oKI8,1,3,dozen,0.6625000238418579,0.8424999713897705,True,8.838636073038586e-11,1.002029538154602,1.2452262918671384,1.6960141945305303,0.8624999999999999,1.6625,1.2825,2.1625,0.8000000000000002,0.8800000000000001 --mJ2ud6oKI8/1,-mJ2ud6oKI8,1,4,or,0.862500011920929,0.9225000143051147,True,8.844412008324198e-11,1.0026843547821045,1.8525124174329262,1.9802406363476905,1.4224999999999999,2.3225,1.5425,2.4625,0.8999999999999999,0.9199999999999999 --mJ2ud6oKI8/1,-mJ2ud6oKI8,1,5,more,0.9424999952316284,1.0824999809265137,True,8.837957449214784e-11,1.0019526481628418,2.13674030925521,2.479925987685495,1.6824999999999999,2.6225,2.0025,2.9625,0.9400000000000002,0.96 --mJ2ud6oKI8/1,-mJ2ud6oKI8,1,6,hands,1.1024999618530273,1.2825000286102295,True,8.822227670624017e-11,1.0001693964004517,2.636425683706365,3.0873399364897796,2.1625,3.1225,2.6025,3.5825,0.96,0.98 --mJ2ud6oKI8/1,-mJ2ud6oKI8,1,7,on,5.002500057220459,5.0625,True,8.802221451720271e-11,0.9979012608528137,3.2438396325030245,3.3715681957004184,2.7425,3.7225,2.8825,3.8625,0.98,0.98 --mJ2ud6oKI8/1,-mJ2ud6oKI8,1,8,techniques,5.082499980926514,5.462500095367432,True,8.812522239720622e-11,0.999069094657898,3.5280678917076664,4.517627610187784,3.0425,4.0025,4.062500000000001,4.9225,0.9600000000000004,0.8599999999999994 --mJ2ud6oKI8/1,-mJ2ud6oKI8,1,9,that,5.482500076293945,5.622499942779541,True,8.802477496905325e-11,0.9979302883148193,4.674114102900365,5.017234219415555,4.242500000000001,5.062500000000001,4.6225000000000005,5.362500000000001,0.8200000000000003,0.7400000000000002 --mJ2ud6oKI8/1,-mJ2ud6oKI8,1,10,we,5.78249979019165,5.84250020980835,True,8.77886582872911e-11,0.9952534437179565,5.173628548001558,5.301276562327708,4.8025,5.482500000000001,4.942500000000001,5.602500000000001,0.6800000000000006,0.6600000000000001 --mJ2ud6oKI8/1,-mJ2ud6oKI8,1,11,can,5.862500190734863,5.962500095367432,True,8.818036578706057e-11,0.9996942281723022,5.4575589081038185,5.692827986897282,5.1425,5.702500000000001,5.4225,5.8825,0.5600000000000005,0.45999999999999996 --mJ2ud6oKI8/1,-mJ2ud6oKI8,1,12,do,5.982500076293945,6.042500019073486,True,9.066991601969221e-11,1.0279181003570557,5.849047962874614,5.976323928323296,5.6425,5.982500000000001,5.822500000000001,6.0425,0.34000000000000075,0.21999999999999975 --mJ2ud6oKI8/2,-mJ2ud6oKI8,2,0,So,0.0024999999441206455,0.0625,True,9.096196018631986e-11,1.0093817710876465,0.032718039902220324,0.12302393990958412,0.0025000000000000005,0.10250000000000001,0.0625,0.2225,0.1,0.16 --mJ2ud6oKI8/2,-mJ2ud6oKI8,2,1,physical,0.08250000327825546,0.7425000071525574,True,9.035900500053984e-11,1.0026909112930298,0.20484162269624073,0.7183170211432781,0.10250000000000001,0.3425,0.5425,0.9425,0.24000000000000002,0.4 --mJ2ud6oKI8/2,-mJ2ud6oKI8,2,2,therapists,0.762499988079071,1.1425000429153442,True,9.044751059228417e-11,1.0036730766296387,0.7999759850899307,1.454059627827414,0.6024999999999999,1.0225,1.2025,1.7225,0.42000000000000004,0.52 --mJ2ud6oKI8/2,-mJ2ud6oKI8,2,3,and,1.162500023841858,1.2625000476837158,True,9.025457464728603e-11,1.0015320777893066,1.5358937446088856,1.6969050105096142,1.2825,1.8225,1.4224999999999999,1.9825,0.54,0.56 --mJ2ud6oKI8/2,-mJ2ud6oKI8,2,4,chiropractors,1.3025000095367432,1.8025000095367432,True,9.00861468755565e-11,0.9996631145477295,1.7787420065370874,2.644814585780178,1.5025,2.0625,2.3425,2.9425,0.56,0.6000000000000001 --mJ2ud6oKI8/2,-mJ2ud6oKI8,2,5,will,1.8224999904632568,1.962499976158142,True,9.00861468755565e-11,0.9996631145477295,2.72665159286188,2.9581697385244805,2.4225,3.0225,2.6625,3.2625,0.6000000000000001,0.6000000000000001 --mJ2ud6oKI8/2,-mJ2ud6oKI8,2,6,do,1.9824999570846558,2.0425000190734863,True,9.00861468755565e-11,0.9996631145477295,3.0400067456061746,3.1305127941614,2.7425,3.3425,2.8225,3.4225,0.5999999999999996,0.6000000000000001 --mJ2ud6oKI8/2,-mJ2ud6oKI8,2,7,joint,2.0625,2.242500066757202,True,9.00861468755565e-11,0.9996631145477295,3.2123498012430876,3.51437399545938,2.9225,3.5025,3.2225,3.8025,0.5800000000000001,0.5800000000000001 --mJ2ud6oKI8/2,-mJ2ud6oKI8,2,8,manipulations,2.262500047683716,2.762500047683716,True,9.00861468755565e-11,0.9996631145477295,3.5962110025410743,4.462293761119333,3.3025,3.8825,4.202500000000001,4.702500000000001,0.5799999999999996,0.5 --mJ2ud6oKI8/2,-mJ2ud6oKI8,2,9,and,4.722499847412109,4.822500228881836,True,9.011650453638609e-11,1.0,4.544132032136779,4.705125324259879,4.3025,4.7625,4.4625,4.9225,0.45999999999999996,0.45999999999999996 --mJ2ud6oKI8/2,-mJ2ud6oKI8,2,10,mobilizations,4.84250020980835,5.682499885559082,True,9.054999805524488e-11,1.0048103332519531,4.786928814409058,5.65272602695609,4.562500000000001,4.982500000000001,5.5825000000000005,5.6825,0.41999999999999993,0.09999999999999964 --mJ2ud6oKI8/6,-mJ2ud6oKI8,6,0,They,0.02250000089406967,0.3824999928474426,True,5.596440533759718e-14,0.25,0.07685901928112787,0.3990715972593789,0.0225,0.14250000000000002,0.3825,0.4425,0.12000000000000002,0.06 --mJ2ud6oKI8/6,-mJ2ud6oKI8,6,1,are,0.4424999952316284,0.7024999856948853,True,6.72760512663434e-13,1.0,0.5160575050547208,0.7227117404819162,0.4425,0.6024999999999999,0.7025,0.7424999999999999,0.15999999999999992,0.039999999999999925 --mJ2ud6oKI8/6,-mJ2ud6oKI8,6,2,all,0.7825000286102295,0.9424999952316284,True,2.1975723649668433e-13,0.3266500234603882,0.7935273972149047,0.9526167018557699,0.7424999999999999,0.8424999999999999,0.8624999999999999,0.9425,0.09999999999999998,0.08000000000000007 --mJ2ud6oKI8/6,-mJ2ud6oKI8,6,3,very,1.0824999809265137,1.3825000524520874,True,3.322413177908601e-11,4.0,1.1101423300401905,1.4078282823092163,1.0625,1.0825,1.3825,1.3825,0.020000000000000018,0.0 --mJ2ud6oKI8/6,-mJ2ud6oKI8,6,4,safe,1.8224999904632568,2.1624999046325684,True,4.374835129578036e-12,4.0,1.859322265183538,2.141602476798535,1.7825,1.9425,2.0225,2.1625,0.15999999999999992,0.14000000000000012 --mJ2ud6oKI8/9,-mJ2ud6oKI8,9,0,It's,0.0625,0.26249998807907104,True,1.3943171617292194e-10,4.0,0.047669511258957874,0.2484408818378565,0.0025000000000000005,0.0625,0.1825,0.28250000000000003,0.06,0.10000000000000003 --mJ2ud6oKI8/9,-mJ2ud6oKI8,9,1,safe,0.4025000035762787,0.6225000023841858,True,4.5447569319012615e-12,4.0,0.3360747022548775,0.5170328362234636,0.2025,0.4025,0.4225,0.6224999999999999,0.2,0.19999999999999996 --mJ2ud6oKI8/9,-mJ2ud6oKI8,9,2,and,0.6424999833106995,0.7425000071525574,True,2.003821819912999e-15,0.25,0.5856019452028779,0.7191063800421992,0.4825,0.6425,0.7025,0.7424999999999999,0.15999999999999998,0.039999999999999925 --mJ2ud6oKI8/9,-mJ2ud6oKI8,9,3,the,0.8424999713897705,0.9624999761581421,True,1.243637679816667e-12,2.812455415725708,0.8453878094860923,0.9667462538582235,0.8424999999999999,0.8424999999999999,0.9624999999999999,0.9624999999999999,0.0,0.0 --mJ2ud6oKI8/9,-mJ2ud6oKI8,9,4,person,1.122499942779541,1.3825000524520874,True,1.8701285366216208e-13,0.4229249060153961,1.0165126982997161,1.308275716440458,0.9824999999999999,1.1225,1.2825,1.3825,0.14000000000000012,0.10000000000000009 --mJ2ud6oKI8/9,-mJ2ud6oKI8,9,5,will,1.462499976158142,1.6425000429153442,True,3.865140087329355e-13,0.8740917444229126,1.3867817686280777,1.5999738769213134,1.3625,1.4625,1.5225,1.7225,0.09999999999999987,0.19999999999999996 --mJ2ud6oKI8/9,-mJ2ud6oKI8,9,6,feel,1.7024999856948853,1.9225000143051147,True,2.057110043288471e-13,0.46521028876304626,1.6644042882905339,1.8580207414522327,1.5625,1.8425,1.7625,2.0825,0.28,0.32000000000000006 --mJ2ud6oKI8/9,-mJ2ud6oKI8,9,7,better,2.0625,2.3424999713897705,True,2.55443778109099e-12,4.0,1.9039668350534087,2.269341184316521,1.8425,2.1225,2.2225,2.3825,0.28,0.1599999999999997 --mJ2ud6oKI8/9,-mJ2ud6oKI8,9,8,later,2.382499933242798,2.742500066757202,True,6.280226447392956e-13,1.4202574491500854,2.3391000804104283,2.610403111609425,2.3225,2.4025,2.5225,2.7425,0.08000000000000007,0.2200000000000002 --mJ2ud6oKI8/9,-mJ2ud6oKI8,9,9,"on,",2.922499895095825,3.002500057220459,True,4.978645534031712e-13,1.1259082555770874,2.736678888486408,2.8013639750269204,2.6825,2.9225,2.7425,3.0025,0.23999999999999977,0.2599999999999998 --mJ2ud6oKI8/9,-mJ2ud6oKI8,9,10,but,3.0225000381469727,3.1424999237060547,True,5.492410657683376e-15,0.25,2.853221959313782,3.0344224455998434,2.8025,3.0225,3.0025,3.1425,0.21999999999999975,0.14000000000000012 --mJ2ud6oKI8/9,-mJ2ud6oKI8,9,11,it's,3.182499885559082,3.2825000286102295,True,7.276466755523625e-12,4.0,3.110513745542075,3.269832850162292,3.0625,3.1825,3.2625,3.2825,0.1200000000000001,0.020000000000000018 --mJ2ud6oKI8/9,-mJ2ud6oKI8,9,12,sort,3.302500009536743,3.4625000953674316,True,1.0976491254550275e-13,0.25,3.30240099690659,3.461609169642533,3.3025,3.3025,3.4425,3.4825,0.0,0.040000000000000036 --mJ2ud6oKI8/9,-mJ2ud6oKI8,9,13,of,3.5425000190734863,3.622499942779541,True,2.677345107768292e-12,4.0,3.5413547723387526,3.6216566418041243,3.5425,3.5425,3.6225,3.6225,0.0,0.0 --mJ2ud6oKI8/9,-mJ2ud6oKI8,9,14,like,3.6624999046325684,3.8424999713897705,True,8.644191455296421e-14,0.25,3.666813689753435,3.838871048201672,3.6625,3.7025,3.8225000000000002,3.8625,0.040000000000000036,0.03999999999999959 --mJ2ud6oKI8/9,-mJ2ud6oKI8,9,15,flossing,3.882499933242798,4.34250020980835,True,1.1762174621874483e-13,0.26599863171577454,3.8838651729144584,4.3424120629860194,3.8825,3.8825,4.3425,4.3425,0.0,0.0 --mJ2ud6oKI8/9,-mJ2ud6oKI8,9,16,your,4.362500190734863,5.0625,True,3.292849730406923e-14,0.25,4.41819147818272,5.111481728190935,4.362500000000001,4.9625,5.022500000000001,5.1625000000000005,0.5999999999999996,0.13999999999999968 --mJ2ud6oKI8/9,-mJ2ud6oKI8,9,17,teeth,5.102499961853027,5.922500133514404,True,1.063016455459323e-13,0.25,5.148201109665343,5.921581298640506,5.102500000000001,5.202500000000001,5.9225,5.9225,0.09999999999999964,0.0 --mJ2ud6oKI8/9,-mJ2ud6oKI8,9,18,for,5.962500095367432,6.0625,True,6.951333768583784e-14,0.25,5.954329937943031,6.058653654509152,5.942500000000001,5.9625,6.0425,6.062500000000001,0.019999999999999574,0.020000000000000462 --mJ2ud6oKI8/9,-mJ2ud6oKI8,9,19,the,6.082499980926514,6.202499866485596,True,4.954940624468662e-11,4.0,6.082503363629208,6.202503801804082,6.0825000000000005,6.0825000000000005,6.202500000000001,6.202500000000001,0.0,0.0 --mJ2ud6oKI8/9,-mJ2ud6oKI8,9,20,first,6.262499809265137,6.502500057220459,True,5.828269290797383e-12,4.0,6.26250188369506,6.513630284736709,6.2625,6.2625,6.5025,6.562500000000001,0.0,0.0600000000000005 --mJ2ud6oKI8/9,-mJ2ud6oKI8,9,21,time,6.662499904632568,6.882500171661377,True,1.4780298296032668e-12,3.342527389526367,6.662037112250419,6.879055062501529,6.6625000000000005,6.6625000000000005,6.862500000000001,6.8825,0.0,0.019999999999999574 --mJ2ud6oKI8/8,-mJ2ud6oKI8,8,0,Sometimes,0.7825000286102295,1.162500023841858,True,6.672226790169211e-13,0.2790868580341339,0.4509397771605163,1.1624976149860125,0.0625,0.7825,1.1624999999999999,1.1624999999999999,0.72,0.0 --mJ2ud6oKI8/8,-mJ2ud6oKI8,8,1,we,1.222499966621399,1.3624999523162842,True,1.8925133682401452e-10,4.0,1.2224980141426944,1.3624753576252613,1.2225,1.2225,1.3625,1.3625,0.0,0.0 --mJ2ud6oKI8/8,-mJ2ud6oKI8,8,2,have,1.4225000143051147,1.6425000429153442,True,1.5286633721009468e-12,0.6394115090370178,1.422078617604423,1.6204572489346851,1.4025,1.4425,1.5825,1.6425,0.039999999999999813,0.06000000000000005 --mJ2ud6oKI8/8,-mJ2ud6oKI8,8,3,to,1.7024999856948853,1.8025000095367432,True,2.3907347455887074e-12,1.0,1.7059088038846568,1.799902197420372,1.7025,1.7025,1.7825,1.8025,0.0,0.020000000000000018 --mJ2ud6oKI8/8,-mJ2ud6oKI8,8,4,stretch,1.9824999570846558,2.262500047683716,True,5.604740629938654e-12,2.3443591594696045,1.932309459892086,2.2160627365081274,1.8825,1.9825,2.1625,2.2625,0.09999999999999987,0.10000000000000009 --mJ2ud6oKI8/8,-mJ2ud6oKI8,8,5,that,2.302500009536743,2.442500114440918,True,2.0492338295013957e-12,0.85715651512146,2.2511005842143135,2.4180146282719335,2.2025,2.3025,2.4025,2.4425,0.10000000000000009,0.040000000000000036 --mJ2ud6oKI8/8,-mJ2ud6oKI8,8,6,joint,2.4825000762939453,2.8424999713897705,True,6.914385296957759e-12,2.8921592235565186,2.4558962302559877,2.8143964443535863,2.4225,2.4825,2.7825,2.8425,0.06000000000000005,0.05999999999999961 --mJ2ud6oKI8/8,-mJ2ud6oKI8,8,7,that,2.922499895095825,3.182499885559082,True,2.6334511828152163e-12,1.101523756980896,2.889294160998902,3.104634416094476,2.8225,2.9425,3.0625,3.1825,0.1200000000000001,0.1200000000000001 --mJ2ud6oKI8/8,-mJ2ud6oKI8,8,8,is,3.2225000858306885,3.2825000286102295,True,1.5851010825088108e-12,0.6630184054374695,3.128230706539492,3.2041105692463807,3.0825,3.2225,3.1825,3.2825,0.14000000000000012,0.10000000000000009 --mJ2ud6oKI8/8,-mJ2ud6oKI8,8,9,already,3.302500009536743,3.702500104904175,True,1.9910991258531574e-11,4.0,3.240455573466579,3.5472033751853838,3.2225,3.3025,3.5025,3.7025,0.08000000000000007,0.20000000000000018 --mJ2ud6oKI8/8,-mJ2ud6oKI8,8,10,irritated,3.742500066757202,4.142499923706055,True,5.874412826838149e-13,0.25,3.594318712702423,4.142499418606456,3.5225,3.7425,4.1425,4.1425,0.2200000000000002,0.0 --mqbVkbCndg/0,-mqbVkbCndg,0,0,"How,",0.16249999403953552,0.36250001192092896,True,7.513402335186659e-13,3.2922470569610596,0.16295956092843808,0.4110743546178127,0.1625,0.1625,0.3625,0.4625,0.0,0.10000000000000003 --mqbVkbCndg/0,-mqbVkbCndg,0,1,at,0.4625000059604645,0.9024999737739563,True,5.430498715638943e-13,2.3795535564422607,0.5327332294690263,0.9094743295388469,0.4625,0.8825,0.9025,0.9624999999999999,0.41999999999999993,0.05999999999999994 --mqbVkbCndg/0,-mqbVkbCndg,0,2,a,0.9825000166893005,1.002500057220459,True,2.976669952192701e-11,4.0,0.9824999384988177,1.0024999384988176,0.9824999999999999,0.9824999999999999,1.0025,1.0025,0.0,0.0 --mqbVkbCndg/0,-mqbVkbCndg,0,3,particular,1.0225000381469727,1.5625,True,1.1336772991719923e-13,0.4967584013938904,1.035725275560386,1.5800902946906012,1.0225,1.0625,1.5625,1.6025,0.040000000000000036,0.040000000000000036 --mqbVkbCndg/0,-mqbVkbCndg,0,4,moment,1.6024999618530273,1.9824999570846558,True,1.4489467568476466e-13,0.6349042057991028,1.6349622213695993,2.0086853034404504,1.6025,1.6625,1.9825,2.0425,0.06000000000000005,0.06000000000000005 --mqbVkbCndg/0,-mqbVkbCndg,0,5,in,2.0225000381469727,2.122499942779541,True,1.2200440310805583e-13,0.5346028804779053,2.0643636679285398,2.153146501312387,2.0225,2.1025,2.1025,2.1825,0.08000000000000007,0.08000000000000007 --mqbVkbCndg/0,-mqbVkbCndg,0,6,time—our,2.242500066757202,2.942500114440918,True,1.081351371293171e-12,4.0,2.2427627508097463,2.94254615237048,2.2425,2.2425,2.9425,2.9425,0.0,0.0 --mqbVkbCndg/0,-mqbVkbCndg,0,7,moment,3.002500057220459,3.4024999141693115,True,2.059274381875295e-13,0.9023395776748657,3.032264713672813,3.4035362198847228,3.0025,3.0625,3.4025,3.4025,0.06000000000000005,0.0 --mqbVkbCndg/0,-mqbVkbCndg,0,8,in,3.442500114440918,3.5425000190734863,True,4.4287579788367115e-13,1.9406076669692993,3.4443813754599724,3.5444835777278967,3.4425,3.4425,3.5425,3.5425,0.0,0.0 --mqbVkbCndg/0,-mqbVkbCndg,0,9,time—are,3.682499885559082,4.622499942779541,True,1.3476970461921006e-13,0.5905382633209229,3.679404616920505,4.624780510292684,3.6225,3.6825,4.6225000000000005,4.6625000000000005,0.06000000000000005,0.040000000000000036 --mqbVkbCndg/0,-mqbVkbCndg,0,10,they,4.722499847412109,4.922500133514404,True,7.855013568845021e-14,0.34419354796409607,4.718384341212022,4.920950495392551,4.702500000000001,4.7225,4.9225,4.9225,0.019999999999999574,0.0 --mqbVkbCndg/0,-mqbVkbCndg,0,11,limited,5.422500133514404,5.902500152587891,True,2.5050260802315927e-13,1.0976605415344238,5.42248890408293,5.900145834505198,5.4225,5.4225,5.8825,5.902500000000001,0.0,0.020000000000000462 --t217m2on-s/2,-t217m2on-s,2,0,But,0.5224999785423279,0.7024999856948853,True,4.395274508933733e-12,0.7390152812004089,0.5225184924573115,0.725752175317485,0.5225,0.5225,0.7025,0.7424999999999999,0.0,0.039999999999999925 --t217m2on-s/2,-t217m2on-s,2,1,a,0.7225000262260437,0.7425000071525574,True,3.8194742507657864e-11,4.0,0.8000684223499559,0.820068422350041,0.7224999999999999,0.9025,0.7424999999999999,0.9225,0.18000000000000005,0.18000000000000005 --t217m2on-s/2,-t217m2on-s,2,2,good,0.862500011920929,1.002500057220459,True,7.123131945396821e-12,1.1976734399795532,0.9991130601109262,1.1892688242883607,0.7825,1.3625,1.0025,1.5625,0.5800000000000001,0.56 --t217m2on-s/2,-t217m2on-s,2,3,thing,1.0625,1.5625,True,4.771816188714473e-12,0.802326500415802,1.2388210425890023,1.644624686370855,1.0625,1.6025,1.5625,1.8225,0.54,0.26 --t217m2on-s/2,-t217m2on-s,2,4,to,1.6425000429153442,1.7024999856948853,True,1.0024173158207361e-10,4.0,1.7111086033802672,1.7718470918463047,1.6425,1.8625,1.7025,1.9224999999999999,0.21999999999999997,0.21999999999999997 --t217m2on-s/2,-t217m2on-s,2,5,do,1.722499966621399,1.8224999904632568,True,1.4645716280362042e-12,0.25,1.8248417371760293,1.899259041877084,1.7225,2.0025,1.8225,2.0625,0.28,0.24 --t217m2on-s/2,-t217m2on-s,2,6,is,1.8624999523162842,1.9225000143051147,True,2.995276249251333e-11,4.0,1.9473941160787953,2.048927727382598,1.8625,2.1225,1.9224999999999999,2.3225,0.26,0.3999999999999999 --t217m2on-s/2,-t217m2on-s,2,7,"yawning,",2.002500057220459,2.5225000381469727,True,2.0731873249385524e-12,0.34858280420303345,2.126425467276586,2.7815458651990497,2.0025,2.4025,2.5225,3.3825,0.3999999999999999,0.8599999999999999 --t217m2on-s/2,-t217m2on-s,2,8,chewing,3.322499990463257,3.862499952316284,True,8.043577089111853e-12,1.352435827255249,3.3678403420855934,3.876952620924111,3.3225000000000002,3.4625,3.8625,3.9025,0.13999999999999968,0.040000000000000036 --t217m2on-s/2,-t217m2on-s,2,9,gum,4.002500057220459,4.182499885559082,True,4.4149128797243975e-12,0.742317259311676,4.002468735954162,4.1826709100986985,4.0025,4.0025,4.1825,4.1825,0.0,0.0 --t217m2on-s/2,-t217m2on-s,2,10,is,4.302499771118164,4.402500152587891,True,4.180251630958587e-11,4.0,4.302498326491306,4.402498558458009,4.3025,4.3025,4.402500000000001,4.402500000000001,0.0,0.0 --t217m2on-s/2,-t217m2on-s,2,11,effective.,4.422500133514404,5.042500019073486,True,2.2316224389251627e-12,0.3752218782901764,4.423601965630909,5.043327191160557,4.4225,4.4225,5.0425,5.0425,0.0,0.0 --t217m2on-s/7,-t217m2on-s,7,0,If,0.5224999785423279,0.6025000214576721,True,2.0082098740962498e-15,0.25,0.3015441331703468,0.6023878008153598,0.0625,0.5425,0.5824999999999999,0.6024999999999999,0.48,0.020000000000000018 --t217m2on-s/7,-t217m2on-s,7,1,you,0.6424999833106995,0.8025000095367432,True,8.301148532669292e-14,0.42261114716529846,0.6434799647001955,0.7975552797224235,0.6425,0.6425,0.7625,0.8025,0.0,0.040000000000000036 --t217m2on-s/7,-t217m2on-s,7,2,find,0.8424999713897705,1.122499942779541,True,2.140681512260989e-12,4.0,0.8412030234650724,1.1153169739376245,0.8424999999999999,0.8424999999999999,1.0625,1.1225,0.0,0.06000000000000005 --t217m2on-s/7,-t217m2on-s,7,3,that,1.1425000429153442,1.3424999713897705,True,1.610306723882004e-15,0.25,1.1383865714841004,1.3366361795938604,1.1025,1.1425,1.2825,1.3425,0.040000000000000036,0.06000000000000005 --t217m2on-s/7,-t217m2on-s,7,4,your,1.402500033378601,1.5425000190734863,True,4.7928254789421365e-14,0.25,1.4035147118997728,1.5474983663610131,1.4025,1.4025,1.5425,1.6025,0.0,0.06000000000000005 --t217m2on-s/7,-t217m2on-s,7,5,ears,1.7024999856948853,2.0225000381469727,True,1.2316479758821275e-13,0.6270315051078796,1.7035309636037015,2.0069588683882187,1.7025,1.7225,1.9425,2.0225,0.020000000000000018,0.08000000000000007 --t217m2on-s/7,-t217m2on-s,7,6,consistently,2.7225000858306885,4.002500057220459,True,5.272141772628969e-13,2.6840453147888184,2.6778890918337224,4.004975277533073,2.0225,2.7225,4.0025,4.0025,0.7000000000000002,0.0 --t217m2on-s/7,-t217m2on-s,7,7,do,4.28249979019165,4.402500152587891,True,2.9934043525164933e-12,4.0,4.279017335996583,4.399301163358553,4.282500000000001,4.282500000000001,4.402500000000001,4.402500000000001,0.0,0.0 --t217m2on-s/7,-t217m2on-s,7,8,this,4.522500038146973,4.702499866485596,True,1.2310472770565937e-14,0.25,4.4871016225096705,4.692839750002059,4.442500000000001,4.522500000000001,4.6625000000000005,4.702500000000001,0.08000000000000007,0.040000000000000036 --t217m2on-s/7,-t217m2on-s,7,9,and,4.78249979019165,4.882500171661377,True,2.4961423986807896e-14,0.25,4.771094354005105,4.876832336738395,4.702500000000001,4.782500000000001,4.8425,4.8825,0.08000000000000007,0.040000000000000036 --t217m2on-s/7,-t217m2on-s,7,10,you,4.902500152587891,5.002500057220459,True,2.269763060296537e-15,0.25,4.900825762575524,5.003465900093947,4.902500000000001,4.902500000000001,5.0025,5.022500000000001,0.0,0.020000000000000462 --t217m2on-s/7,-t217m2on-s,7,11,can't,5.042500019073486,5.34250020980835,True,1.9953183549858977e-10,4.0,5.0430587580198285,5.342191859761064,5.0425,5.0425,5.3425,5.3425,0.0,0.0 --t217m2on-s/7,-t217m2on-s,7,12,pop,5.5625,5.802499771118164,True,2.0839250464144143e-12,4.0,5.562475953090791,5.802493273965683,5.562500000000001,5.562500000000001,5.8025,5.8025,0.0,0.0 --t217m2on-s/7,-t217m2on-s,7,13,them,5.862500190734863,6.0625,True,3.170972870131933e-14,0.25,5.862493429115527,6.062460001350499,5.862500000000001,5.862500000000001,6.062500000000001,6.062500000000001,0.0,0.0 --t217m2on-s/7,-t217m2on-s,7,14,"often,",6.182499885559082,6.442500114440918,True,3.143114634123097e-14,0.25,6.167211454501574,6.46103084293285,6.102500000000001,6.1825,6.442500000000001,6.482500000000001,0.07999999999999918,0.040000000000000036 --t217m2on-s/7,-t217m2on-s,7,15,you'll,6.482500076293945,7.082499980926514,True,6.824945990302478e-12,4.0,6.574808668518842,7.082477879268368,6.482500000000001,6.742500000000001,7.0825000000000005,7.0825000000000005,0.2599999999999998,0.0 --t217m2on-s/7,-t217m2on-s,7,16,definitely,7.102499961853027,7.702499866485596,True,7.39595559275108e-13,3.7652781009674072,7.102586666901631,7.699765961681586,7.102500000000001,7.102500000000001,7.6825,7.702500000000001,0.0,0.020000000000000462 --t217m2on-s/7,-t217m2on-s,7,17,need,7.742499828338623,7.902500152587891,True,4.3668524742426773e-13,2.223162889480591,7.742483042947323,7.90343923658525,7.742500000000001,7.742500000000001,7.902500000000001,7.902500000000001,0.0,0.0 --t217m2on-s/7,-t217m2on-s,7,18,to,7.982500076293945,8.042499542236328,True,7.402548727805918e-15,0.25,7.967266830139866,8.02793425896618,7.942500000000001,7.982500000000001,8.0025,8.0425,0.040000000000000036,0.040000000000000924 --t217m2on-s/7,-t217m2on-s,7,19,see,8.0625,8.202500343322754,True,6.569796789923643e-13,3.3446807861328125,8.062499998585567,8.202499998830312,8.0625,8.0625,8.202499999999999,8.202499999999999,0.0,0.0 --t217m2on-s/7,-t217m2on-s,7,20,a,8.242500305175781,8.262499809265137,True,2.488813842516091e-11,4.0,8.242500408823773,8.262500408823774,8.2425,8.2425,8.2625,8.2625,0.0,0.0 --t217m2on-s/7,-t217m2on-s,7,21,physician,8.322500228881836,8.882499694824219,True,4.652816760347678e-13,2.3687472343444824,8.318703380787824,8.881929128769334,8.282499999999999,8.3225,8.8825,8.8825,0.040000000000000924,0.0 --t217m2on-s/7,-t217m2on-s,7,22,regarding,8.90250015258789,9.922499656677246,True,1.5294997256568021e-13,0.778667688369751,8.904235783104783,9.922499327985719,8.9025,8.9025,9.9225,9.9225,0.0,0.0 --t217m2on-s/7,-t217m2on-s,7,23,those,9.942500114440918,10.162500381469727,True,1.9642521929732343e-13,1.0,9.942499955586987,10.162498402387016,9.942499999999999,9.942499999999999,10.1625,10.1625,0.0,0.0 --t217m2on-s/7,-t217m2on-s,7,24,"things,",10.202500343322754,10.522500038146973,True,3.872858929171094e-14,0.25,10.202499406780868,10.522499422185247,10.2025,10.2025,10.522499999999999,10.522499999999999,0.0,0.0 --t217m2on-s/7,-t217m2on-s,7,25,it,10.90250015258789,10.982500076293945,True,1.0897798505618561e-13,0.5548064708709717,10.90176918863294,10.98161988705827,10.9025,10.9025,10.9825,10.9825,0.0,0.0 --t217m2on-s/7,-t217m2on-s,7,26,could,11.022500038146973,11.22249984741211,True,3.0060584013322234e-13,1.5303831100463867,11.022415515548126,11.222436263178336,11.022499999999999,11.022499999999999,11.2225,11.2225,0.0,0.0 --t217m2on-s/7,-t217m2on-s,7,27,be,11.242500305175781,11.302499771118164,True,3.1117084820300733e-13,1.5841695070266724,11.242499890968537,11.302500000932035,11.2425,11.2425,11.3025,11.3025,0.0,0.0 --t217m2on-s/7,-t217m2on-s,7,28,something,11.362500190734863,11.762499809265137,True,1.3482193775293545e-14,0.25,11.36250003427757,11.76250000280012,11.362499999999999,11.362499999999999,11.7625,11.7625,0.0,0.0 --t217m2on-s/7,-t217m2on-s,7,29,more,11.782500267028809,11.982500076293945,True,2.739622764758032e-13,1.3947408199310303,11.782500172700903,11.982499985922653,11.782499999999999,11.782499999999999,11.9825,11.9825,0.0,0.0 --t217m2on-s/7,-t217m2on-s,7,30,of,12.0024995803833,12.0625,True,1.2251334495505528e-11,4.0,12.00250300781206,12.062503075601885,12.0025,12.0025,12.0625,12.0625,0.0,0.0 --t217m2on-s/7,-t217m2on-s,7,31,a,12.1225004196167,12.142499923706055,True,1.9523441023572286e-12,4.0,12.122493511797718,12.142493511797717,12.1225,12.1225,12.1425,12.1425,0.0,0.0 --t217m2on-s/7,-t217m2on-s,7,32,nasal,12.202500343322754,12.482500076293945,True,1.2489926627667902e-12,4.0,12.202481052988533,12.482563637084958,12.2025,12.2025,12.4825,12.4825,0.0,0.0 --t217m2on-s/7,-t217m2on-s,7,33,infection,12.542499542236328,13.082500457763672,True,1.863801268268267e-13,0.9488604664802551,12.548488364093338,13.112190709215227,12.5425,12.5825,13.0825,13.2025,0.03999999999999915,0.120000000000001 --t217m2on-s/7,-t217m2on-s,7,34,or,13.202500343322754,13.362500190734863,True,1.096706384560997e-12,4.0,13.268630794746127,13.380613030877182,13.2025,13.3425,13.362499999999999,13.4025,0.1399999999999988,0.040000000000000924 --t217m2on-s/7,-t217m2on-s,7,35,a,13.482500076293945,13.5024995803833,True,5.468596062097042e-12,4.0,13.480302700842564,13.500302700842568,13.442499999999999,13.4825,13.4625,13.5025,0.040000000000000924,0.03999999999999915 --t217m2on-s/7,-t217m2on-s,7,36,sinus,13.542499542236328,13.802499771118164,True,6.39902573203871e-13,3.2577414512634277,13.55040940879016,13.803847280153091,13.5025,13.5825,13.8025,13.8025,0.08000000000000007,0.0 --t217m2on-s/7,-t217m2on-s,7,37,infection,13.842499732971191,14.5024995803833,True,1.1748278131579193e-12,4.0,13.844256664988658,14.507515066421155,13.8425,13.8425,14.5025,14.522499999999999,0.0,0.019999999999999574 --t217m2on-s/7,-t217m2on-s,7,38,that,14.6225004196167,15.322500228881836,True,1.0841008673450128e-14,0.25,14.62701468477748,15.32177485942577,14.6225,14.6225,15.3225,15.3225,0.0,0.0 --t217m2on-s/7,-t217m2on-s,7,39,he,15.382499694824219,15.462499618530273,True,1.5006362038411103e-12,4.0,15.382499899762017,15.462499926162874,15.3825,15.3825,15.4625,15.4625,0.0,0.0 --t217m2on-s/7,-t217m2on-s,7,40,would,15.522500038146973,15.742500305175781,True,7.458575722102054e-14,0.37971580028533936,15.523687096195976,15.743719806141243,15.522499999999999,15.522499999999999,15.7425,15.7425,0.0,0.0 --t217m2on-s/7,-t217m2on-s,7,41,need,15.782500267028809,15.982500076293945,True,6.329921260544644e-14,0.32225602865219116,15.783733230314803,15.975640595301629,15.7825,15.8025,15.9625,15.9825,0.019999999999999574,0.019999999999999574 --t217m2on-s/7,-t217m2on-s,7,42,to,16.022499084472656,16.082500457763672,True,2.435565990424951e-14,0.25,16.01099501177981,16.070999623759587,15.9825,16.0225,16.0425,16.082500000000003,0.040000000000000924,0.0400000000000027 --t217m2on-s/7,-t217m2on-s,7,43,deal,16.102500915527344,16.262500762939453,True,5.6791098482689064e-15,0.25,16.102225899317638,16.262741723317955,16.102500000000003,16.102500000000003,16.262500000000003,16.262500000000003,0.0,0.0 --t217m2on-s/7,-t217m2on-s,7,44,with.,16.342500686645508,16.522499084472656,True,4.8448539695074636e-14,0.25,16.342197762523412,16.52250670243474,16.3425,16.3425,16.5225,16.5225,0.0,0.0 --tANM6ETl_M/3,-tANM6ETl_M,3,0,The,0.5625,0.6625000238418579,True,6.435688570602394e-14,2.004267930984497,0.5356969890918912,0.658616661956421,0.3425,0.5625,0.6224999999999999,0.6625,0.21999999999999997,0.040000000000000036 --tANM6ETl_M/3,-tANM6ETl_M,3,1,first,0.7024999856948853,0.9624999761581421,True,3.526284895593451e-14,1.098191738128662,0.7009661313991286,0.9602388802710622,0.7025,0.7025,0.9225,0.9624999999999999,0.0,0.039999999999999925 --tANM6ETl_M/3,-tANM6ETl_M,3,2,place,1.002500057220459,1.3224999904632568,True,1.331900779580732e-14,0.4147941470146179,0.999946689866764,1.308838714213955,1.0025,1.0025,1.2825,1.3225,0.0,0.040000000000000036 --tANM6ETl_M/3,-tANM6ETl_M,3,3,is,1.3825000524520874,1.4424999952316284,True,4.107557105185273e-15,0.25,1.389821334669526,1.45349568534902,1.3625,1.4224999999999999,1.4425,1.4825,0.05999999999999983,0.040000000000000036 --tANM6ETl_M/3,-tANM6ETl_M,3,4,either,1.5425000190734863,1.7825000286102295,True,2.895699020735547e-14,0.9018082022666931,1.5201676262785533,1.7605858681075623,1.4825,1.5425,1.7225,1.7825,0.06000000000000005,0.06000000000000005 --tANM6ETl_M/3,-tANM6ETl_M,3,5,you,1.8624999523162842,2.0225000381469727,True,3.5744268601835966e-14,1.1131845712661743,1.8553028266965272,2.0036440368509445,1.8225,1.8625,1.9224999999999999,2.0225,0.040000000000000036,0.10000000000000009 --tANM6ETl_M/3,-tANM6ETl_M,3,6,have,2.0625,2.202500104904175,True,7.299865464709121e-15,0.25,2.062385601587532,2.202536012487326,2.0625,2.0625,2.2025,2.2025,0.0,0.0 --tANM6ETl_M/3,-tANM6ETl_M,3,7,a,2.2825000286102295,2.302500009536743,True,1.1580021663792905e-11,4.0,2.282498533579872,2.302498533579872,2.2825,2.2825,2.3025,2.3025,0.0,0.0 --tANM6ETl_M/3,-tANM6ETl_M,3,8,"prospect,",2.322499990463257,2.882499933242798,True,4.4684812321421196e-15,0.25,2.3231238527656637,2.882916379552269,2.3225,2.3225,2.8825,2.8825,0.0,0.0 --tANM6ETl_M/3,-tANM6ETl_M,3,9,or,2.942500114440918,3.002500057220459,True,2.767639904147773e-13,4.0,2.942497276629371,3.0032399939030863,2.9425,2.9425,3.0025,3.0025,0.0,0.0 --tANM6ETl_M/3,-tANM6ETl_M,3,10,a,3.0625,3.0824999809265137,True,1.837679140803683e-11,4.0,3.0620961698677016,3.0820961698677016,3.0625,3.0625,3.0825,3.0825,0.0,0.0 --tANM6ETl_M/3,-tANM6ETl_M,3,11,customer,3.1024999618530273,3.4825000762939453,True,1.1064295367489013e-13,3.445755958557129,3.103188292319035,3.4840491250071417,3.1025,3.1025,3.4825,3.4825,0.0,0.0 --tANM6ETl_M/3,-tANM6ETl_M,3,12,who's,3.5225000381469727,3.682499885559082,True,3.082221630701376e-11,4.0,3.5274568778891453,3.6835674538224654,3.5225,3.5425,3.6825,3.6825,0.020000000000000018,0.0 --tANM6ETl_M/3,-tANM6ETl_M,3,13,never,3.882499933242798,4.182499885559082,True,8.976713720498884e-15,0.27956199645996094,3.8070924541804487,4.15445694471168,3.7225,3.8825,4.1225000000000005,4.1825,0.1599999999999997,0.05999999999999961 --tANM6ETl_M/3,-tANM6ETl_M,3,14,done,4.28249979019165,4.462500095367432,True,3.556252158937656e-15,0.25,4.255324390674593,4.449549096474829,4.202500000000001,4.282500000000001,4.4225,4.4625,0.08000000000000007,0.040000000000000036 --tANM6ETl_M/3,-tANM6ETl_M,3,15,it,4.482500076293945,4.542500019073486,True,2.5008395351864936e-14,0.7788370251655579,4.485970581662388,4.545979863534526,4.482500000000001,4.522500000000001,4.5425,4.5825000000000005,0.040000000000000036,0.040000000000000036 --tANM6ETl_M/3,-tANM6ETl_M,3,16,"before,",4.602499961853027,4.982500076293945,True,2.1828892859954152e-14,0.6798176765441895,4.602479292145233,4.978115573980364,4.602500000000001,4.602500000000001,4.982500000000001,4.982500000000001,0.0,0.0 --tANM6ETl_M/3,-tANM6ETl_M,3,17,or,5.022500038146973,5.082499980926514,True,5.056437717533904e-14,1.5747275352478027,5.0206841105147095,5.0806852891637515,5.022500000000001,5.022500000000001,5.0825000000000005,5.0825000000000005,0.0,0.0 --tANM6ETl_M/3,-tANM6ETl_M,3,18,they've,5.102499961853027,5.34250020980835,True,3.8970549335291815e-13,4.0,5.101592897531236,5.337826895494357,5.102500000000001,5.102500000000001,5.322500000000001,5.3425,0.0,0.019999999999999574 --tANM6ETl_M/3,-tANM6ETl_M,3,19,never,5.422500133514404,5.662499904632568,True,2.0569947790450085e-14,0.6406103372573853,5.422381810653897,5.662099104183884,5.4225,5.4225,5.6625000000000005,5.6625000000000005,0.0,0.0 --tANM6ETl_M/3,-tANM6ETl_M,3,20,tried,5.722499847412109,6.002500057220459,True,1.0326153248988758e-14,0.32158762216567993,5.722183877149623,6.001503992763337,5.7225,5.7225,6.0025,6.0025,0.0,0.0 --tANM6ETl_M/3,-tANM6ETl_M,3,21,it.,6.0625,6.122499942779541,True,2.0461776804175935e-12,4.0,6.063300842860167,6.130318478523356,6.062500000000001,6.062500000000001,6.1225000000000005,6.1225000000000005,0.0,0.0 --tPCytz4rww/11,-tPCytz4rww,11,0,Make,0.0024999999441206455,0.14249999821186066,True,3.090905894946594e-14,0.25,0.02169566240224484,0.17425271469887066,0.0025000000000000005,0.0425,0.14250000000000002,0.1825,0.04,0.03999999999999998 --tPCytz4rww/11,-tPCytz4rww,11,1,sure,0.18250000476837158,0.6225000023841858,True,6.222975260095076e-12,4.0,0.346787166754646,0.6374821536776674,0.1825,0.5025,0.6224999999999999,0.6825,0.31999999999999995,0.06000000000000005 --tPCytz4rww/11,-tPCytz4rww,11,2,that,0.6625000238418579,0.8224999904632568,True,3.477579552449428e-13,1.9737460613250732,0.6725399070879395,0.8375782669395493,0.6625,0.7025,0.8225,0.8825,0.040000000000000036,0.05999999999999994 --tPCytz4rww/11,-tPCytz4rww,11,3,your,0.862500011920929,1.0225000381469727,True,3.126307340515556e-15,0.25,0.8784328640568163,1.0433921603265537,0.8624999999999999,0.9225,1.0225,1.1025,0.06000000000000005,0.08000000000000007 --tPCytz4rww/11,-tPCytz4rww,11,4,using,1.0425000190734863,1.222499966621399,True,1.8500610386110866e-13,1.050026535987854,1.0729127611360898,1.2830561203794688,1.0425,1.1624999999999999,1.2225,1.4625,0.11999999999999988,0.24 --tPCytz4rww/11,-tPCytz4rww,11,5,comps,1.3025000095367432,1.5425000190734863,True,6.064278853384897e-14,0.34418612718582153,1.3432746992012874,1.6062773987725414,1.2425,1.5625,1.5025,1.8825,0.32000000000000006,0.3800000000000001 --tPCytz4rww/11,-tPCytz4rww,11,6,that,1.5625,1.8224999904632568,True,6.134831141355046e-13,3.4819042682647705,1.6472699997478626,1.8896951897898389,1.5625,1.9025,1.8225,2.0625,0.3400000000000001,0.24 --tPCytz4rww/11,-tPCytz4rww,11,7,are,1.9225000143051147,2.0625,True,5.638180792741105e-15,0.25,1.971279454556468,2.097049019461683,1.9224999999999999,2.1025,2.0625,2.2025,0.18000000000000016,0.14000000000000012 --tPCytz4rww/11,-tPCytz4rww,11,8,not,2.1024999618530273,2.302500009536743,True,1.9874132721475757e-12,4.0,2.133150452735309,2.3222142523728997,2.1025,2.2225,2.3025,2.3825,0.1200000000000001,0.07999999999999963 --tPCytz4rww/11,-tPCytz4rww,11,9,"larger,",2.502500057220459,2.8424999713897705,True,2.330519674811904e-13,1.3227171897888184,2.4520214020764155,2.820602708781465,2.4025,2.5025,2.7625,2.8425,0.10000000000000009,0.07999999999999963 --tPCytz4rww/11,-tPCytz4rww,11,10,no,3.2225000858306885,3.322499990463257,True,7.816119171159819e-14,0.4436141550540924,3.2170783747909404,3.32249684334124,3.2225,3.2225,3.3225000000000002,3.3225000000000002,0.0,0.0 --tPCytz4rww/11,-tPCytz4rww,11,11,larger,3.382499933242798,3.682499885559082,True,9.446646752602622e-15,0.25,3.382499571327774,3.6829963136388377,3.3825,3.3825,3.6825,3.6825,0.0,0.0 --tPCytz4rww/11,-tPCytz4rww,11,12,than,3.702500104904175,3.9024999141693115,True,2.853919290018818e-14,0.25,3.703456733094279,3.884414196985789,3.7025,3.7025,3.8425,3.9025,0.0,0.06000000000000005 --tPCytz4rww/11,-tPCytz4rww,11,13,twelve,3.942500114440918,4.242499828338623,True,6.64411762912008e-14,0.37709563970565796,3.9459603741824063,4.243307639989169,3.9425,3.9625,4.242500000000001,4.242500000000001,0.020000000000000018,0.0 --tPCytz4rww/11,-tPCytz4rww,11,14,hundred,4.262499809265137,4.622499942779541,True,1.7619183835439894e-13,1.0,4.263793015967037,4.62249338252602,4.2625,4.2625,4.6225000000000005,4.6225000000000005,0.0,0.0 --tPCytz4rww/11,-tPCytz4rww,11,15,square,4.662499904632568,4.982500076293945,True,3.165683318782919e-13,1.7967252731323242,4.662500502666387,4.982478809793004,4.6625000000000005,4.6625000000000005,4.982500000000001,4.982500000000001,0.0,0.0 --tPCytz4rww/11,-tPCytz4rww,11,16,feet.,5.0625,5.28249979019165,True,3.689433470104725e-13,2.0939865112304688,5.062500417509267,5.282497153233201,5.062500000000001,5.062500000000001,5.282500000000001,5.282500000000001,0.0,0.0 --tPCytz4rww/10,-tPCytz4rww,10,0,Say,0.0024999999441206455,0.12250000238418579,True,3.2502712327131533e-11,4.0,0.002505057883538294,0.1225226855817078,0.0025000000000000005,0.0025000000000000005,0.1225,0.1225,0.0,0.0 --tPCytz4rww/10,-tPCytz4rww,10,1,twenty,0.20250000059604645,0.7225000262260437,True,6.181854507458784e-12,1.105215072631836,0.20256298455497526,0.7225242384992536,0.2025,0.2025,0.7224999999999999,0.7224999999999999,0.0,0.0 --tPCytz4rww/10,-tPCytz4rww,10,2,percent,0.8025000095367432,1.2024999856948853,True,4.0030847560379446e-13,0.25,0.8175673372248227,1.202531136762618,0.8025,0.9025,1.2025,1.2025,0.09999999999999998,0.0 --tPCytz4rww/10,-tPCytz4rww,10,3,so,1.2424999475479126,1.3825000524520874,True,1.546988042224265e-13,0.25,1.2430952066521186,1.3768309486444459,1.2425,1.2425,1.3625,1.3825,0.0,0.020000000000000018 --tPCytz4rww/10,-tPCytz4rww,10,4,if,1.5824999809265137,1.722499966621399,True,2.316052731543561e-12,0.41407257318496704,1.582535696275133,1.722513322878117,1.5825,1.5825,1.7225,1.7225,0.0,0.0 --tPCytz4rww/10,-tPCytz4rww,10,5,you've,1.9424999952316284,2.2825000286102295,True,1.4418195803944656e-10,4.0,1.9519629063531054,2.282409676113536,1.9425,1.9625,2.2825,2.2825,0.020000000000000018,0.0 --tPCytz4rww/10,-tPCytz4rww,10,6,got,2.4825000762939453,2.6424999237060547,True,1.1913363524851395e-11,2.129915714263916,2.4824364558586436,2.642480769217724,2.4825,2.4825,2.6425,2.6425,0.0,0.0 --tPCytz4rww/10,-tPCytz4rww,10,7,a,2.702500104904175,2.7225000858306885,True,8.198944127790764e-12,1.4658379554748535,2.702496664722302,2.7224966647239226,2.7025,2.7025,2.7225,2.7225,0.0,0.0 --tPCytz4rww/10,-tPCytz4rww,10,8,thousand,2.822499990463257,3.2825000286102295,True,6.314457962584841e-13,0.25,2.822534476359815,3.281519597807987,2.8225,2.8225,3.2825,3.2825,0.0,0.0 --tPCytz4rww/10,-tPCytz4rww,10,9,square,3.322499990463257,3.882499933242798,True,5.894128501243712e-13,0.25,3.4688986221058005,3.8957732430891063,3.3225000000000002,3.6825,3.8825,3.9225,0.3599999999999999,0.040000000000000036 --tPCytz4rww/10,-tPCytz4rww,10,10,foot,3.9024999141693115,4.122499942779541,True,2.942341509326596e-11,4.0,3.9231015848774184,4.122296003381612,3.9025,3.9625,4.1225000000000005,4.1225000000000005,0.06000000000000005,0.0 --tPCytz4rww/10,-tPCytz4rww,10,11,condo.,4.422500133514404,4.622499942779541,True,5.004845062689389e-12,0.8947849869728088,4.422276698912244,4.637538051382122,4.4225,4.4225,4.6225000000000005,4.6625000000000005,0.0,0.040000000000000036 --tPCytz4rww/12,-tPCytz4rww,12,0,No,0.08250000327825546,0.16249999403953552,True,1.4483042586402317e-12,2.761003017425537,0.08114481503602712,0.16217620079296532,0.0625,0.0825,0.1625,0.1625,0.020000000000000004,0.0 --tPCytz4rww/12,-tPCytz4rww,12,1,less,0.2224999964237213,0.4625000059604645,True,4.10721673685388e-12,4.0,0.22219314838082402,0.4616554631769186,0.2225,0.2225,0.4625,0.4625,0.0,0.0 --tPCytz4rww/12,-tPCytz4rww,12,2,than,0.5024999976158142,0.6825000047683716,True,5.063582474325312e-13,0.9653059244155884,0.5017505310429379,0.6818042885306567,0.5025,0.5025,0.6825,0.6825,0.0,0.0 --tPCytz4rww/12,-tPCytz4rww,12,3,eight,0.7024999856948853,1.0425000190734863,True,9.050614532997436e-13,1.7253814935684204,0.7020298754293801,1.0413866100393672,0.7025,0.7025,1.0425,1.0425,0.0,0.0 --tPCytz4rww/12,-tPCytz4rww,12,4,hundred,1.3624999523162842,1.7424999475479126,True,1.8136402481824104e-13,0.34574684500694275,1.3600963696569792,1.740637256117597,1.3625,1.3625,1.7425,1.7425,0.0,0.0 --tPCytz4rww/12,-tPCytz4rww,12,5,squire,1.7825000286102295,2.2225000858306885,True,1.852836894328247e-12,3.532191753387451,1.7936826033289333,2.203577332640142,1.7825,1.8225,2.0225,2.2225,0.040000000000000036,0.20000000000000018 --tPCytz4rww/12,-tPCytz4rww,12,6,feet,2.6024999618530273,2.7825000286102295,True,1.4244164658547276e-12,2.7154641151428223,2.562656419923969,2.737386374888778,2.0425,2.6225,2.2225,2.7825,0.5800000000000001,0.56 --tPCytz4rww/12,-tPCytz4rww,12,7,and,2.822499990463257,2.922499895095825,True,7.50539994737176e-12,4.0,2.8040084810806176,2.9083167912758485,2.6625,2.8225,2.8825,2.9225,0.1599999999999997,0.040000000000000036 --tPCytz4rww/12,-tPCytz4rww,12,8,going,2.9825000762939453,3.242500066757202,True,1.8712631270900726e-12,3.567318916320801,2.972907476639749,3.2485900463543764,2.9225,2.9825,3.1825,3.3425,0.06000000000000005,0.1599999999999997 --tPCytz4rww/12,-tPCytz4rww,12,9,to,3.322499990463257,3.4625000953674316,True,1.7221121718317273e-13,0.3282982110977173,3.3804194320253904,3.4819767729461604,3.2425,3.6425,3.3425,3.7225,0.3999999999999999,0.38000000000000034 --tPCytz4rww/12,-tPCytz4rww,12,10,similar,3.6424999237060547,4.022500038146973,True,8.151455313694378e-13,1.5539685487747192,3.6554667644090957,4.022687363378376,3.6025,3.7625,3.9625,4.062500000000001,0.16000000000000014,0.10000000000000098 --tPCytz4rww/12,-tPCytz4rww,12,11,"in,",4.042500019073486,4.122499942779541,True,6.854618001678192e-12,4.0,4.062473519113548,4.135646046857629,4.0425,4.1025,4.1225000000000005,4.1625000000000005,0.05999999999999961,0.040000000000000036 --tPCytz4rww/12,-tPCytz4rww,12,12,similar,4.942500114440918,5.322500228881836,True,3.7164002886398706e-13,0.7084832191467285,4.856473555076607,5.325159731998561,4.202500000000001,4.942500000000001,5.322500000000001,5.322500000000001,0.7400000000000002,0.0 --tPCytz4rww/12,-tPCytz4rww,12,13,with,5.582499980926514,5.78249979019165,True,5.430205913289736e-14,0.25,5.565606085452562,5.774287522003375,5.4625,5.5825000000000005,5.742500000000001,5.782500000000001,0.1200000000000001,0.040000000000000036 --tPCytz4rww/12,-tPCytz4rww,12,14,bedrooms,5.922500133514404,6.322500228881836,True,2.7115378627325104e-13,0.5169193148612976,5.91833513197217,6.321445991446334,5.9225,5.9225,6.322500000000001,6.322500000000001,0.0,0.0 --tPCytz4rww/12,-tPCytz4rww,12,15,and,6.422500133514404,6.582499980926514,True,1.5096515617457618e-12,2.8779537677764893,6.415225660149443,6.570339834181551,6.3825,6.4225,6.5025,6.5825000000000005,0.040000000000000036,0.08000000000000007 --tPCytz4rww/12,-tPCytz4rww,12,16,bathrooms,6.662499904632568,7.102499961853027,True,9.588660296539278e-14,0.25,6.649534180591883,7.103515746095183,6.5825000000000005,6.6625000000000005,7.102500000000001,7.102500000000001,0.08000000000000007,0.0 --tPCytz4rww/12,-tPCytz4rww,12,17,as,7.182499885559082,7.28249979019165,True,2.5051279952358063e-13,0.47756996750831604,7.182713277688271,7.281488350142335,7.1825,7.1825,7.282500000000001,7.282500000000001,0.0,0.0 --tPCytz4rww/12,-tPCytz4rww,12,18,well,7.882500171661377,8.082500457763672,True,1.5330628205714042e-13,0.2922584116458893,7.743203575778251,8.06287017488467,7.3025,7.8825,8.022499999999999,8.0825,0.5800000000000001,0.0600000000000005 --tPCytz4rww/12,-tPCytz4rww,12,19,and,8.242500305175781,8.342499732971191,True,1.736000666135995e-13,0.3309458792209625,8.195382128579398,8.336167495849628,8.1225,8.2425,8.3025,8.362499999999999,0.11999999999999922,0.05999999999999872 --tPCytz4rww/12,-tPCytz4rww,12,20,hopefully,8.362500190734863,8.762499809265137,True,5.427562696155852e-13,1.034693956375122,8.38126225674004,8.800728012660858,8.362499999999999,8.4225,8.7625,8.862499999999999,0.0600000000000005,0.09999999999999964 --tPCytz4rww/12,-tPCytz4rww,12,21,the,8.842499732971191,9.22249984741211,True,1.5777048450234948e-13,0.30076882243156433,8.939716417127721,9.233476473717799,8.8225,9.1425,9.2225,9.3025,0.3200000000000003,0.08000000000000007 --tPCytz4rww/12,-tPCytz4rww,12,22,complexes,9.40250015258789,9.862500190734863,True,4.707200883420637e-13,0.8973664045333862,9.400885044089927,9.865401598848464,9.4025,9.4025,9.862499999999999,9.9025,0.0,0.040000000000000924 --tPCytz4rww/12,-tPCytz4rww,12,23,have,9.942500114440918,10.102499961853027,True,2.9300275313642876e-12,4.0,9.941644931466874,10.10126370487901,9.942499999999999,9.942499999999999,10.1025,10.1025,0.0,0.0 --tPCytz4rww/12,-tPCytz4rww,12,24,similar,10.162500381469727,10.542499542236328,True,1.139832179379921e-13,0.25,10.163551445389935,10.604138254114487,10.1625,10.1625,10.5425,10.7025,0.0,0.16000000000000014 --tPCytz4rww/12,-tPCytz4rww,12,25,amenities.,10.6225004196167,11.602499961853027,True,3.5955082227506763e-12,4.0,10.709443501320298,11.61568048027064,10.6225,10.8425,11.5425,11.7225,0.21999999999999886,0.17999999999999972 --tPCytz4rww/16,-tPCytz4rww,16,0,So,0.5824999809265137,0.7225000262260437,True,1.0900147971726337e-11,2.107679605484009,0.5824988545142109,0.7225003068930176,0.5824999999999999,0.5824999999999999,0.7224999999999999,0.7224999999999999,0.0,0.0 --tPCytz4rww/16,-tPCytz4rww,16,1,make,0.8824999928474426,1.0824999809265137,True,8.273993469531948e-12,1.5998799800872803,0.8873053054868005,1.0895852394390597,0.8624999999999999,0.9624999999999999,1.0825,1.1425,0.09999999999999998,0.06000000000000005 --tPCytz4rww/16,-tPCytz4rww,16,2,sure,1.1825000047683716,1.3624999523162842,True,4.89173209317767e-13,0.25,1.1824972875537523,1.3625090418290506,1.1824999999999999,1.1824999999999999,1.3625,1.3625,0.0,0.0 --tPCytz4rww/16,-tPCytz4rww,16,3,to,1.4824999570846558,1.662500023841858,True,8.923322150633517e-13,0.25,1.4824959809329938,1.6625015961399936,1.4825,1.4825,1.6625,1.6625,0.0,0.0 --tPCytz4rww/16,-tPCytz4rww,16,4,get,1.9225000143051147,2.0425000190734863,True,2.0692742224576177e-12,0.4001200199127197,1.9224425845184057,2.0424873809086117,1.9224999999999999,1.9224999999999999,2.0425,2.0425,0.0,0.0 --tPCytz4rww/16,-tPCytz4rww,16,5,a,2.1024999618530273,2.122499942779541,True,1.6197307384224757e-11,3.1319515705108643,2.1024966862255567,2.122496686225557,2.1025,2.1025,2.1225,2.1225,0.0,0.0 --tPCytz4rww/16,-tPCytz4rww,16,6,through,2.202500104904175,2.5625,True,6.382161509346784e-13,0.25,2.194829264614116,2.557246651427563,2.1425,2.2025,2.5025,2.5625,0.06000000000000005,0.06000000000000005 --tPCytz4rww/16,-tPCytz4rww,16,7,or,3.1424999237060547,3.2225000858306885,True,2.622704137200671e-11,4.0,3.1424300748546017,3.2224545318159237,3.1425,3.1425,3.2225,3.2225,0.0,0.0 --tPCytz4rww/16,-tPCytz4rww,16,8,to,4.262499809265137,4.34250020980835,True,9.882743359562393e-14,0.25,4.210863172668486,4.341936445692636,3.9225,4.2625,4.3425,4.3425,0.3400000000000003,0.0 --tPCytz4rww/16,-tPCytz4rww,16,9,do,4.422500133514404,4.522500038146973,True,1.4996654959520406e-11,2.8997905254364014,4.422508837940596,4.5225076494860605,4.4225,4.4225,4.522500000000001,4.522500000000001,0.0,0.0 --tPCytz4rww/16,-tPCytz4rww,16,10,a,4.662499904632568,4.682499885559082,True,2.231034974820023e-11,4.0,4.6619831203681485,4.681983120368152,4.6625000000000005,4.6625000000000005,4.6825,4.6825,0.0,0.0 --tPCytz4rww/16,-tPCytz4rww,16,11,through,4.722499847412109,5.102499961853027,True,6.987023806748205e-13,0.25,4.722842072869845,5.102508213245117,4.7225,4.7225,5.102500000000001,5.102500000000001,0.0,0.0 --tPCytz4rww/16,-tPCytz4rww,16,12,cleaning,5.122499942779541,5.542500019073486,True,6.977411812388035e-13,0.25,5.123908908733183,5.544329216386563,5.1225000000000005,5.1225000000000005,5.5425,5.5425,0.0,0.0 --tPCytz4rww/16,-tPCytz4rww,16,13,of,5.582499980926514,5.862500190734863,True,1.382491083418147e-11,2.6732192039489746,5.616153867927133,5.8758597493577955,5.5825000000000005,5.8425,5.862500000000001,5.9625,0.2599999999999998,0.09999999999999964 --tPCytz4rww/16,-tPCytz4rww,16,14,the,6.262499809265137,6.502500057220459,True,1.5708401246428139e-10,4.0,6.266147318112281,6.501861147995156,6.2625,6.322500000000001,6.5025,6.5025,0.0600000000000005,0.0 --tPCytz4rww/16,-tPCytz4rww,16,15,property.,6.5625,7.122499942779541,True,1.007599602712017e-12,0.25,6.562252572276781,7.122499604680712,6.562500000000001,6.562500000000001,7.1225000000000005,7.1225000000000005,0.0,0.0 --tPCytz4rww/18,-tPCytz4rww,18,0,Do,0.5425000190734863,0.6424999833106995,True,6.279769673017688e-12,4.0,0.4577015282761664,0.5637259104571192,0.0425,0.5425,0.10250000000000001,0.6425,0.5,0.5399999999999999 --tPCytz4rww/18,-tPCytz4rww,18,1,so,0.762499988079071,0.9225000143051147,True,9.772651438089142e-13,4.0,0.7297637425083854,0.8808360734940381,0.5425,0.7625,0.6425,0.9225,0.21999999999999997,0.28 --tPCytz4rww/18,-tPCytz4rww,18,2,and,1.5225000381469727,1.622499942779541,True,3.8262928524386564e-13,2.566894769668579,1.3848902857859928,1.5188761214324742,0.7025,1.5225,0.9225,1.6225,0.82,0.7000000000000001 --tPCytz4rww/18,-tPCytz4rww,18,3,as,1.7024999856948853,1.7625000476837158,True,1.1480210228634324e-13,0.7701577544212341,1.6801337977048072,1.7422092862293954,1.5625,1.7025,1.6225,1.7625,0.1399999999999999,0.1399999999999999 --tPCytz4rww/18,-tPCytz4rww,18,4,well,1.8224999904632568,2.1024999618530273,True,4.317257136640315e-14,0.2896261513233185,1.8047449158844084,2.0739518481040995,1.7025,1.8225,1.9425,2.1025,0.1200000000000001,0.16000000000000014 --tPCytz4rww/18,-tPCytz4rww,18,5,you'll,2.5625,2.7825000286102295,True,4.398781686121289e-11,4.0,2.5010674825755013,2.7816743887812576,2.1025,2.5625,2.7825,2.7825,0.45999999999999996,0.0 --tPCytz4rww/18,-tPCytz4rww,18,6,also,2.822499990463257,3.0625,True,1.0343581460098283e-13,0.6939062476158142,2.8229435101245044,3.0581425038034475,2.8025,2.8425,3.0225,3.0825,0.03999999999999959,0.06000000000000005 --tPCytz4rww/18,-tPCytz4rww,18,7,want,3.1424999237060547,3.322499990463257,True,7.557796314510475e-15,0.25,3.14970832157837,3.3279337466346512,3.1425,3.2025,3.3225000000000002,3.3625,0.06000000000000005,0.03999999999999959 --tPCytz4rww/18,-tPCytz4rww,18,8,to,3.4024999141693115,3.5425000190734863,True,1.7010866456765306e-13,1.1411856412887573,3.4025001233819,3.5425000693102824,3.4025,3.4025,3.5425,3.5425,0.0,0.0 --tPCytz4rww/18,-tPCytz4rww,18,9,remove,3.622499942779541,3.942500114440918,True,5.3244467347482796e-14,0.3571941554546356,3.626808956541107,3.9453705442557396,3.6225,3.6825,3.9425,3.9825,0.06000000000000005,0.040000000000000036 --tPCytz4rww/18,-tPCytz4rww,18,10,any,3.9625000953674316,4.102499961853027,True,1.28017523881932e-13,0.8588143587112427,3.9746334399483496,4.104266931525665,3.9625,4.0025,4.1025,4.1025,0.04000000000000048,0.0 --tPCytz4rww/18,-tPCytz4rww,18,11,clutter,4.222499847412109,4.662499904632568,True,2.1503506847332307e-14,0.25,4.215421975132926,4.663287259592333,4.1425,4.2225,4.6625000000000005,4.6825,0.08000000000000007,0.019999999999999574 --tPCytz4rww/18,-tPCytz4rww,18,12,from,4.84250020980835,4.982500076293945,True,5.341139314683774e-13,3.5831398963928223,4.837114731944649,4.977657863914085,4.8425,4.8425,4.982500000000001,4.982500000000001,0.0,0.0 --tPCytz4rww/18,-tPCytz4rww,18,13,that,5.002500057220459,5.142499923706055,True,5.396275382785328e-16,0.25,4.999508925414773,5.139697183402384,5.0025,5.0025,5.1425,5.1425,0.0,0.0 --tPCytz4rww/18,-tPCytz4rww,18,14,you've,5.162499904632568,5.34250020980835,True,2.645488515751193e-11,4.0,5.16074853713978,5.342500661315979,5.1625000000000005,5.1625000000000005,5.3425,5.3425,0.0,0.0 --tPCytz4rww/18,-tPCytz4rww,18,15,accumulated.,5.402500152587891,6.522500038146973,True,8.827004340135336e-13,4.0,5.400102213934783,6.512170678859689,5.3825,5.4625,6.4625,6.522500000000001,0.08000000000000007,0.0600000000000005 --vxjVxOeScU/4,-vxjVxOeScU,4,0,You're,0.0024999999441206455,0.32249999046325684,True,1.5470193485619954e-12,3.368727445602417,0.0029563428740617594,0.29346729925949566,0.0025000000000000005,0.0025000000000000005,0.2025,0.4225,0.0,0.21999999999999997 --vxjVxOeScU/4,-vxjVxOeScU,4,1,going,0.5224999785423279,0.7024999856948853,True,9.600089820316349e-13,2.090477228164673,0.5220072174639193,0.7031866953765705,0.5225,0.5225,0.7025,0.7025,0.0,0.0 --vxjVxOeScU/4,-vxjVxOeScU,4,2,to,0.7225000262260437,0.7825000286102295,True,2.1261818531920912e-13,0.46298885345458984,0.7239908232403981,0.7843177483023872,0.7224999999999999,0.7224999999999999,0.7825,0.7825,0.0,0.0 --vxjVxOeScU/4,-vxjVxOeScU,4,3,talk,0.8424999713897705,1.122499942779541,True,3.087919934400933e-14,0.25,0.8273659506445371,1.0905327934600164,0.8025,0.8424999999999999,1.0425,1.1225,0.039999999999999925,0.08000000000000007 --vxjVxOeScU/4,-vxjVxOeScU,4,4,about,1.1825000047683716,1.6024999618530273,True,6.140968809853486e-13,1.3372328281402588,1.1852211848482213,1.6047478626253122,1.1824999999999999,1.1824999999999999,1.6025,1.6025,0.0,0.0 --vxjVxOeScU/4,-vxjVxOeScU,4,5,their,1.6425000429153442,2.0625,True,6.062020409437633e-15,0.25,1.6640391436621444,2.0694865731735606,1.6425,1.8825,2.0625,2.1025,0.24,0.040000000000000036 --vxjVxOeScU/4,-vxjVxOeScU,4,6,"life,",2.1024999618530273,2.5425000190734863,True,1.918054690769333e-12,4.0,2.140782386335001,2.579308133483268,2.1025,2.2025,2.5425,2.6425,0.10000000000000009,0.10000000000000009 --vxjVxOeScU/4,-vxjVxOeScU,4,7,their,2.622499942779541,3.182499885559082,True,1.0584406818343016e-14,0.25,2.7224969696046233,3.1752309276097845,2.6225,2.9625,3.1425,3.1825,0.33999999999999986,0.040000000000000036 --vxjVxOeScU/4,-vxjVxOeScU,4,8,marriage,3.242500066757202,3.822499990463257,True,9.971537823423061e-15,0.25,3.241210169650607,3.825199297988689,3.1825,3.2425,3.8225000000000002,3.8225000000000002,0.06000000000000005,0.0 --vxjVxOeScU/4,-vxjVxOeScU,4,9,and,4.462500095367432,4.5625,True,1.410027368302369e-12,3.0704190731048584,4.452967302117755,4.640251380407333,4.3825,4.5025,4.522500000000001,4.782500000000001,0.1200000000000001,0.2599999999999998 --vxjVxOeScU/4,-vxjVxOeScU,4,10,usually,4.762499809265137,5.482500076293945,True,1.6004079572001784e-12,3.4849843978881836,4.851114393665739,5.482486596984726,4.7625,5.0025,5.482500000000001,5.482500000000001,0.2400000000000002,0.0 --vxjVxOeScU/4,-vxjVxOeScU,4,11,how,5.522500038146973,5.722499847412109,True,4.592296052978451e-13,1.0,5.525640963404545,5.725972052153117,5.522500000000001,5.522500000000001,5.7225,5.7225,0.0,0.0 --vxjVxOeScU/4,-vxjVxOeScU,4,12,amazing,5.902500152587891,6.502500057220459,True,6.916904657545964e-13,1.506197452545166,5.9024997564652315,6.502508539881368,5.902500000000001,5.902500000000001,6.5025,6.5025,0.0,0.0 --vxjVxOeScU/4,-vxjVxOeScU,4,13,it,6.662499904632568,6.722499847412109,True,2.1100000002424735e-13,0.4594651460647583,6.662473520526038,6.722503456624384,6.6625000000000005,6.6625000000000005,6.7225,6.7225,0.0,0.0 --vxjVxOeScU/4,-vxjVxOeScU,4,14,is,6.84250020980835,6.902500152587891,True,6.980565807329772e-16,0.25,6.834745016706655,6.902340309975699,6.7625,6.8425,6.902500000000001,6.902500000000001,0.08000000000000007,0.0 --vxjVxOeScU/4,-vxjVxOeScU,4,15,that,6.982500076293945,7.162499904632568,True,1.3848431678741696e-13,0.30155789852142334,6.982535263961875,7.162875631455382,6.982500000000001,6.982500000000001,7.1625000000000005,7.1625000000000005,0.0,0.0 --vxjVxOeScU/4,-vxjVxOeScU,4,16,they've,7.182499885559082,7.502500057220459,True,1.4167369534467955e-12,3.0850296020507812,7.18830786025921,7.499636426891534,7.1825,7.202500000000001,7.4625,7.5025,0.020000000000000462,0.040000000000000036 --vxjVxOeScU/4,-vxjVxOeScU,4,17,stayed,7.522500038146973,7.862500190734863,True,2.276652174074134e-13,0.4957546591758728,7.5225191866663135,7.8628040961908825,7.522500000000001,7.522500000000001,7.862500000000001,7.862500000000001,0.0,0.0 --vxjVxOeScU/4,-vxjVxOeScU,4,18,together,7.922500133514404,8.482500076293945,True,7.508617208898394e-13,1.635046362876892,7.951205794831128,8.482846561288776,7.9225,7.982500000000001,8.4825,8.4825,0.0600000000000005,0.0 --vxjVxOeScU/4,-vxjVxOeScU,4,19,this,8.5625,8.782500267028809,True,1.077622973494341e-11,4.0,8.562488552433173,8.782505471531966,8.5625,8.5625,8.782499999999999,8.782499999999999,0.0,0.0 --vxjVxOeScU/4,-vxjVxOeScU,4,20,long.,8.862500190734863,9.022500038146973,True,1.3307234884873433e-14,0.25,8.84487426972022,9.02198370726463,8.8225,8.862499999999999,9.022499999999999,9.022499999999999,0.03999999999999915,0.0 --wMB_hJL-3o/7,-wMB_hJL-3o,7,0,So,0.6025000214576721,0.8224999904632568,True,4.930794271149064e-13,4.0,0.602499648212456,0.8224999940402619,0.6024999999999999,0.6024999999999999,0.8225,0.8225,0.0,0.0 --wMB_hJL-3o/7,-wMB_hJL-3o,7,1,if,0.9424999952316284,1.1425000429153442,True,3.520454937224089e-14,2.2842962741851807,0.9495859338563555,1.1379864720902402,0.9425,0.9425,1.1225,1.1425,0.0,0.020000000000000018 --wMB_hJL-3o/7,-wMB_hJL-3o,7,2,you,1.2024999856948853,1.3224999904632568,True,8.520083340831774e-15,0.5528374910354614,1.1899086153822664,1.3046461227483739,1.1624999999999999,1.2025,1.2625,1.3425,0.040000000000000036,0.08000000000000007 --wMB_hJL-3o/7,-wMB_hJL-3o,7,3,have,1.3825000524520874,1.5225000381469727,True,1.1133222165352064e-13,4.0,1.3555953310480724,1.5160767063261227,1.3225,1.3825,1.5025,1.5225,0.06000000000000005,0.020000000000000018 --wMB_hJL-3o/7,-wMB_hJL-3o,7,4,a,1.5425000190734863,1.5625,True,4.2741949302788074e-13,4.0,1.5406014206323078,1.5606014206323082,1.5225,1.5425,1.5425,1.5625,0.020000000000000018,0.020000000000000018 --wMB_hJL-3o/7,-wMB_hJL-3o,7,5,loved,1.6024999618530273,1.8224999904632568,True,2.6587540762762485e-12,4.0,1.6017163722664503,1.8216123303039624,1.6025,1.6025,1.8225,1.8225,0.0,0.0 --wMB_hJL-3o/7,-wMB_hJL-3o,7,6,one,1.902500033378601,2.002500057220459,True,6.939063734013153e-15,0.4502508342266083,1.896415540653591,2.000333519800293,1.8425,1.9025,1.9825,2.0025,0.06000000000000005,0.020000000000000018 --wMB_hJL-3o/7,-wMB_hJL-3o,7,7,who,2.0225000381469727,2.1624999046325684,True,2.149073570807008e-15,0.25,2.0224997179877056,2.149062987763053,2.0225,2.0225,2.1225,2.1625,0.0,0.040000000000000036 --wMB_hJL-3o/7,-wMB_hJL-3o,7,8,is,2.202500104904175,2.262500047683716,True,1.8062620152294213e-14,1.17201828956604,2.1850443997523645,2.2531201231317675,2.1425,2.2025,2.2225,2.2825,0.06000000000000005,0.06000000000000005 --wMB_hJL-3o/7,-wMB_hJL-3o,7,9,depressed,2.302500009536743,2.9024999141693115,True,8.335262128169425e-16,0.25,2.302498985661637,2.8908095885097147,2.3025,2.3025,2.8625,2.9025,0.0,0.040000000000000036 --wMB_hJL-3o/7,-wMB_hJL-3o,7,10,those,2.922499895095825,3.4024999141693115,True,2.3576904588807485e-14,1.5298203229904175,2.922649231893573,3.40250415475127,2.9225,2.9225,3.4025,3.4025,0.0,0.0 --wMB_hJL-3o/7,-wMB_hJL-3o,7,11,are,3.442500114440918,3.5625,True,4.111901791281625e-14,2.668064832687378,3.4426174034431227,3.5625004913768072,3.4425,3.4425,3.5625,3.5625,0.0,0.0 --wMB_hJL-3o/7,-wMB_hJL-3o,7,12,some,3.6024999618530273,3.762500047683716,True,6.959169839785423e-14,4.0,3.6024968346111734,3.762500000089275,3.6025,3.6025,3.7625,3.7625,0.0,0.0 --wMB_hJL-3o/7,-wMB_hJL-3o,7,13,of,3.7825000286102295,3.8424999713897705,True,8.037168681778416e-15,0.5215029120445251,3.782500000350712,3.8425000004085677,3.7825,3.7825,3.8425,3.8425,0.0,0.0 --wMB_hJL-3o/7,-wMB_hJL-3o,7,14,the,3.862499952316284,3.9625000953674316,True,9.505426603977334e-15,0.6167728900909424,3.8625000018810254,3.9625000861085344,3.8625,3.8625,3.9625,3.9625,0.0,0.0 --wMB_hJL-3o/7,-wMB_hJL-3o,7,15,things,4.022500038146973,4.28249979019165,True,2.8207193254314172e-14,1.8302631378173828,4.02228486995236,4.282719674458678,4.022500000000001,4.022500000000001,4.282500000000001,4.282500000000001,0.0,0.0 --wMB_hJL-3o/7,-wMB_hJL-3o,7,16,that,4.302499771118164,4.442500114440918,True,2.5476262894126795e-15,0.25,4.317388672273269,4.4650042095716405,4.3025,4.3425,4.442500000000001,4.5025,0.040000000000000036,0.05999999999999961 --wMB_hJL-3o/7,-wMB_hJL-3o,7,17,you,4.522500038146973,4.622499942779541,True,1.6509219537028477e-15,0.25,4.522330946791593,4.623047680043856,4.522500000000001,4.522500000000001,4.6225000000000005,4.6225000000000005,0.0,0.0 --wMB_hJL-3o/7,-wMB_hJL-3o,7,18,should,4.662499904632568,4.882500171661377,True,7.711374716913349e-16,0.25,4.662444498188476,4.892354900163382,4.6625000000000005,4.6625000000000005,4.8825,4.902500000000001,0.0,0.020000000000000462 --wMB_hJL-3o/7,-wMB_hJL-3o,7,19,think,4.922500133514404,5.162499904632568,True,6.412755661775252e-14,4.0,4.922610088256987,5.162437694966212,4.9225,4.9225,5.1625000000000005,5.1625000000000005,0.0,0.0 --wMB_hJL-3o/7,-wMB_hJL-3o,7,20,about,5.182499885559082,5.482500076293945,True,1.2760483587750254e-14,0.8279817700386047,5.182502383872996,5.482478605735311,5.1825,5.1825,5.482500000000001,5.482500000000001,0.0,0.0 --wMB_hJL-3o/7,-wMB_hJL-3o,7,21,doing.,5.502500057220459,5.942500114440918,True,5.4805903658440016e-17,0.25,5.502500038298437,5.9373994065594875,5.5025,5.5025,5.862500000000001,5.9625,0.0,0.09999999999999964 --wny0OAz3g8/1,-wny0OAz3g8,1,0,And,0.0625,0.16249999403953552,True,4.102848025515013e-14,0.25,0.06047791614036171,0.1625861933013224,0.0625,0.0625,0.1625,0.1625,0.0,0.0 --wny0OAz3g8/1,-wny0OAz3g8,1,1,because,0.2224999964237213,0.7225000262260437,True,1.2541806785823506e-12,4.0,0.22249961554408024,0.7191211883038924,0.2225,0.2225,0.6825,0.7224999999999999,0.0,0.039999999999999925 --wny0OAz3g8/1,-wny0OAz3g8,1,2,they,0.762499988079071,0.9225000143051147,True,5.174728917936577e-13,1.7670706510543823,0.7614318724074157,0.9217152166737397,0.7625,0.7625,0.9225,0.9225,0.0,0.0 --wny0OAz3g8/1,-wny0OAz3g8,1,3,couldn’t,0.9624999761581421,1.3224999904632568,True,1.1262601094796931e-12,3.8459622859954834,0.9657010687822808,1.3224324547627764,0.9624999999999999,1.0225,1.3225,1.3225,0.06000000000000005,0.0 --wny0OAz3g8/1,-wny0OAz3g8,1,4,join,1.3624999523162842,1.5824999809265137,True,9.85640280330713e-13,3.3657724857330322,1.3624999986916286,1.564069483231479,1.3625,1.3625,1.5225,1.5825,0.0,0.06000000000000005 --wny0OAz3g8/1,-wny0OAz3g8,1,5,"unions,",1.7024999856948853,2.002500057220459,True,9.332146871671859e-14,0.3186749219894409,1.7022222882961973,2.0023825938707542,1.7025,1.7025,2.0025,2.0025,0.0,0.0 --wny0OAz3g8/1,-wny0OAz3g8,1,6,many,2.1624999046325684,2.322499990463257,True,2.7132393554119005e-12,4.0,2.162479380379709,2.3224794737033037,2.1625,2.1625,2.3225,2.3225,0.0,0.0 --wny0OAz3g8/1,-wny0OAz3g8,1,7,Black,2.362499952316284,2.5824999809265137,True,1.329381618892303e-14,0.25,2.3624801795036876,2.58248096295503,2.3625,2.3625,2.5825,2.5825,0.0,0.0 --wny0OAz3g8/1,-wny0OAz3g8,1,8,workers,2.6024999618530273,2.9024999141693115,True,5.2922337329510197e-14,0.25,2.602482919026416,2.9021214065219594,2.6025,2.6025,2.9025,2.9025,0.0,0.0 --wny0OAz3g8/1,-wny0OAz3g8,1,9,couldn’t,2.922499895095825,3.202500104904175,True,6.70556167016445e-13,2.289820671081543,2.9221269767762283,3.2024805980770332,2.9225,2.9225,3.2025,3.2025,0.0,0.0 --wny0OAz3g8/1,-wny0OAz3g8,1,10,get,3.242500066757202,3.3424999713897705,True,2.4445779127639684e-14,0.25,3.2424999997519612,3.3425003277495025,3.2425,3.2425,3.3425,3.3425,0.0,0.0 --wny0OAz3g8/1,-wny0OAz3g8,1,11,manufacturing,3.362499952316284,4.002500057220459,True,1.1555361702220157e-13,0.39459341764450073,3.362711746755879,4.003943023298609,3.3625,3.3625,4.0025,4.022500000000001,0.0,0.020000000000000462 --wny0OAz3g8/1,-wny0OAz3g8,1,12,or,4.042500019073486,4.102499961853027,True,1.3667748573545357e-12,4.0,4.042501825771753,4.102502245324265,4.0425,4.0425,4.1025,4.1025,0.0,0.0 --wny0OAz3g8/1,-wny0OAz3g8,1,13,trade,4.162499904632568,4.362500190734863,True,2.0616414323870562e-14,0.25,4.157861064149656,4.35788689791687,4.1225000000000005,4.1625000000000005,4.322500000000001,4.362500000000001,0.040000000000000036,0.040000000000000036 --wny0OAz3g8/1,-wny0OAz3g8,1,14,work,4.382500171661377,4.542500019073486,True,5.308752315378489e-15,0.25,4.3896416702266565,4.542659962096714,4.3425,4.402500000000001,4.5425,4.5425,0.0600000000000005,0.0 --wny0OAz3g8/1,-wny0OAz3g8,1,15,–,nan,nan,False,0.0,nan,nan,nan,nan,nan,nan,nan,nan,nan --wny0OAz3g8/1,-wny0OAz3g8,1,16,which,4.622499942779541,4.822500228881836,True,1.5271720282957705e-15,0.25,4.622532694722632,4.8226636212397045,4.6225000000000005,4.6225000000000005,4.822500000000001,4.822500000000001,0.0,0.0 --wny0OAz3g8/1,-wny0OAz3g8,1,17,paid,4.862500190734863,5.042500019073486,True,1.2096574826883644e-12,4.0,4.8626972941115385,5.042674934174243,4.862500000000001,4.862500000000001,5.0425,5.0425,0.0,0.0 --wny0OAz3g8/1,-wny0OAz3g8,1,18,much,5.082499980926514,5.28249979019165,True,3.8547794513690836e-13,1.3163331747055054,5.110245524980024,5.306652598313615,5.0825000000000005,5.1625000000000005,5.282500000000001,5.3425,0.08000000000000007,0.05999999999999961 --wny0OAz3g8/1,-wny0OAz3g8,1,19,better,5.382500171661377,5.702499866485596,True,1.6741794243795537e-14,0.25,5.3826235445812465,5.702633447017242,5.3825,5.3825,5.702500000000001,5.702500000000001,0.0,0.0 --wny0OAz3g8/1,-wny0OAz3g8,1,20,than,5.84250020980835,6.042500019073486,True,2.0020649634661103e-13,0.6836667656898499,5.8132744013990765,6.02222844530872,5.782500000000001,5.8425,6.0025,6.0425,0.05999999999999961,0.040000000000000036 --wny0OAz3g8/1,-wny0OAz3g8,1,21,service,6.102499961853027,6.482500076293945,True,4.1255077153946884e-13,1.4087817668914795,6.104189832791148,6.482308960960844,6.102500000000001,6.102500000000001,6.482500000000001,6.482500000000001,0.0,0.0 --wny0OAz3g8/1,-wny0OAz3g8,1,22,work,6.522500038146973,6.722499847412109,True,1.1393435023557275e-12,3.890639543533325,6.522533906902053,6.722653624861335,6.522500000000001,6.522500000000001,6.7225,6.7225,0.0,0.0 --wny0OAz3g8/0,-wny0OAz3g8,0,0,trade,0.4025000035762787,0.6825000047683716,True,6.750676840444614e-12,4.0,0.3219886038225564,0.6163855182678646,0.0425,0.4425,0.5025,0.7224999999999999,0.4,0.21999999999999997 --wny0OAz3g8/0,-wny0OAz3g8,0,1,labor,0.762499988079071,0.9825000166893005,True,2.737547818640329e-12,2.004483222961426,0.6723732232751013,0.8851323232237341,0.5225,0.7825,0.7224999999999999,0.9824999999999999,0.26,0.26 --wny0OAz3g8/0,-wny0OAz3g8,0,2,unions,1.1024999618530273,1.3424999713897705,True,1.97636991407929e-13,0.25,0.9698868422267436,1.2332032969798863,0.7625,1.1025,1.0625,1.3425,0.3400000000000001,0.28 --wny0OAz3g8/0,-wny0OAz3g8,0,3,didn’t,1.3825000524520874,1.6825000047683716,True,1.3657125560659344e-12,1.0,1.2886744936782788,1.5570604996248456,1.1425,1.3825,1.3625,1.6824999999999999,0.24,0.31999999999999984 --wny0OAz3g8/0,-wny0OAz3g8,0,4,allow,1.722499966621399,1.9424999952316284,True,7.948464342223335e-14,0.25,1.597575059821635,1.8485178438401406,1.3825,1.7625,1.6824999999999999,1.9825,0.3799999999999999,0.30000000000000004 --wny0OAz3g8/0,-wny0OAz3g8,0,5,Black,2.002500057220459,2.2825000286102295,True,1.8220999795787174e-12,1.3341753482818604,1.9280555178208747,2.2017594206098794,1.7225,2.0025,1.9425,2.2825,0.28,0.3400000000000003 --wny0OAz3g8/0,-wny0OAz3g8,0,6,workers,2.3424999713897705,2.762500047683716,True,2.0082564354973603e-13,0.25,2.278583747946665,2.7073076409000514,2.0025,2.4025,2.4225,2.8825,0.3999999999999999,0.45999999999999996 --wny0OAz3g8/0,-wny0OAz3g8,0,7,to,2.822499990463257,2.882499933242798,True,1.7081647240343306e-13,0.25,2.795627903779211,2.867191431881903,2.4825,2.9225,2.6225,2.9825,0.43999999999999995,0.3599999999999999 --wny0OAz3g8/0,-wny0OAz3g8,0,8,join,2.9625000953674316,3.202500104904175,True,2.8858948650928307e-12,2.113105535507202,2.9688315656033817,3.2127652271035108,2.9225,3.0625,3.2025,3.2425,0.14000000000000012,0.040000000000000036 --wny0OAz3g8/3,-wny0OAz3g8,3,0,Which,0.0024999999441206455,0.30250000953674316,True,1.063455855494777e-12,4.0,0.002532140686589533,0.2758708790689764,0.0025000000000000005,0.0025000000000000005,0.2225,0.3025,0.0,0.07999999999999999 --wny0OAz3g8/3,-wny0OAz3g8,3,1,then,0.32249999046325684,0.48249998688697815,True,1.6761636837617916e-13,4.0,0.31656018451331996,0.4774565875920375,0.28250000000000003,0.3225,0.4425,0.4825,0.03999999999999998,0.03999999999999998 --wny0OAz3g8/3,-wny0OAz3g8,3,2,allowed,0.5425000190734863,0.8224999904632568,True,3.7471050296899316e-14,1.023621916770935,0.5441020695647343,0.8225031085039468,0.5425,0.5625,0.8225,0.8225,0.020000000000000018,0.0 --wny0OAz3g8/3,-wny0OAz3g8,3,3,the,0.9024999737739563,1.0225000381469727,True,2.521534498263695e-15,0.25,0.9020954097118318,1.022499565639348,0.9025,0.9025,1.0225,1.0225,0.0,0.0 --wny0OAz3g8/3,-wny0OAz3g8,3,4,white,1.0625,1.2424999475479126,True,2.5187026130111395e-14,0.6880509853363037,1.0624995479965396,1.242500032360087,1.0625,1.0625,1.2425,1.2425,0.0,0.0 --wny0OAz3g8/3,-wny0OAz3g8,3,5,workers,1.2825000286102295,1.6825000047683716,True,9.733679113372792e-14,2.6590147018432617,1.2825008640728779,1.6824524891403205,1.2825,1.2825,1.6824999999999999,1.6824999999999999,0.0,0.0 --wny0OAz3g8/3,-wny0OAz3g8,3,6,and,1.722499966621399,1.8224999904632568,True,3.1632411533893956e-14,0.8641238808631897,1.7225790148273712,1.8226231419127565,1.7225,1.7225,1.8225,1.8225,0.0,0.0 --wny0OAz3g8/3,-wny0OAz3g8,3,7,unions,1.962499976158142,2.2225000858306885,True,5.4908461878297975e-15,0.25,1.9136149388959556,2.1972650430525142,1.8825,1.9625,2.1825,2.2225,0.07999999999999985,0.040000000000000036 --wny0OAz3g8/3,-wny0OAz3g8,3,8,to,2.242500066757202,2.322499990463257,True,2.5397617155523654e-14,0.6938038468360901,2.242499492552246,2.322500654512255,2.2425,2.2425,2.3225,2.3225,0.0,0.0 --wny0OAz3g8/3,-wny0OAz3g8,3,9,justify,2.3424999713897705,2.702500104904175,True,2.7394013164643016e-13,4.0,2.3465313452716563,2.708943472591961,2.3425,2.4025,2.7025,2.8025,0.06000000000000005,0.10000000000000009 --wny0OAz3g8/3,-wny0OAz3g8,3,10,their,2.7825000286102295,3.002500057220459,True,3.7028682257998075e-14,1.0115374326705933,2.7863605350957643,3.0051172336331358,2.7825,2.8425,3.0025,3.0425,0.05999999999999961,0.040000000000000036 --wny0OAz3g8/3,-wny0OAz3g8,3,11,decision,3.0625,3.442500114440918,True,1.0442468660338666e-14,0.28526395559310913,3.061928269798612,3.446658912342991,3.0625,3.0625,3.4425,3.4825,0.0,0.040000000000000036 --wny0OAz3g8/3,-wny0OAz3g8,3,12,to,3.5225000381469727,3.622499942779541,True,1.8596247859745813e-13,4.0,3.522543175857031,3.6225387940545746,3.5225,3.5225,3.6225,3.6225,0.0,0.0 --wny0OAz3g8/3,-wny0OAz3g8,3,13,not,3.762500047683716,3.922499895095825,True,6.781422211971089e-13,4.0,3.7626099906511024,3.922812910626179,3.7625,3.7625,3.9225,3.9225,0.0,0.0 --wny0OAz3g8/3,-wny0OAz3g8,3,14,allow,3.9825000762939453,4.262499809265137,True,3.618399728607356e-14,0.9884626269340515,3.9831660641663293,4.259794101175912,3.9825,3.9825,4.2225,4.2625,0.0,0.040000000000000036 --wny0OAz3g8/3,-wny0OAz3g8,3,15,black,4.302499771118164,4.622499942779541,True,5.304778426425127e-13,4.0,4.302467397441632,4.6238221223566285,4.3025,4.3025,4.6225000000000005,4.6425,0.0,0.019999999999999574 --wny0OAz3g8/3,-wny0OAz3g8,3,16,workers,4.822500228881836,5.182499885559082,True,3.043428004187096e-14,0.8313937187194824,4.7511172240657515,5.1626108171564065,4.6625000000000005,4.822500000000001,5.102500000000001,5.1825,0.16000000000000014,0.07999999999999918 --wny0OAz3g8/3,-wny0OAz3g8,3,17,into,5.202499866485596,5.382500171661377,True,1.884133819828656e-14,0.5147015452384949,5.19585098799925,5.381566976982173,5.1625000000000005,5.202500000000001,5.3825,5.3825,0.040000000000000036,0.0 --wny0OAz3g8/3,-wny0OAz3g8,3,18,their,5.422500133514404,5.762499809265137,True,4.205888736515551e-15,0.25,5.421675399709751,5.760589260048857,5.4225,5.4225,5.7625,5.7625,0.0,0.0 --wny0OAz3g8/3,-wny0OAz3g8,3,19,union,5.78249979019165,6.002500057220459,True,8.382809962674542e-13,4.0,5.782500067776348,6.002500253985618,5.782500000000001,5.782500000000001,6.0025,6.0025,0.0,0.0 --wny0OAz3g8/2,-wny0OAz3g8,2,0,And,0.0024999999441206455,0.10249999910593033,True,1.7852615273681455e-14,0.39666062593460083,0.009268933724016128,0.11272779056163183,0.0025000000000000005,0.0425,0.10250000000000001,0.1625,0.04,0.06 --wny0OAz3g8/2,-wny0OAz3g8,2,1,because,0.14249999821186066,0.48249998688697815,True,3.0093440760159407e-13,4.0,0.15613830486104457,0.4783389175803099,0.14250000000000002,0.2225,0.4425,0.4825,0.07999999999999999,0.03999999999999998 --wny0OAz3g8/2,-wny0OAz3g8,2,2,they,0.5024999976158142,0.6424999833106995,True,3.2948963314140788e-15,0.25,0.500228014631938,0.6411874151576354,0.4625,0.5025,0.6224999999999999,0.6425,0.039999999999999925,0.020000000000000018 --wny0OAz3g8/2,-wny0OAz3g8,2,3,couldn’t,0.6625000238418579,1.0425000190734863,True,1.0930697536340461e-12,4.0,0.6621778628090622,1.0338893709683967,0.6625,0.6625,0.9824999999999999,1.0425,0.0,0.06000000000000005 --wny0OAz3g8/2,-wny0OAz3g8,2,4,get,1.122499942779541,1.2424999475479126,True,9.124004449103523e-14,2.027228593826294,1.1044792090557718,1.2214760298378058,1.0025,1.1225,1.1025,1.2425,0.1200000000000001,0.1399999999999999 --wny0OAz3g8/2,-wny0OAz3g8,2,5,these,1.2625000476837158,1.4424999952316284,True,4.420967765998837e-15,0.25,1.2414761103051,1.4275101963469414,1.1225,1.2625,1.3425,1.4425,0.1399999999999999,0.09999999999999987 --wny0OAz3g8/2,-wny0OAz3g8,2,6,"jobs,",1.4824999570846558,1.622499942779541,True,9.117111257921076e-17,0.25,1.4671903258153054,1.6149842590168326,1.3825,1.4825,1.5625,1.6225,0.09999999999999987,0.06000000000000005 --wny0OAz3g8/2,-wny0OAz3g8,2,7,Black,1.6425000429153442,2.0225000381469727,True,4.183806079360863e-12,4.0,1.6425267594186002,2.0225037593548576,1.6425,1.6425,2.0225,2.0225,0.0,0.0 --wny0OAz3g8/2,-wny0OAz3g8,2,8,communities,2.2225000858306885,2.762500047683716,True,8.090853833263301e-13,4.0,2.2210278203653933,2.762521926399968,2.2225,2.2225,2.7625,2.7625,0.0,0.0 --wny0OAz3g8/2,-wny0OAz3g8,2,9,had,2.822499990463257,2.922499895095825,True,5.415088831576794e-15,0.25,2.8224974932022153,2.922509663136557,2.8225,2.8225,2.9225,2.9225,0.0,0.0 --wny0OAz3g8/2,-wny0OAz3g8,2,10,more,2.942500114440918,3.122499942779541,True,4.5007278611473855e-14,1.0,2.942523637142635,3.1224999999350835,2.9425,2.9425,3.1225,3.1225,0.0,0.0 --wny0OAz3g8/2,-wny0OAz3g8,2,11,men,3.1624999046325684,3.262500047683716,True,3.634124725866543e-14,0.8074526786804199,3.162499999504434,3.2625000000072166,3.1625,3.1625,3.2625,3.2625,0.0,0.0 --wny0OAz3g8/2,-wny0OAz3g8,2,12,out,3.2825000286102295,3.382499933242798,True,1.8249694102019344e-16,0.25,3.282708035980563,3.3827283868097444,3.2825,3.2825,3.3825,3.3825,0.0,0.0 --wny0OAz3g8/2,-wny0OAz3g8,2,13,of,3.422499895095825,3.4825000762939453,True,3.758835148519324e-13,4.0,3.4222075384617283,3.4822075403563395,3.4225,3.4225,3.4825,3.4825,0.0,0.0 --wny0OAz3g8/2,-wny0OAz3g8,2,14,"work,",3.5225000381469727,3.6624999046325684,True,3.3016277022459087e-14,0.7335764169692993,3.522500088158193,3.662500670791443,3.5225,3.5225,3.6625,3.6625,0.0,0.0 --wny0OAz3g8/2,-wny0OAz3g8,2,15,higher,3.7225000858306885,4.202499866485596,True,6.150453190229823e-15,0.25,3.724500860928217,4.153264174821034,3.7225,3.7225,4.1425,4.202500000000001,0.0,0.0600000000000005 --wny0OAz3g8/2,-wny0OAz3g8,2,16,rates,4.222499847412109,4.402500152587891,True,4.178439617420239e-14,0.9283919930458069,4.19143499158515,4.3718706695944265,4.1825,4.2225,4.362500000000001,4.402500000000001,0.040000000000000036,0.040000000000000036 --wny0OAz3g8/2,-wny0OAz3g8,2,17,of,4.422500133514404,4.482500076293945,True,8.391063451712588e-14,1.8643791675567627,4.407059628080299,4.467172046816429,4.402500000000001,4.4225,4.4625,4.482500000000001,0.019999999999999574,0.020000000000000462 --wny0OAz3g8/2,-wny0OAz3g8,2,18,"poverty,",4.502500057220459,4.982500076293945,True,1.2409367424696255e-13,2.7571911811828613,4.502723343495389,4.982492269661619,4.5025,4.5025,4.982500000000001,4.982500000000001,0.0,0.0 --wny0OAz3g8/2,-wny0OAz3g8,2,19,and,5.082499980926514,5.182499885559082,True,4.206491823973996e-15,0.25,5.082532400809459,5.1832919282128875,5.0825000000000005,5.0825000000000005,5.1825,5.1825,0.0,0.0 --wny0OAz3g8/2,-wny0OAz3g8,2,20,more,5.28249979019165,5.522500038146973,True,7.057249478813893e-14,1.5680240392684937,5.286690563603926,5.522587796836602,5.282500000000001,5.362500000000001,5.522500000000001,5.522500000000001,0.08000000000000007,0.0 --wny0OAz3g8/2,-wny0OAz3g8,2,21,criminal,5.602499961853027,6.002500057220459,True,5.797682348313363e-14,1.2881654500961304,5.6024998811431255,6.004895968302497,5.602500000000001,5.602500000000001,6.0025,6.0025,0.0,0.0 --wny0OAz3g8/2,-wny0OAz3g8,2,22,behavior,6.042500019073486,6.502500057220459,True,8.128294044784656e-12,4.0,6.044907337430317,6.502260696408047,6.0425,6.0425,6.5025,6.5025,0.0,0.0 --wny0OAz3g8/5,-wny0OAz3g8,5,0,This,0.0024999999441206455,0.26249998807907104,True,1.3640474383694312e-12,2.6988413333892822,0.003992614795843328,0.26402516901857465,0.0025000000000000005,0.0025000000000000005,0.2625,0.2625,0.0,0.0 --wny0OAz3g8/5,-wny0OAz3g8,5,1,is,0.3425000011920929,0.4025000035762787,True,5.003446875567752e-12,4.0,0.3455404024503229,0.4057867967217855,0.3425,0.3425,0.4025,0.4025,0.0,0.0 --wny0OAz3g8/5,-wny0OAz3g8,5,2,what’s,0.4625000059604645,0.8224999904632568,True,1.3798032161282947e-11,4.0,0.4689256588302098,0.8257665121741922,0.4625,0.4625,0.8225,0.8225,0.0,0.0 --wny0OAz3g8/5,-wny0OAz3g8,5,3,now,0.8824999928474426,1.002500057220459,True,7.477922361193157e-13,1.4795472621917725,0.884681124078631,1.005510603459454,0.8825,0.8825,1.0025,1.0025,0.0,0.0 --wny0OAz3g8/5,-wny0OAz3g8,5,4,known,1.1024999618530273,1.402500033378601,True,6.791148996236271e-14,0.25,1.1045596670118656,1.4033642322333042,1.1025,1.1025,1.4025,1.4025,0.0,0.0 --wny0OAz3g8/5,-wny0OAz3g8,5,5,as,1.5625,1.622499942779541,True,3.495196482499602e-13,0.691543459892273,1.5624999617181765,1.6224999909013247,1.5625,1.5625,1.6225,1.6225,0.0,0.0 --wny0OAz3g8/5,-wny0OAz3g8,5,6,racial,1.7424999475479126,2.0225000381469727,True,2.5938493432124676e-14,0.25,1.7236696275904895,2.0135054081516173,1.7025,1.7425,1.9825,2.0225,0.040000000000000036,0.040000000000000036 --wny0OAz3g8/5,-wny0OAz3g8,5,7,formation,2.0425000190734863,2.502500057220459,True,8.995870048227397e-14,0.25,2.042498883726085,2.502516094158499,2.0425,2.0425,2.5025,2.5025,0.0,0.0 --wny0OAz3g8/5,-wny0OAz3g8,5,8,"theory,",2.5625,2.822499990463257,True,2.28589906335272e-13,0.45227745175361633,2.561166959632408,2.8224983990052683,2.5625,2.5625,2.8225,2.8225,0.0,0.0 --wny0OAz3g8/5,-wny0OAz3g8,5,9,a,3.1024999618530273,3.122499942779541,True,1.5396341970438931e-12,3.0462491512298584,3.1025002400560107,3.122500240056011,3.1025,3.1025,3.1225,3.1225,0.0,0.0 --wny0OAz3g8/5,-wny0OAz3g8,5,10,theory,3.182499885559082,3.4024999141693115,True,8.635281346317664e-14,0.25,3.182499996308189,3.4024999967473804,3.1825,3.1825,3.4025,3.4025,0.0,0.0 --wny0OAz3g8/5,-wny0OAz3g8,5,11,formalized,3.422499895095825,3.922499895095825,True,3.7153637913629745e-13,0.7351047396659851,3.422499999704111,3.9223584723202434,3.4225,3.4225,3.9225,3.9225,0.0,0.0 --wny0OAz3g8/5,-wny0OAz3g8,5,12,by,3.942500114440918,4.002500057220459,True,2.2909525838887834e-12,4.0,3.942500007809117,4.002500007918179,3.9425,3.9425,4.0025,4.0025,0.0,0.0 --wny0OAz3g8/5,-wny0OAz3g8,5,13,modern,4.0625,4.362500190734863,True,4.389206148059169e-14,0.25,4.072012047116495,4.362462041170702,4.062500000000001,4.0825000000000005,4.362500000000001,4.362500000000001,0.019999999999999574,0.0 --wny0OAz3g8/5,-wny0OAz3g8,5,14,sociologists,4.382500171661377,5.022500038146973,True,7.646028992239207e-13,1.5128079652786255,4.3826825043211555,5.022640992110379,4.3825,4.3825,5.022500000000001,5.022500000000001,0.0,0.0 --wny0OAz3g8/5,-wny0OAz3g8,5,15,Michael,5.042500019073486,5.442500114440918,True,2.0837234119153863e-13,0.41227591037750244,5.047794963805033,5.442525017815331,5.0425,5.0825000000000005,5.442500000000001,5.442500000000001,0.040000000000000036,0.0 --wny0OAz3g8/5,-wny0OAz3g8,5,16,Omi,5.502500057220459,5.622499942779541,True,2.1487714765063698e-14,0.25,5.502505713472408,5.622502608037449,5.5025,5.5025,5.6225000000000005,5.6225000000000005,0.0,0.0 --wny0OAz3g8/5,-wny0OAz3g8,5,17,and,5.662499904632568,5.822500228881836,True,4.389145297212238e-12,4.0,5.662574457646359,5.822578829922969,5.6625000000000005,5.6625000000000005,5.822500000000001,5.822500000000001,0.0,0.0 --wny0OAz3g8/5,-wny0OAz3g8,5,18,Howard,5.922500133514404,6.222499847412109,True,6.393029009822693e-13,1.2648952007293701,5.921724323074964,6.218265066239246,5.9225,5.9225,6.1625000000000005,6.2225,0.0,0.05999999999999961 --wny0OAz3g8/5,-wny0OAz3g8,5,19,Winant,6.302499771118164,6.662499904632568,True,5.3509067836354784e-12,4.0,6.302641526631446,6.662501030109093,6.3025,6.3025,6.6625000000000005,6.6625000000000005,0.0,0.0 --wny0OAz3g8/7,-wny0OAz3g8,7,0,Omi,0.042500000447034836,0.18250000476837158,True,5.724248657544562e-13,2.633195638656616,0.04244340083416118,0.18338120669739688,0.0425,0.0425,0.1825,0.1825,0.0,0.0 --wny0OAz3g8/7,-wny0OAz3g8,7,1,and,0.2824999988079071,0.4424999952316284,True,2.6359350899923806e-13,1.212549090385437,0.28245764724904965,0.4467660931471465,0.28250000000000003,0.28250000000000003,0.4425,0.5025,0.0,0.05999999999999994 --wny0OAz3g8/7,-wny0OAz3g8,7,2,Winant,0.48249998688697815,0.8025000095367432,True,8.451231901795975e-12,4.0,0.49016837626293247,0.7853902575957773,0.4825,0.5225,0.7625,0.8025,0.03999999999999998,0.040000000000000036 --wny0OAz3g8/7,-wny0OAz3g8,7,3,argue,0.8224999904632568,1.0625,True,7.892336957582291e-13,3.6305317878723145,0.8224757457922287,1.0676672843497057,0.8225,0.8225,1.0625,1.1025,0.0,0.040000000000000036 --wny0OAz3g8/7,-wny0OAz3g8,7,4,that,1.1425000429153442,1.3224999904632568,True,6.123268938337117e-14,0.2816747725009918,1.1377341883765733,1.3195217703113347,1.0825,1.1425,1.2825,1.3225,0.06000000000000005,0.040000000000000036 --wny0OAz3g8/7,-wny0OAz3g8,7,5,the,1.3424999713897705,1.4424999952316284,True,1.2730490998120927e-14,0.25,1.3440425032977281,1.4448918858978665,1.3425,1.3625,1.4425,1.4625,0.020000000000000018,0.020000000000000018 --wny0OAz3g8/7,-wny0OAz3g8,7,6,concept,1.5225000381469727,1.8624999523162842,True,2.460763797590415e-13,1.1319690942764282,1.5279296219329088,1.8634414995423771,1.5225,1.5425,1.8625,1.8625,0.020000000000000018,0.0 --wny0OAz3g8/7,-wny0OAz3g8,7,7,of,1.9225000143051147,1.9824999570846558,True,1.3178159735324768e-12,4.0,1.9226435499615355,1.9829324455007173,1.9224999999999999,1.9224999999999999,1.9825,1.9825,0.0,0.0 --wny0OAz3g8/7,-wny0OAz3g8,7,8,race,2.0824999809265137,2.242500066757202,True,3.6809178751914806e-14,0.25,2.0824184093373526,2.2424999998142665,2.0825,2.0825,2.2425,2.2425,0.0,0.0 --wny0OAz3g8/7,-wny0OAz3g8,7,9,came,2.2825000286102295,2.4625000953674316,True,1.1092636412277784e-13,0.510269284248352,2.282500009294918,2.46249946919691,2.2825,2.2825,2.4625,2.4625,0.0,0.0 --wny0OAz3g8/7,-wny0OAz3g8,7,10,about,2.5225000381469727,2.702500104904175,True,1.5981041766614454e-14,0.25,2.50596479396657,2.688239210156162,2.4825,2.5225,2.6625,2.7025,0.040000000000000036,0.040000000000000036 --wny0OAz3g8/7,-wny0OAz3g8,7,11,as,2.742500066757202,2.822499990463257,True,1.3851884862661062e-13,0.6371966600418091,2.7414056060970298,2.820828518642153,2.7425,2.7425,2.8225,2.8225,0.0,0.0 --wny0OAz3g8/7,-wny0OAz3g8,7,12,a,2.8424999713897705,2.862499952316284,True,1.0622554051653577e-11,4.0,2.8424999992289264,2.862499999228926,2.8425,2.8425,2.8625,2.8625,0.0,0.0 --wny0OAz3g8/7,-wny0OAz3g8,7,13,tool,2.922499895095825,3.122499942779541,True,2.4609784696205672e-12,4.0,2.922499514367321,3.122506056854534,2.9225,2.9225,3.1225,3.1225,0.0,0.0 --wny0OAz3g8/7,-wny0OAz3g8,7,14,to,3.202500104904175,3.262500047683716,True,2.1649702701149326e-13,0.995901882648468,3.2025010194804278,3.2625016442219503,3.2025,3.2025,3.2625,3.2625,0.0,0.0 --wny0OAz3g8/7,-wny0OAz3g8,7,15,justify,3.322499990463257,3.762500047683716,True,6.311653131564621e-13,2.9034059047698975,3.3224999965992708,3.7625087559140353,3.3225000000000002,3.3225000000000002,3.7625,3.7625,0.0,0.0 --wny0OAz3g8/7,-wny0OAz3g8,7,16,and,3.8424999713897705,3.9825000762939453,True,6.5197286385301235e-15,0.25,3.842662866801597,3.980611906887309,3.8425,3.8425,3.9625,3.9825,0.0,0.020000000000000018 --wny0OAz3g8/7,-wny0OAz3g8,7,17,maintain,4.002500057220459,4.462500095367432,True,2.042441863626585e-15,0.25,4.002481016298704,4.461250026333836,4.0025,4.0025,4.4625,4.4625,0.0,0.0 --wny0OAz3g8/7,-wny0OAz3g8,7,18,the,4.482500076293945,4.582499980926514,True,1.5537561471809513e-12,4.0,4.483034653975056,4.583079213530119,4.482500000000001,4.482500000000001,4.5825000000000005,4.5825000000000005,0.0,0.0 --wny0OAz3g8/7,-wny0OAz3g8,7,19,economic,4.642499923706055,5.042500019073486,True,2.8485436123597274e-13,1.3103505373001099,4.6367405754513396,5.044914535897253,4.6225000000000005,4.6425,5.0425,5.062500000000001,0.019999999999999574,0.020000000000000462 --wny0OAz3g8/7,-wny0OAz3g8,7,20,and,5.102499961853027,5.202499866485596,True,1.1146189900961348e-13,0.512732744216919,5.10250104206515,5.202626715315435,5.102500000000001,5.102500000000001,5.202500000000001,5.202500000000001,0.0,0.0 --wny0OAz3g8/7,-wny0OAz3g8,7,21,political,5.242499828338623,5.602499961853027,True,2.099547554381049e-15,0.25,5.244466340076222,5.62200941915277,5.242500000000001,5.242500000000001,5.602500000000001,5.6425,0.0,0.03999999999999915 --wny0OAz3g8/7,-wny0OAz3g8,7,22,power,5.622499942779541,5.982500076293945,True,2.1738790238409744e-13,1.0,5.653380236049285,5.989345211747652,5.6225000000000005,5.6625000000000005,5.942500000000001,5.982500000000001,0.040000000000000036,0.040000000000000036 --wny0OAz3g8/7,-wny0OAz3g8,7,23,held,6.042500019073486,6.222499847412109,True,2.3580451962790586e-14,0.25,6.05669488419283,6.2355620783067325,6.0425,6.0425,6.2225,6.2225,0.0,0.0 --wny0OAz3g8/7,-wny0OAz3g8,7,24,by,6.28249979019165,6.34250020980835,True,5.590170457070963e-14,0.25715187191963196,6.295711270231749,6.355844879545134,6.282500000000001,6.282500000000001,6.3425,6.3425,0.0,0.0 --wny0OAz3g8/7,-wny0OAz3g8,7,25,those,6.382500171661377,6.622499942779541,True,2.3303180132078216e-13,1.0719630718231201,6.397350767685814,6.637488449175456,6.3825,6.4225,6.6225000000000005,6.6225000000000005,0.040000000000000036,0.0 --wny0OAz3g8/7,-wny0OAz3g8,7,26,of,6.702499866485596,6.762499809265137,True,7.917183923701002e-15,0.25,6.714737727531676,6.779059354262793,6.6625000000000005,6.742500000000001,6.7625,6.8425,0.08000000000000007,0.08000000000000007 --wny0OAz3g8/7,-wny0OAz3g8,7,27,European,6.822500228881836,7.382500171661377,True,3.6068148251064414e-13,1.6591607332229614,6.839878020990127,7.40042919656395,6.822500000000001,7.0025,7.3825,7.442500000000001,0.17999999999999972,0.0600000000000005 --wny0OAz3g8/7,-wny0OAz3g8,7,28,descent,7.5625,7.902500152587891,True,5.926632448693958e-12,4.0,7.563703156515533,7.902497095601888,7.562500000000001,7.562500000000001,7.902500000000001,7.902500000000001,0.0,0.0 --wny0OAz3g8/9,-wny0OAz3g8,9,0,He,0.02250000089406967,0.10249999910593033,True,3.690228678188134e-12,2.9857406616210938,0.01570359411021808,0.08848826505862535,0.0025000000000000005,0.0225,0.0625,0.10250000000000001,0.019999999999999997,0.04000000000000001 --wny0OAz3g8/9,-wny0OAz3g8,9,1,explores,0.14249999821186066,0.6424999833106995,True,1.33896398742811e-12,1.0833473205566406,0.12249887573356905,0.6389535213723231,0.0825,0.1625,0.5824999999999999,0.6425,0.08,0.06000000000000005 --wny0OAz3g8/9,-wny0OAz3g8,9,2,why,0.6825000047683716,0.7825000286102295,True,9.870467290729046e-12,4.0,0.6788645232657202,0.784400961311651,0.6625,0.6825,0.7825,0.7825,0.020000000000000018,0.0 --wny0OAz3g8/9,-wny0OAz3g8,9,3,Black,0.862500011920929,1.1024999618530273,True,3.686124756124842e-12,2.9824202060699463,0.8631983314393331,1.1029731457106366,0.8624999999999999,0.8624999999999999,1.1025,1.1025,0.0,0.0 --wny0OAz3g8/9,-wny0OAz3g8,9,4,and,1.1825000047683716,1.3424999713897705,True,5.2772343786533504e-12,4.0,1.1825146996856872,1.342497699820921,1.1824999999999999,1.1824999999999999,1.3425,1.3425,0.0,0.0 --wny0OAz3g8/9,-wny0OAz3g8,9,5,White,1.402500033378601,1.5824999809265137,True,8.070731583043056e-13,0.6529977917671204,1.4024933386901064,1.5832357178381051,1.4025,1.4025,1.5825,1.5825,0.0,0.0 --wny0OAz3g8/9,-wny0OAz3g8,9,6,Americans,1.6425000429153442,2.0824999809265137,True,1.0394870999120426e-13,0.25,1.6424944033583473,2.0809849259710984,1.6425,1.6425,2.0825,2.0825,0.0,0.0 --wny0OAz3g8/9,-wny0OAz3g8,9,7,tend,2.1024999618530273,2.262500047683716,True,3.9480879909748953e-14,0.25,2.102222472329328,2.262513185028439,2.1025,2.1025,2.2625,2.2625,0.0,0.0 --wny0OAz3g8/9,-wny0OAz3g8,9,8,to,2.2825000286102295,2.3424999713897705,True,6.124948638552841e-13,0.4955657422542572,2.28261991037791,2.3426199111197468,2.2825,2.2825,2.3425,2.3425,0.0,0.0 --wny0OAz3g8/9,-wny0OAz3g8,9,9,have,2.362499952316284,2.502500057220459,True,1.3514602848277435e-12,1.0934580564498901,2.365759465357853,2.5093280317862643,2.3625,2.4025,2.5025,2.5625,0.040000000000000036,0.06000000000000005 --wny0OAz3g8/9,-wny0OAz3g8,9,10,such,2.5425000190734863,2.702500104904175,True,4.4576911606419856e-12,3.606689929962158,2.563265883639007,2.7336550703965714,2.5425,2.5825,2.7025,2.7625,0.040000000000000036,0.06000000000000005 --wny0OAz3g8/9,-wny0OAz3g8,9,11,different,2.802500009536743,3.322499990463257,True,2.1473345020520118e-13,0.25,2.8025875890661442,3.3226400145089827,2.8025,2.8025,3.3225000000000002,3.3225000000000002,0.0,0.0 --wny0OAz3g8/9,-wny0OAz3g8,9,12,outcomes,3.382499933242798,3.9024999141693115,True,8.532017323550911e-13,0.6903201341629028,3.382868179253032,3.9038235552458773,3.3825,3.3825,3.9025,3.9025,0.0,0.0 --wny0OAz3g8/9,-wny0OAz3g8,9,13,in,4.002500057220459,4.0625,True,3.568455752243904e-13,0.28872150182724,4.0023310891423645,4.062508621161237,4.0025,4.0025,4.062500000000001,4.062500000000001,0.0,0.0 --wny0OAz3g8/9,-wny0OAz3g8,9,14,terms,4.162499904632568,4.482500076293945,True,3.854301426631235e-12,3.1184909343719482,4.162879085237475,4.482499860398114,4.1625000000000005,4.1625000000000005,4.482500000000001,4.482500000000001,0.0,0.0 --wny0OAz3g8/9,-wny0OAz3g8,9,15,of,4.542500019073486,4.662499904632568,True,2.5795234749755556e-14,0.25,4.543504439499194,4.663010117094874,4.522500000000001,4.602500000000001,4.6625000000000005,4.6625000000000005,0.08000000000000007,0.0 --wny0OAz3g8/9,-wny0OAz3g8,9,16,"income,",4.722499847412109,5.082499980926514,True,1.1329377106600313e-12,0.9166527390480042,4.722783972994184,5.083036643699158,4.7225,4.7225,5.0825000000000005,5.0825000000000005,0.0,0.0 --wny0OAz3g8/9,-wny0OAz3g8,9,17,"education,",5.202499866485596,5.722499847412109,True,3.289460934544075e-12,2.661482095718384,5.20112438124031,5.617248567010778,5.202500000000001,5.202500000000001,5.5825000000000005,5.7225,0.0,0.13999999999999968 --wny0OAz3g8/9,-wny0OAz3g8,9,18,and,5.762499809265137,5.862500190734863,True,3.816548178837628e-14,0.25,5.647324687175936,5.747357974508286,5.6225000000000005,5.7625,5.7225,5.862500000000001,0.13999999999999968,0.14000000000000057 --wny0OAz3g8/9,-wny0OAz3g8,9,19,more,5.882500171661377,6.022500038146973,True,2.074348722305719e-12,1.6783424615859985,5.817082481580934,5.993166312381108,5.782500000000001,5.8825,5.982500000000001,6.022500000000001,0.09999999999999964,0.040000000000000036 --571d8cVauQ/0,-571d8cVauQ,0,0,This,0.42250001430511475,1.1425000429153442,True,1.6880530193742792e-15,0.25,0.36545353509037076,1.1497830274676015,0.0425,0.7625,1.1425,1.2025,0.72,0.05999999999999983 --571d8cVauQ/0,-571d8cVauQ,0,1,is,1.2024999856948853,1.2625000476837158,True,1.1562954370034073e-12,4.0,1.2072494672557035,1.2695928728483776,1.2025,1.2425,1.2625,1.3225,0.040000000000000036,0.06000000000000005 --571d8cVauQ/0,-571d8cVauQ,0,2,Rhett,1.3025000095367432,1.5425000190734863,True,1.0972020953467845e-13,0.5990563631057739,1.314310355709599,1.5400492489243816,1.3025,1.3425,1.5025,1.5425,0.040000000000000036,0.040000000000000036 --571d8cVauQ/0,-571d8cVauQ,0,3,"Reiger,",1.5625,1.8825000524520874,True,1.3116477305327723e-13,0.7161405682563782,1.5646701061124126,1.8860143148046669,1.5625,1.5825,1.8825,1.9025,0.020000000000000018,0.020000000000000018 --571d8cVauQ/0,-571d8cVauQ,0,4,White,1.9225000143051147,2.1424999237060547,True,7.403700862020773e-14,0.4042312800884247,1.9225171969481951,2.1425231516004852,1.9224999999999999,1.9224999999999999,2.1425,2.1425,0.0,0.0 --571d8cVauQ/0,-571d8cVauQ,0,5,Caspian,2.1624999046325684,2.5625,True,1.1581609152613859e-12,4.0,2.162561668852808,2.5634643731990616,2.1625,2.1625,2.5625,2.5625,0.0,0.0 --571d8cVauQ/0,-571d8cVauQ,0,6,Studios,2.622499942779541,3.0625,True,1.5272361825711955e-13,0.8338487148284912,2.622576837146804,3.0645311269113757,2.6225,2.6225,3.0625,3.1025,0.0,0.040000000000000036 --571d8cVauQ/0,-571d8cVauQ,0,7,on,3.1424999237060547,3.202500104904175,True,2.5477747082197633e-12,4.0,3.1424877070707216,3.2024918071032786,3.1425,3.1425,3.2025,3.2025,0.0,0.0 --571d8cVauQ/0,-571d8cVauQ,0,8,behalf,3.262500047683716,3.6024999618530273,True,7.087249352926567e-14,0.3869534730911255,3.262499999603474,3.5985239851668043,3.2625,3.2625,3.5825,3.6025,0.0,0.020000000000000018 --571d8cVauQ/0,-571d8cVauQ,0,9,of,3.622499942779541,3.682499885559082,True,2.463900936576502e-13,1.3452539443969727,3.622492865316998,3.6826183503531253,3.6225,3.6225,3.6825,3.6825,0.0,0.0 --571d8cVauQ/0,-571d8cVauQ,0,10,Expert,3.702500104904175,4.082499980926514,True,4.2966633940003107e-13,2.3459155559539795,3.718376212606498,4.069501795831513,3.7025,3.7825,4.0425,4.0825000000000005,0.08000000000000007,0.040000000000000036 --571d8cVauQ/0,-571d8cVauQ,0,11,Village.,4.102499961853027,4.982500076293945,True,2.135865269370374e-13,1.1661512851715088,4.102528781943396,4.942896755710078,4.1025,4.1025,4.902500000000001,4.982500000000001,0.0,0.08000000000000007 --571d8cVauQ/5,-571d8cVauQ,5,0,So,0.0625,0.14249999821186066,True,1.961745210721233e-10,4.0,0.061026267841565805,0.14039837035299824,0.0625,0.0625,0.14250000000000002,0.14250000000000002,0.0,0.0 --571d8cVauQ/5,-571d8cVauQ,5,1,very,0.5425000190734863,0.7225000262260437,True,5.542242012546161e-13,3.911118745803833,0.39099748158334563,0.7070536888457671,0.1825,0.5425,0.6825,0.7224999999999999,0.36,0.039999999999999925 --571d8cVauQ/5,-571d8cVauQ,5,2,important,0.762499988079071,1.3025000095367432,True,1.289873698302746e-13,0.9102542400360107,0.7504742650006566,1.2691000312282303,0.7224999999999999,0.7625,1.2025,1.3425,0.040000000000000036,0.14000000000000012 --571d8cVauQ/5,-571d8cVauQ,5,3,to,1.3424999713897705,1.402500033378601,True,6.078231137740422e-16,0.25,1.3274161608563455,1.3876820258440432,1.2825,1.4224999999999999,1.3425,1.4825,0.1399999999999999,0.1399999999999999 --571d8cVauQ/5,-571d8cVauQ,5,4,go,1.4225000143051147,1.4824999570846558,True,5.364711279376433e-12,4.0,1.4430355265690127,1.512146626666273,1.4224999999999999,1.6025,1.4825,1.7425,0.18000000000000016,0.26 --571d8cVauQ/5,-571d8cVauQ,5,5,out,1.6024999618530273,1.8025000095367432,True,9.859104635120963e-13,4.0,1.637724047396162,1.82970814525818,1.6025,1.9224999999999999,1.8025,2.0425,0.31999999999999984,0.24 --571d8cVauQ/5,-571d8cVauQ,5,6,to,1.9225000143051147,2.002500057220459,True,1.4170477671045928e-13,1.0,1.9843274093437095,2.066520692378383,1.9224999999999999,2.4625,2.0025,2.5625,0.54,0.56 --571d8cVauQ/5,-571d8cVauQ,5,7,the,2.4625000953674316,2.6424999237060547,True,4.532087053733813e-13,3.1982598304748535,2.464986666672805,2.648123686812614,2.4225,2.6225,2.5625,2.7225,0.20000000000000018,0.16000000000000014 --571d8cVauQ/5,-571d8cVauQ,5,8,"locations,",2.742500066757202,3.382499933242798,True,2.9229296392117854e-13,2.0626895427703857,2.7477243046229103,3.379244935643703,2.7425,2.8025,3.3625,3.3825,0.06000000000000005,0.020000000000000018 --571d8cVauQ/5,-571d8cVauQ,5,9,walk,3.4024999141693115,3.742500066757202,True,8.698149042223296e-16,0.25,3.405197916129465,3.7593203164399864,3.4025,3.4025,3.7225,4.022500000000001,0.0,0.3000000000000007 --571d8cVauQ/5,-571d8cVauQ,5,10,"around,",3.762500047683716,4.082499980926514,True,4.603956444055625e-14,0.32489776611328125,3.7894646126851903,4.113669860878586,3.7625,4.1425,4.0825000000000005,4.482500000000001,0.3799999999999999,0.40000000000000036 --571d8cVauQ/5,-571d8cVauQ,5,11,talk,4.142499923706055,4.442500114440918,True,1.35541764986237e-13,0.9565081000328064,4.190362867190777,4.484542398894459,4.1425,4.5025,4.442500000000001,4.9225,0.3600000000000003,0.47999999999999954 --571d8cVauQ/5,-571d8cVauQ,5,12,with,4.502500057220459,4.922500133514404,True,8.38819099358186e-14,0.5919483304023743,4.541720300661576,4.940244070441893,4.5025,4.9625,4.9225,5.102500000000001,0.45999999999999996,0.1800000000000006 --571d8cVauQ/5,-571d8cVauQ,5,13,the,5.002500057220459,5.102499961853027,True,2.0982386767193044e-14,0.25,5.018430928164901,5.1207677393025,5.0025,5.1625000000000005,5.102500000000001,5.2625,0.16000000000000014,0.15999999999999925 --571d8cVauQ/5,-571d8cVauQ,5,14,owners,5.162499904632568,5.482500076293945,True,3.260156359284616e-13,2.3006680011749268,5.183334041083281,5.504277901364218,5.1625000000000005,5.3425,5.482500000000001,5.602500000000001,0.17999999999999972,0.1200000000000001 --571d8cVauQ/5,-571d8cVauQ,5,15,if,5.502500057220459,5.5625,True,1.7678204942973808e-16,0.25,5.535479301056968,5.596502741603346,5.5025,5.6625000000000005,5.562500000000001,5.7225,0.16000000000000014,0.15999999999999925 --571d8cVauQ/5,-571d8cVauQ,5,16,you,5.582499980926514,5.722499847412109,True,4.4787060209583104e-14,0.3160589337348938,5.624735476439397,5.761850848637931,5.5825000000000005,5.742500000000001,5.7225,5.862500000000001,0.16000000000000014,0.14000000000000057 --571d8cVauQ/5,-571d8cVauQ,5,17,"can,",5.742499828338623,5.862500190734863,True,4.924350383299532e-14,0.3475077152252197,5.7829325715282085,5.904529793030309,5.742500000000001,5.8825,5.862500000000001,6.0825000000000005,0.13999999999999968,0.21999999999999975 --571d8cVauQ/5,-571d8cVauQ,5,18,tell,5.882500171661377,6.142499923706055,True,2.1348444930249788e-13,1.506543755531311,5.9288363923069145,6.188435906968508,5.8825,6.1625000000000005,6.142500000000001,6.5025,0.28000000000000025,0.35999999999999943 --571d8cVauQ/5,-571d8cVauQ,5,19,them,6.482500076293945,6.682499885559082,True,1.303422159700668e-13,0.9198152422904968,6.374882165415015,6.68920056196025,6.1625000000000005,6.562500000000001,6.642500000000001,6.742500000000001,0.40000000000000036,0.09999999999999964 --571d8cVauQ/5,-571d8cVauQ,5,20,what,6.722499847412109,6.882500171661377,True,4.340288640102517e-14,0.3062909245491028,6.74280020146315,6.90711834793619,6.6625000000000005,6.782500000000001,6.822500000000001,6.942500000000001,0.1200000000000001,0.1200000000000001 --571d8cVauQ/5,-571d8cVauQ,5,21,you're,6.922500133514404,7.162499904632568,True,6.8854756965497366e-12,4.0,6.949658840062754,7.201229129569963,6.862500000000001,6.982500000000001,7.1625000000000005,7.1625000000000005,0.1200000000000001,0.0 --571d8cVauQ/5,-571d8cVauQ,5,22,"doing,",7.182499885559082,7.422500133514404,True,2.756355798987087e-13,1.9451396465301514,7.2233293105612,7.466068313841497,7.1825,7.1825,7.4225,7.4225,0.0,0.0 --571d8cVauQ/5,-571d8cVauQ,5,23,build,7.682499885559082,7.902500152587891,True,4.2132330203880144e-14,0.29732468724250793,7.713083083513668,7.964945886320176,7.642500000000001,7.6825,7.902500000000001,7.9625,0.03999999999999915,0.05999999999999961 --571d8cVauQ/5,-571d8cVauQ,5,24,a,7.942500114440918,7.962500095367432,True,3.905624535263143e-14,0.27561700344085693,8.004457849233917,8.024457849233954,7.942500000000001,7.982500000000001,7.9625,8.0025,0.040000000000000036,0.03999999999999915 --571d8cVauQ/5,-571d8cVauQ,5,25,little,7.982500076293945,8.262499809265137,True,3.241799393489085e-14,0.25,8.047286338490512,8.319486249797016,7.982500000000001,8.0425,8.2625,8.3025,0.05999999999999961,0.040000000000000924 --571d8cVauQ/5,-571d8cVauQ,5,26,"excitement,",8.282500267028809,8.862500190734863,True,3.179512656306151e-14,0.25,8.340643589235283,8.907759359152092,8.282499999999999,8.3425,8.8225,8.862499999999999,0.0600000000000005,0.03999999999999915 --571d8cVauQ/5,-571d8cVauQ,5,27,put,9.422499656677246,9.522500038146973,True,7.793622653707102e-14,0.5499901175498962,9.448525366526367,9.558693789160388,9.4225,9.4225,9.522499999999999,9.522499999999999,0.0,0.0 --571d8cVauQ/5,-571d8cVauQ,5,28,a,9.5625,9.582500457763672,True,9.874617399804886e-13,4.0,9.599558257830385,9.619558257830356,9.5625,9.5825,9.5825,9.6025,0.019999999999999574,0.019999999999999574 --571d8cVauQ/5,-571d8cVauQ,5,29,little,9.6225004196167,9.882499694824219,True,8.713415053504189e-14,0.6148991584777832,9.657902881779448,9.933980702020806,9.6225,9.6225,9.8825,9.8825,0.0,0.0 --571d8cVauQ/5,-571d8cVauQ,5,30,glitz,9.982500076293945,10.182499885559082,True,2.0400179809310082e-11,4.0,9.989943619156207,10.19563550900826,9.9225,9.9825,10.1225,10.1825,0.0600000000000005,0.05999999999999872 --571d8cVauQ/5,-571d8cVauQ,5,31,on,10.282500267028809,10.382499694824219,True,1.639427634446411e-12,4.0,10.275149544087014,10.392708390362388,10.1625,10.282499999999999,10.3025,10.3825,0.11999999999999922,0.08000000000000007 --571d8cVauQ/5,-571d8cVauQ,5,32,there,10.422499656677246,10.6225004196167,True,4.004103296216359e-14,0.2825665771961212,10.454077564626562,10.673171811912887,10.362499999999999,10.4225,10.6225,10.6225,0.0600000000000005,0.0 --571d8cVauQ/5,-571d8cVauQ,5,33,and,10.642499923706055,11.322500228881836,True,8.731728447924914e-13,4.0,10.912128782316048,11.369185804372504,10.6425,11.2625,11.3225,11.362499999999999,0.6199999999999992,0.03999999999999915 --571d8cVauQ/5,-571d8cVauQ,5,34,let,11.542499542236328,11.662500381469727,True,4.009867524829014e-14,0.28297334909439087,11.569560975686585,11.698227520663279,11.5425,11.5425,11.6625,11.6625,0.0,0.0 --571d8cVauQ/5,-571d8cVauQ,5,35,everybody,11.702500343322754,12.082500457763672,True,9.238042188858264e-13,4.0,11.740536622390566,12.121806518011748,11.7025,11.7025,12.0825,12.0825,0.0,0.0 --571d8cVauQ/5,-571d8cVauQ,5,36,knows,12.102499961853027,12.302499771118164,True,9.206563734032863e-14,0.6497002840042114,12.144266740138423,12.349209984328715,12.1025,12.1025,12.3025,12.3225,0.0,0.019999999999999574 --571d8cVauQ/5,-571d8cVauQ,5,37,this,12.762499809265137,12.942500114440918,True,3.215953165661839e-13,2.2694740295410156,12.73313275369772,12.95957414691892,12.3225,12.7625,12.8825,12.942499999999999,0.4399999999999995,0.05999999999999872 --571d8cVauQ/5,-571d8cVauQ,5,38,is,12.982500076293945,13.042499542236328,True,4.4049882014576824e-13,3.108567237854004,13.019727126882461,13.080592199899773,12.9825,12.9825,13.0425,13.0425,0.0,0.0 --571d8cVauQ/5,-571d8cVauQ,5,39,a,13.162500381469727,13.182499885559082,True,3.718831232540909e-12,4.0,13.198762296608688,13.218762296608658,13.1625,13.1625,13.1825,13.1825,0.0,0.0 --571d8cVauQ/5,-571d8cVauQ,5,40,very,13.322500228881836,13.542499542236328,True,1.494705916113212e-13,1.0548027753829956,13.35522890003284,13.57665212442405,13.3225,13.3225,13.5425,13.5425,0.0,0.0 --571d8cVauQ/5,-571d8cVauQ,5,41,valuable,13.682499885559082,14.442500114440918,True,9.463182190985742e-13,4.0,13.714516252757837,14.474684869756821,13.6825,13.6825,14.442499999999999,14.5025,0.0,0.0600000000000005 --571d8cVauQ/5,-571d8cVauQ,5,42,spot.,14.662500381469727,14.962499618530273,True,1.3657936543884364e-12,4.0,14.673377195931495,14.96784942174552,14.6625,14.6625,14.9025,15.0425,0.0,0.14000000000000057 --I_e4mIh0yE/1,-I_e4mIh0yE,1,0,In,0.16249999403953552,0.24250000715255737,True,8.721677351684887e-13,4.0,0.1142069655201318,0.21499044195057157,0.0625,0.1625,0.1825,0.2425,0.1,0.06 --I_e4mIh0yE/1,-I_e4mIh0yE,1,1,the,0.8224999904632568,0.9624999761581421,True,4.6919015032767866e-14,0.4219171106815338,0.779575729691009,0.9513972402826147,0.28250000000000003,0.8424999999999999,0.8624999999999999,0.9624999999999999,0.5599999999999998,0.09999999999999998 --I_e4mIh0yE/1,-I_e4mIh0yE,1,2,United,1.0225000381469727,1.2825000286102295,True,1.241436966246956e-13,1.116356611251831,1.022454650069054,1.2824630944967872,1.0225,1.0225,1.2825,1.2825,0.0,0.0 --I_e4mIh0yE/1,-I_e4mIh0yE,1,3,States,1.3025000095367432,1.5824999809265137,True,2.2734993226268757e-15,0.25,1.3219094885294929,1.6019038732024349,1.3025,1.3425,1.5825,1.6225,0.040000000000000036,0.040000000000000036 --I_e4mIh0yE/1,-I_e4mIh0yE,1,4,we,1.6425000429153442,1.7424999475479126,True,5.195034398323972e-13,4.0,1.6425025929936214,1.7425022697843806,1.6425,1.6425,1.7425,1.7425,0.0,0.0 --I_e4mIh0yE/1,-I_e4mIh0yE,1,5,don't,1.8624999523162842,2.0824999809265137,True,3.625834965603758e-09,4.0,1.8625138297841282,2.0820620731977453,1.8625,1.8625,2.0825,2.0825,0.0,0.0 --I_e4mIh0yE/1,-I_e4mIh0yE,1,6,punish,2.202500104904175,2.502500057220459,True,9.826499016611992e-14,0.8836435079574585,2.2024907371313374,2.5025001246537304,2.2025,2.2025,2.5025,2.5025,0.0,0.0 --I_e4mIh0yE/1,-I_e4mIh0yE,1,7,failure,2.5625,3.0824999809265137,True,3.813583563522238e-14,0.342934787273407,2.57581736001806,3.080994991799556,2.5625,2.6425,3.0825,3.0825,0.08000000000000007,0.0 --I_e4mIh0yE/1,-I_e4mIh0yE,1,8,to,3.5225000381469727,3.622499942779541,True,3.0746702384641666e-13,2.764883279800415,3.52221470372663,3.622506415239828,3.5225,3.5225,3.6225,3.6225,0.0,0.0 --I_e4mIh0yE/1,-I_e4mIh0yE,1,9,the,3.682499885559082,3.7825000286102295,True,3.3432115989452324e-14,0.30063679814338684,3.6824927941693253,3.782492797896148,3.6825,3.6825,3.7825,3.7825,0.0,0.0 --I_e4mIh0yE/1,-I_e4mIh0yE,1,10,degree,3.802500009536743,4.162499904632568,True,6.262374109946081e-14,0.5631411671638489,3.802499999654366,4.162501191750939,3.8025,3.8025,4.1625000000000005,4.1625000000000005,0.0,0.0 --I_e4mIh0yE/1,-I_e4mIh0yE,1,11,to,4.302499771118164,4.362500190734863,True,8.0105626992788e-13,4.0,4.291511506534855,4.352642714953695,4.2625,4.3025,4.322500000000001,4.362500000000001,0.040000000000000036,0.040000000000000036 --I_e4mIh0yE/1,-I_e4mIh0yE,1,12,which,4.422500133514404,4.662499904632568,True,2.4741273347552925e-14,0.25,4.405226899791058,4.654286753863474,4.3425,4.4225,4.6225000000000005,4.6625000000000005,0.08000000000000007,0.040000000000000036 --I_e4mIh0yE/1,-I_e4mIh0yE,1,13,failure,4.742499828338623,5.28249979019165,True,2.8274669931771523e-13,2.5425868034362793,4.739944443800792,5.282521785832095,4.7225,4.742500000000001,5.282500000000001,5.282500000000001,0.020000000000000462,0.0 --I_e4mIh0yE/1,-I_e4mIh0yE,1,14,is,5.34250020980835,5.402500152587891,True,4.104637975539151e-14,0.369107723236084,5.34226851016023,5.4052279359374715,5.3425,5.3425,5.402500000000001,5.442500000000001,0.0,0.040000000000000036 --I_e4mIh0yE/1,-I_e4mIh0yE,1,15,punished,5.502500057220459,5.902500152587891,True,7.313151684706573e-14,0.6576318740844727,5.500985614179578,5.901454375232485,5.5025,5.5025,5.902500000000001,5.902500000000001,0.0,0.0 --I_e4mIh0yE/1,-I_e4mIh0yE,1,16,in,6.302499771118164,6.422500133514404,True,2.6584829715230185e-13,2.3906288146972656,6.284817034685479,6.406331516286906,6.1625000000000005,6.322500000000001,6.322500000000001,6.4225,0.16000000000000014,0.09999999999999964 --I_e4mIh0yE/1,-I_e4mIh0yE,1,17,Europe.,6.662499904632568,6.922500133514404,True,5.098422226935961e-13,4.0,6.656895370927335,6.922440434999503,6.642500000000001,6.6625000000000005,6.9225,6.9225,0.019999999999999574,0.0 --I_e4mIh0yE/3,-I_e4mIh0yE,3,0,It's,0.5824999809265137,0.7225000262260437,True,3.472087617417685e-10,4.0,0.5822805233935374,0.7211801408748947,0.5824999999999999,0.5824999999999999,0.7025,0.7224999999999999,0.0,0.019999999999999907 --I_e4mIh0yE/3,-I_e4mIh0yE,3,1,perceived,0.9225000143051147,1.4824999570846558,True,1.4726222086376695e-13,0.25,0.8894760335439114,1.4662801504889216,0.7224999999999999,0.9225,1.4425,1.4825,0.20000000000000007,0.040000000000000036 --I_e4mIh0yE/3,-I_e4mIh0yE,3,2,that,1.5425000190734863,1.7424999475479126,True,2.1773252959714912e-14,0.25,1.5118009805496575,1.7076001797166942,1.4625,1.5425,1.6625,1.7425,0.08000000000000007,0.07999999999999985 --I_e4mIh0yE/3,-I_e4mIh0yE,3,3,you,1.7625000476837158,1.8624999523162842,True,4.304102037343098e-14,0.25,1.7445763600944204,1.8591816436803994,1.7225,1.7625,1.8225,1.8825,0.040000000000000036,0.06000000000000005 --I_e4mIh0yE/3,-I_e4mIh0yE,3,4,have,1.9225000143051147,2.1424999237060547,True,3.9425008396820616e-12,4.0,1.923373173881217,2.165102454180477,1.9224999999999999,1.9224999999999999,2.1425,2.1825,0.0,0.040000000000000036 --I_e4mIh0yE/3,-I_e4mIh0yE,3,5,actually,2.1624999046325684,2.6424999237060547,True,4.010823791145146e-12,4.0,2.1990408804792785,2.68428186359062,2.1625,2.2225,2.6425,2.8025,0.06000000000000005,0.16000000000000014 --I_e4mIh0yE/3,-I_e4mIh0yE,3,6,learned,2.7825000286102295,3.122499942779541,True,4.510655087289206e-13,0.5370558500289917,2.781821592938269,3.1219551838308943,2.6625,2.8425,3.0025,3.1625,0.17999999999999972,0.16000000000000014 --I_e4mIh0yE/3,-I_e4mIh0yE,3,7,"something,",3.2225000858306885,3.702500104904175,True,1.2301406638118295e-12,1.4646525382995605,3.210776660611705,3.685039851830411,3.0625,3.2225,3.4425,3.7025,0.16000000000000014,0.26000000000000023 --I_e4mIh0yE/3,-I_e4mIh0yE,3,8,over,3.762500047683716,3.9625000953674316,True,6.062504827580167e-14,0.25,3.7497129407356837,3.9509308917543975,3.5025,3.8225000000000002,3.7025,4.0425,0.3200000000000003,0.3400000000000003 --I_e4mIh0yE/3,-I_e4mIh0yE,3,9,the,3.9825000762939453,4.082499980926514,True,7.674462736313725e-14,0.25,3.988517118629397,4.105443941306858,3.8225000000000002,4.1225000000000005,4.0425,4.362500000000001,0.30000000000000027,0.3200000000000003 --I_e4mIh0yE/3,-I_e4mIh0yE,3,10,course,4.262499809265137,4.542500019073486,True,1.2368673793505813e-12,1.4726616144180298,4.274087408439977,4.559334574473354,4.2625,4.3825,4.5425,4.6825,0.1200000000000001,0.13999999999999968 --I_e4mIh0yE/3,-I_e4mIh0yE,3,11,of,4.622499942779541,4.682499885559082,True,4.1304034303045467e-13,0.491781622171402,4.680345626946339,4.744915525012013,4.6225000000000005,5.1625000000000005,4.6825,5.2625,0.54,0.5800000000000001 --I_e4mIh0yE/3,-I_e4mIh0yE,3,12,your,5.242499828338623,5.5625,True,1.1803501752394308e-11,4.0,5.248953696227165,5.565865409986523,5.1625000000000005,5.4625,5.562500000000001,5.6225000000000005,0.2999999999999998,0.05999999999999961 --I_e4mIh0yE/3,-I_e4mIh0yE,3,13,"carreer,",5.682499885559082,6.022500038146973,True,5.404035292172482e-12,4.0,5.67524877133456,6.022628998062419,5.6625000000000005,5.6825,6.022500000000001,6.022500000000001,0.019999999999999574,0.0 --I_e4mIh0yE/3,-I_e4mIh0yE,3,14,and,6.042500019073486,6.162499904632568,True,1.5327623068342455e-12,1.824965476989746,6.051594198076872,6.163218343693183,6.0425,6.062500000000001,6.1625000000000005,6.1625000000000005,0.020000000000000462,0.0 --I_e4mIh0yE/3,-I_e4mIh0yE,3,15,that,6.222499847412109,6.362500190734863,True,8.04463049994264e-13,0.9578244686126709,6.223196086715864,6.366824761858561,6.2225,6.2225,6.362500000000001,6.362500000000001,0.0,0.0 --I_e4mIh0yE/3,-I_e4mIh0yE,3,16,you,6.482500076293945,6.742499828338623,True,8.753082893914188e-13,1.042175531387329,6.485121347497934,6.727387463759083,6.482500000000001,6.482500000000001,6.602500000000001,6.782500000000001,0.0,0.17999999999999972 --I_e4mIh0yE/3,-I_e4mIh0yE,3,17,won't,6.902500152587891,7.0625,True,6.68682470505999e-11,4.0,6.850043955382938,7.036261507491488,6.7225,6.902500000000001,7.0025,7.0825000000000005,0.1800000000000006,0.08000000000000007 --I_e4mIh0yE/3,-I_e4mIh0yE,3,18,make,7.082499980926514,7.462500095367432,True,4.19843760451899e-12,4.0,7.142215541761871,7.4625317001592855,7.0825000000000005,7.202500000000001,7.4625,7.4625,0.1200000000000001,0.0 --I_e4mIh0yE/3,-I_e4mIh0yE,3,19,the,7.702499866485596,7.942500114440918,True,2.8825946078898934e-13,0.34321272373199463,7.711799725224728,7.948721670810593,7.702500000000001,7.7225,7.942500000000001,7.9625,0.019999999999999574,0.019999999999999574 --I_e4mIh0yE/3,-I_e4mIh0yE,3,20,mistake,8.0024995803833,8.422499656677246,True,2.3740891522648633e-13,0.2826681435108185,8.001170899583583,8.421542106933641,8.0025,8.0025,8.4225,8.4225,0.0,0.0 --I_e4mIh0yE/3,-I_e4mIh0yE,3,21,twice.,8.662500381469727,8.962499618530273,True,1.2501067889192363e-14,0.25,8.587039530663365,8.962645923111332,8.4825,8.6825,8.9625,8.9625,0.1999999999999993,0.0 --UacrmKiTn4/10,-UacrmKiTn4,10,0,"Because,",0.02250000089406967,0.36250001192092896,True,1.475930685448327e-14,0.25,0.022500000004257795,0.3625472694174722,0.0225,0.0225,0.3625,0.3625,0.0,0.0 --UacrmKiTn4/10,-UacrmKiTn4,10,1,if,0.4025000035762787,0.4625000059604645,True,2.200777673164525e-13,1.5552595853805542,0.4026353313760795,0.46269966085687303,0.4025,0.4025,0.4625,0.4625,0.0,0.0 --UacrmKiTn4/10,-UacrmKiTn4,10,2,they,0.5224999785423279,0.7825000286102295,True,1.5841776675185049e-13,1.1195167303085327,0.5250717282237793,0.7824865774462136,0.5225,0.5625,0.7825,0.7825,0.040000000000000036,0.0 --UacrmKiTn4/10,-UacrmKiTn4,10,3,are,1.0225000381469727,1.162500023841858,True,2.8222001084298072e-14,0.25,0.9993191173234123,1.1572935816657954,0.9425,1.0225,1.1225,1.2425,0.07999999999999996,0.11999999999999988 --UacrmKiTn4/10,-UacrmKiTn4,10,4,not,1.1825000047683716,1.3025000095367432,True,1.917614504687304e-12,4.0,1.212195552950287,1.3411265228208296,1.1824999999999999,1.3825,1.3025,1.6225,0.20000000000000018,0.32000000000000006 --UacrmKiTn4/10,-UacrmKiTn4,10,5,in,1.5225000381469727,1.622499942779541,True,3.806191202059689e-13,2.6897835731506348,1.5472873413699313,1.6685377212106935,1.5225,1.7025,1.6225,2.2225,0.17999999999999994,0.6000000000000001 --UacrmKiTn4/10,-UacrmKiTn4,10,6,any,2.442500114440918,2.5625,True,4.2097759739984086e-13,2.9749913215637207,2.4295782593879096,2.562499437343288,2.2025,2.4425,2.5625,2.5625,0.23999999999999977,0.0 --UacrmKiTn4/10,-UacrmKiTn4,10,7,way,2.6424999237060547,2.7825000286102295,True,1.2459322039793524e-13,0.8804833292961121,2.642499960569166,2.782499959619364,2.6425,2.6425,2.7825,2.7825,0.0,0.0 --UacrmKiTn4/10,-UacrmKiTn4,10,8,held,2.882499933242798,3.0625,True,1.871778990483741e-12,4.0,2.882499663382942,3.06249970189482,2.8825,2.8825,3.0625,3.0625,0.0,0.0 --UacrmKiTn4/10,-UacrmKiTn4,10,9,accountable,3.1024999618530273,3.8424999713897705,True,2.4792566274706856e-14,0.25,3.1034985154384263,3.843995047957288,3.1025,3.1025,3.8425,3.8625,0.0,0.020000000000000018 --UacrmKiTn4/10,-UacrmKiTn4,10,10,for,3.9625000953674316,4.142499923706055,True,8.828910909655652e-13,4.0,3.9618912743665837,4.1422515787201855,3.9625,3.9625,4.1425,4.1425,0.0,0.0 --UacrmKiTn4/10,-UacrmKiTn4,10,11,reading,4.202499866485596,4.522500038146973,True,5.040660204231988e-14,0.35621657967567444,4.217612209195304,4.533819065539573,4.202500000000001,4.282500000000001,4.522500000000001,4.5825000000000005,0.08000000000000007,0.05999999999999961 --UacrmKiTn4/10,-UacrmKiTn4,10,12,the,4.602499961853027,4.702499866485596,True,4.6737817744691226e-14,0.3302897810935974,4.602499650444098,4.702499657454214,4.602500000000001,4.602500000000001,4.702500000000001,4.702500000000001,0.0,0.0 --UacrmKiTn4/10,-UacrmKiTn4,10,13,material,4.722499847412109,5.322500228881836,True,2.7899259508537555e-14,0.25,4.722500025503899,5.3163663313084415,4.7225,4.7225,5.2625,5.322500000000001,0.0,0.0600000000000005 --UacrmKiTn4/10,-UacrmKiTn4,10,14,they,5.34250020980835,6.122499942779541,True,1.6694450184241705e-14,0.25,5.346698826778056,6.105480164175808,5.3425,5.3425,6.062500000000001,6.1225000000000005,0.0,0.05999999999999961 --UacrmKiTn4/10,-UacrmKiTn4,10,15,won't,6.142499923706055,6.302499771118164,True,6.240683664282543e-11,4.0,6.1425008497064475,6.309788862779577,6.142500000000001,6.142500000000001,6.3025,6.3425,0.0,0.040000000000000036 --UacrmKiTn4/10,-UacrmKiTn4,10,16,do,6.402500152587891,6.502500057220459,True,8.948922874431331e-13,4.0,6.4025000340549125,6.502500042623035,6.402500000000001,6.402500000000001,6.5025,6.5025,0.0,0.0 --UacrmKiTn4/10,-UacrmKiTn4,10,17,it.,6.622499942779541,6.682499885559082,True,2.6122733262547854e-14,0.25,6.623106947941723,6.688042407993376,6.6225000000000005,6.6225000000000005,6.6825,6.702500000000001,0.0,0.020000000000000462 --UacrmKiTn4/4,-UacrmKiTn4,4,0,Just,0.0024999999441206455,0.6424999833106995,True,4.562072507957593e-12,4.0,0.004947655251735573,0.6504811942238563,0.0025000000000000005,0.0225,0.6425,0.7025,0.019999999999999997,0.06000000000000005 --UacrmKiTn4/4,-UacrmKiTn4,4,1,given,0.762499988079071,1.002500057220459,True,6.256041691632408e-14,1.8532153367996216,0.7364139253098347,0.9636047049601082,0.6825,0.7625,0.8825,1.0025,0.07999999999999996,0.12 --UacrmKiTn4/4,-UacrmKiTn4,4,2,to,1.0225000381469727,1.0824999809265137,True,1.5428832189179169e-15,0.25,1.0025937583992537,1.0639978885987913,0.9425,1.0225,1.0025,1.0825,0.07999999999999996,0.08000000000000007 --UacrmKiTn4/4,-UacrmKiTn4,4,3,their,1.1024999618530273,1.3224999904632568,True,2.0475887269816778e-16,0.25,1.0908284753739195,1.3135099105503243,1.0225,1.1025,1.2225,1.3225,0.08000000000000007,0.10000000000000009 --UacrmKiTn4/4,-UacrmKiTn4,4,4,own,1.3825000524520874,1.502500057220459,True,1.73095121474621e-15,0.25,1.37705306367968,1.4988073905995172,1.3225,1.3825,1.4625,1.5025,0.06000000000000005,0.040000000000000036 --UacrmKiTn4/4,-UacrmKiTn4,4,5,devices,1.5425000190734863,2.122499942779541,True,4.961841416797723e-14,1.4698368310928345,1.5408861101749405,2.117455888833504,1.5425,1.5425,2.0825,2.1225,0.0,0.040000000000000036 --UacrmKiTn4/4,-UacrmKiTn4,4,6,they,2.202500104904175,2.3424999713897705,True,6.740486261595097e-14,1.9967213869094849,2.2006234143728935,2.341308883214659,2.2025,2.2025,2.3425,2.3425,0.0,0.0 --UacrmKiTn4/4,-UacrmKiTn4,4,7,are,2.362499952316284,2.4825000762939453,True,3.205953569025005e-13,4.0,2.3615948075228883,2.481585319634036,2.3625,2.3625,2.4825,2.4825,0.0,0.0 --UacrmKiTn4/4,-UacrmKiTn4,4,8,not,2.5225000381469727,2.682499885559082,True,5.5410154410759013e-14,1.6414045095443726,2.52250550991515,2.6825054463052336,2.5225,2.5225,2.6825,2.6825,0.0,0.0 --UacrmKiTn4/4,-UacrmKiTn4,4,9,going,2.762500047683716,3.0425000190734863,True,1.7897125160993774e-14,0.5301631689071655,2.743302852447095,3.0226983210219336,2.7225,2.7625,3.0025,3.0425,0.040000000000000036,0.040000000000000036 --UacrmKiTn4/4,-UacrmKiTn4,4,10,to,3.0824999809265137,3.1424999237060547,True,4.2949559449852355e-15,0.25,3.0824999856606508,3.1425000044551568,3.0825,3.0825,3.1425,3.1425,0.0,0.0 --UacrmKiTn4/4,-UacrmKiTn4,4,11,read,3.2225000858306885,3.422499895095825,True,3.4303006890215463e-15,0.25,3.222702148003313,3.418441830412285,3.2225,3.2425,3.3825,3.4225,0.020000000000000018,0.040000000000000036 --UacrmKiTn4/4,-UacrmKiTn4,4,12,the,3.442500114440918,3.5425000190734863,True,1.6336893860283141e-15,0.25,3.4691372489699823,3.5816860218914264,3.4425,3.6625,3.5425,3.8225000000000002,0.2200000000000002,0.28000000000000025 --UacrmKiTn4/4,-UacrmKiTn4,4,13,textbook.,3.6624999046325684,4.142499923706055,True,1.503377094038208e-13,4.0,3.647318800103063,4.282380916193305,3.5625,3.9025,4.0825000000000005,4.6625000000000005,0.33999999999999986,0.5800000000000001 --hnBHBN8p5A/7,-hnBHBN8p5A,7,0,Picture,0.16249999403953552,0.6424999833106995,True,2.388505246451317e-13,1.0,0.16093215462874963,0.6492774175568524,0.1625,0.1625,0.6425,0.7025,0.0,0.06000000000000005 --hnBHBN8p5A/7,-hnBHBN8p5A,7,1,"this,",0.6825000047683716,1.002500057220459,True,1.7479208185011696e-12,4.0,0.6967693237113916,1.0043499540624952,0.6825,0.7424999999999999,1.0025,1.0025,0.05999999999999994,0.0 --hnBHBN8p5A/7,-hnBHBN8p5A,7,2,before,1.2625000476837158,1.8825000524520874,True,3.712301462326789e-14,0.25,1.2568305382584097,1.8793181771780305,1.1624999999999999,1.2625,1.8225,1.8825,0.10000000000000009,0.06000000000000005 --hnBHBN8p5A/7,-hnBHBN8p5A,7,3,we,1.9824999570846558,2.122499942779541,True,3.7951361346079404e-13,1.5889167785644531,1.9788165575745025,2.1177397110667036,1.9825,1.9825,2.1225,2.1225,0.0,0.0 --hnBHBN8p5A/7,-hnBHBN8p5A,7,4,actually,2.2225000858306885,3.682499885559082,True,2.084581151359094e-13,0.8727555274963379,2.217809149643507,3.6792332685589186,2.2225,2.2225,3.6225,3.6825,0.0,0.06000000000000005 --hnBHBN8p5A/7,-hnBHBN8p5A,7,5,start,3.742500066757202,4.082499980926514,True,1.9712341568084435e-12,4.0,3.7424998928545663,4.082502830606967,3.7425,3.7425,4.0825000000000005,4.0825000000000005,0.0,0.0 --hnBHBN8p5A/7,-hnBHBN8p5A,7,6,"hacking,",4.222499847412109,4.702499866485596,True,2.2997982980347588e-14,0.25,4.221812245247405,4.727831407783964,4.2225,4.242500000000001,4.702500000000001,4.782500000000001,0.020000000000000462,0.08000000000000007 --hnBHBN8p5A/7,-hnBHBN8p5A,7,7,we’re,4.922500133514404,5.142499923706055,True,1.77046884097809e-11,4.0,4.920433348583369,5.142277923757999,4.9225,4.9225,5.1425,5.1425,0.0,0.0 --hnBHBN8p5A/7,-hnBHBN8p5A,7,8,in,5.182499885559082,5.242499828338623,True,3.179557853984216e-13,1.3311915397644043,5.182457696430692,5.242471813790377,5.1825,5.1825,5.242500000000001,5.242500000000001,0.0,0.0 --hnBHBN8p5A/7,-hnBHBN8p5A,7,9,a,5.28249979019165,5.302499771118164,True,5.193478754553704e-15,0.25,5.284921857502635,5.3049218575026345,5.282500000000001,5.3025,5.3025,5.322500000000001,0.019999999999999574,0.020000000000000462 --hnBHBN8p5A/7,-hnBHBN8p5A,7,10,room,5.34250020980835,5.502500057220459,True,4.2035475374493404e-15,0.25,5.342924994112858,5.502498287036115,5.3425,5.3425,5.5025,5.5025,0.0,0.0 --hnBHBN8p5A/7,-hnBHBN8p5A,7,11,formal,5.522500038146973,5.902500152587891,True,1.3692799877892264e-13,0.5732790231704712,5.522499935669881,5.902497519672031,5.522500000000001,5.522500000000001,5.902500000000001,5.902500000000001,0.0,0.0 --hnBHBN8p5A/7,-hnBHBN8p5A,7,12,setting,6.882500171661377,7.242499828338623,True,5.154608294019591e-13,2.1580896377563477,6.876668294203695,7.242903312234083,6.8425,6.8825,7.242500000000001,7.242500000000001,0.040000000000000036,0.0 --hnBHBN8p5A/6,-hnBHBN8p5A,6,0,"Discussion,",0.20250000059604645,0.6025000214576721,True,7.413789807928048e-16,0.25,0.05734253021101946,0.6025331203999742,0.0025000000000000005,0.1825,0.6024999999999999,0.6024999999999999,0.18,0.0 --hnBHBN8p5A/6,-hnBHBN8p5A,6,1,how,0.6424999833106995,0.7825000286102295,True,1.488793626141377e-13,0.9633798003196716,0.6425435974958801,0.7825102245774119,0.6425,0.6425,0.7825,0.7825,0.0,0.0 --hnBHBN8p5A/6,-hnBHBN8p5A,6,2,to,0.862500011920929,0.9424999952316284,True,4.985656256329546e-14,0.3226155936717987,0.8625061466012319,0.9433688622350123,0.8624999999999999,0.8624999999999999,0.9425,0.9425,0.0,0.0 --hnBHBN8p5A/6,-hnBHBN8p5A,6,3,discuss,1.002500057220459,1.2825000286102295,True,5.747768390797561e-14,0.37193092703819275,1.002478560527885,1.282636894103437,1.0025,1.0025,1.2825,1.2825,0.0,0.0 --hnBHBN8p5A/6,-hnBHBN8p5A,6,4,ideas,1.3224999904632568,1.7424999475479126,True,7.848715709475595e-13,4.0,1.3870056407994262,1.7424735743902229,1.3225,1.4825,1.7425,1.7425,0.15999999999999992,0.0 --hnBHBN8p5A/6,-hnBHBN8p5A,6,5,and,1.7625000476837158,1.8624999523162842,True,1.503318303175405e-11,4.0,1.7624947007218714,1.8624953633132175,1.7625,1.7625,1.8625,1.8625,0.0,0.0 --hnBHBN8p5A/6,-hnBHBN8p5A,6,6,opinions,1.8825000524520874,2.2225000858306885,True,2.2395399337099553e-12,4.0,1.88249543276377,2.223362908527545,1.8825,1.8825,2.2225,2.2225,0.0,0.0 --hnBHBN8p5A/6,-hnBHBN8p5A,6,7,more,3.8424999713897705,3.9825000762939453,True,2.2274653909554187e-12,4.0,3.813089593624601,3.975339622828584,3.7625,3.8625,3.9225,4.0025,0.09999999999999964,0.08000000000000052 --hnBHBN8p5A/6,-hnBHBN8p5A,6,8,effectively,4.002500057220459,4.582499980926514,True,1.0292728990076924e-13,0.6660296320915222,4.001976607641939,4.579303253022034,3.9425,4.0425,4.5425,4.5825000000000005,0.10000000000000053,0.040000000000000036 --hnBHBN8p5A/6,-hnBHBN8p5A,6,9,than,4.602499961853027,4.942500114440918,True,1.545385997989146e-13,1.0,4.602805718995574,4.942454042242472,4.602500000000001,4.602500000000001,4.942500000000001,4.942500000000001,0.0,0.0 --hnBHBN8p5A/6,-hnBHBN8p5A,6,10,a,4.982500076293945,5.002500057220459,True,1.1543436345684555e-11,4.0,4.973083161483878,4.993083161483986,4.9625,4.982500000000001,4.982500000000001,5.0025,0.020000000000000462,0.019999999999999574 --hnBHBN8p5A/6,-hnBHBN8p5A,6,11,native,5.022500038146973,5.982500076293945,True,2.7570120123519837e-13,1.7840280532836914,5.023246868555434,5.982429087559479,5.022500000000001,5.022500000000001,5.982500000000001,5.982500000000001,0.0,0.0 --hnBHBN8p5A/6,-hnBHBN8p5A,6,12,speaker,6.002500057220459,6.322500228881836,True,1.1699105226248285e-13,0.7570344805717468,6.0024817013264,6.318882058754529,6.0025,6.0025,6.3025,6.322500000000001,0.0,0.020000000000000462 --qDkUB0GgYY/6,-qDkUB0GgYY,6,0,We,0.0024999999441206455,0.0625,True,9.337668442285785e-13,0.4947294592857361,0.004150950202978793,0.06513475794367299,0.0025000000000000005,0.0225,0.0625,0.0825,0.019999999999999997,0.020000000000000004 --qDkUB0GgYY/6,-qDkUB0GgYY,6,1,always,0.10249999910593033,0.4025000035762787,True,2.7101797368811464e-12,1.435910701751709,0.10268331893228248,0.4027179907882608,0.10250000000000001,0.10250000000000001,0.4025,0.4025,0.0,0.0 --qDkUB0GgYY/6,-qDkUB0GgYY,6,2,love,0.48249998688697815,0.6625000238418579,True,1.558735508288417e-13,0.25,0.4821765173364106,0.6623160427138763,0.4825,0.4825,0.6625,0.6625,0.0,0.0 --qDkUB0GgYY/6,-qDkUB0GgYY,6,3,to,0.7225000262260437,0.8025000095367432,True,6.635134065444137e-13,0.35154345631599426,0.7222857214492022,0.8027704858444851,0.7224999999999999,0.7224999999999999,0.8025,0.8025,0.0,0.0 --qDkUB0GgYY/6,-qDkUB0GgYY,6,4,hear,0.9825000166893005,1.1425000429153442,True,5.576355783382114e-12,2.9544713497161865,0.9824963006452994,1.1424985239327123,0.9824999999999999,0.9824999999999999,1.1425,1.1425,0.0,0.0 --qDkUB0GgYY/6,-qDkUB0GgYY,6,5,what,1.222499966621399,1.402500033378601,True,6.127329275473076e-14,0.25,1.2225943761411022,1.4025803637052279,1.2225,1.2225,1.4025,1.4025,0.0,0.0 --qDkUB0GgYY/6,-qDkUB0GgYY,6,6,you,1.462499976158142,1.5625,True,1.2773379664372201e-14,0.25,1.4508682284819499,1.5565077680365997,1.4224999999999999,1.4625,1.5225,1.5625,0.040000000000000036,0.040000000000000036 --qDkUB0GgYY/6,-qDkUB0GgYY,6,7,"say,",1.5824999809265137,1.7424999475479126,True,2.74772760967823e-12,1.4558043479919434,1.5837011690674971,1.7213764295415506,1.5825,1.5825,1.6824999999999999,1.7625,0.0,0.08000000000000007 --qDkUB0GgYY/6,-qDkUB0GgYY,6,8,and,1.902500033378601,2.122499942779541,True,2.0415532112072476e-11,4.0,1.9027662090732207,2.123002766118228,1.9025,1.9025,2.1225,2.1225,0.0,0.0 --qDkUB0GgYY/6,-qDkUB0GgYY,6,9,like,2.202500104904175,2.702500104904175,True,1.0162235636324013e-12,0.5384168028831482,2.2032672035614334,2.67955362682512,2.2025,2.2025,2.6625,2.7025,0.0,0.040000000000000036 --qDkUB0GgYY/6,-qDkUB0GgYY,6,10,and,2.742500066757202,2.882499933242798,True,3.416096572284033e-11,4.0,2.7427614638556794,2.8827771318550117,2.7425,2.7425,2.8825,2.8825,0.0,0.0 --qDkUB0GgYY/6,-qDkUB0GgYY,6,11,share,2.942500114440918,3.242500066757202,True,1.1194105538347987e-11,4.0,2.9573490079626183,3.2448006952303574,2.9425,3.0225,3.2425,3.2625,0.08000000000000007,0.020000000000000018 --qDkUB0GgYY/6,-qDkUB0GgYY,6,12,this,3.322499990463257,3.5625,True,1.1903970864590718e-11,4.0,3.3267286352579317,3.5372195818299765,3.3225000000000002,3.3425,3.4825,3.5625,0.019999999999999574,0.08000000000000007 --qDkUB0GgYY/6,-qDkUB0GgYY,6,13,video,3.6024999618530273,3.9024999141693115,True,7.060332787162116e-12,3.7407138347625732,3.601699909740036,3.9012860766225366,3.6025,3.6025,3.9025,3.9025,0.0,0.0 --qDkUB0GgYY/6,-qDkUB0GgYY,6,14,as,3.922499895095825,4.002500057220459,True,1.0646788355453407e-12,0.5640894174575806,3.9230020734809483,4.002898737678011,3.9225,3.9225,4.0025,4.0025,0.0,0.0 --qDkUB0GgYY/6,-qDkUB0GgYY,6,15,well.,4.042500019073486,4.522500038146973,True,7.8364842826667e-13,0.4151935279369354,4.1010353264747215,4.535698864584865,4.0425,4.4225,4.522500000000001,4.602500000000001,0.3799999999999999,0.08000000000000007 --uywlfIYOS8/4,-uywlfIYOS8,4,0,And,0.02250000089406967,0.16249999403953552,True,5.988297357983896e-11,4.0,0.022602156621392876,0.1630419189656043,0.0225,0.0225,0.1625,0.1625,0.0,0.0 --uywlfIYOS8/4,-uywlfIYOS8,4,1,then,0.42250001430511475,0.6625000238418579,True,1.9874759390331453e-12,4.0,0.4046817558066659,0.6583254135084216,0.3825,0.4225,0.6224999999999999,0.6625,0.03999999999999998,0.040000000000000036 --uywlfIYOS8/4,-uywlfIYOS8,4,2,from,0.8224999904632568,0.9825000166893005,True,1.0401202468757198e-12,4.0,0.8134819794270989,0.9735283961462557,0.7625,0.8225,0.9225,0.9824999999999999,0.06000000000000005,0.05999999999999994 --uywlfIYOS8/4,-uywlfIYOS8,4,3,a,1.0824999809265137,1.1024999618530273,True,6.67349883036808e-14,0.5558029413223267,1.0652153145723244,1.0852153145723227,0.9624999999999999,1.0825,0.9824999999999999,1.1025,0.1200000000000001,0.1200000000000001 --uywlfIYOS8/4,-uywlfIYOS8,4,4,brand,1.2024999856948853,1.4424999952316284,True,1.370544624920136e-14,0.25,1.1838669782022566,1.4434563674323948,1.0825,1.2025,1.4425,1.4425,0.11999999999999988,0.0 --uywlfIYOS8/4,-uywlfIYOS8,4,5,point,1.5824999809265137,1.9824999570846558,True,1.667973620550836e-13,1.3891733884811401,1.6264036729392484,2.021516023502526,1.5825,1.7625,1.9825,2.2025,0.17999999999999994,0.2200000000000002 --uywlfIYOS8/4,-uywlfIYOS8,4,6,of,2.122499942779541,2.202500104904175,True,3.508121744488779e-12,4.0,2.1405318506933226,2.2203001571442478,2.1225,2.2425,2.2025,2.3025,0.1200000000000001,0.10000000000000009 --uywlfIYOS8/4,-uywlfIYOS8,4,7,"view,",2.382499933242798,2.5425000190734863,True,3.820997066927151e-13,3.1823208332061768,2.382480809329932,2.54428426955582,2.3825,2.3825,2.5425,2.5625,0.0,0.020000000000000018 --uywlfIYOS8/4,-uywlfIYOS8,4,8,we,2.6424999237060547,2.7225000858306885,True,4.428764280761839e-14,0.3688500225543976,2.642474815240312,2.722478205982455,2.6425,2.6425,2.7225,2.7225,0.0,0.0 --uywlfIYOS8/4,-uywlfIYOS8,4,9,need,2.822499990463257,3.002500057220459,True,7.078356862233112e-14,0.589521586894989,2.8015348641925786,2.9936915393927097,2.7825,2.8225,2.9625,3.0025,0.03999999999999959,0.040000000000000036 --uywlfIYOS8/4,-uywlfIYOS8,4,10,to,3.0824999809265137,3.1424999237060547,True,1.7816755286826497e-14,0.25,3.082466476739016,3.142468401478628,3.0825,3.0825,3.1425,3.1425,0.0,0.0 --uywlfIYOS8/4,-uywlfIYOS8,4,11,make,3.202500104904175,3.362499952316284,True,7.334166233314773e-14,0.6108267307281494,3.182153732642052,3.342160432953954,3.1625,3.2025,3.3225000000000002,3.3625,0.040000000000000036,0.03999999999999959 --uywlfIYOS8/4,-uywlfIYOS8,4,12,sure,3.442500114440918,3.6024999618530273,True,5.5085622207348e-14,0.45878109335899353,3.43999834296272,3.5975051950710397,3.4025,3.4425,3.5425,3.6025,0.040000000000000036,0.06000000000000005 --uywlfIYOS8/4,-uywlfIYOS8,4,13,we're,3.682499885559082,3.862499952316284,True,3.684579377716268e-11,4.0,3.6833066425391294,3.8624815665334,3.6825,3.6825,3.8625,3.8625,0.0,0.0 --uywlfIYOS8/4,-uywlfIYOS8,4,14,driving,3.9024999141693115,4.222499847412109,True,4.1946619924260534e-14,0.34935280680656433,3.9024850739862837,4.222491770692106,3.9025,3.9025,4.2225,4.2225,0.0,0.0 --uywlfIYOS8/4,-uywlfIYOS8,4,15,the,4.242499828338623,4.34250020980835,True,3.531454168263955e-14,0.2941174805164337,4.242503793608108,4.342507015743014,4.242500000000001,4.242500000000001,4.3425,4.3425,0.0,0.0 --uywlfIYOS8/4,-uywlfIYOS8,4,16,relevant,4.362500190734863,4.722499847412109,True,3.1015102053451316e-13,2.5830955505371094,4.362528100683705,4.7228847343356,4.362500000000001,4.362500000000001,4.7225,4.7225,0.0,0.0 --uywlfIYOS8/4,-uywlfIYOS8,4,17,insight.,4.882500171661377,5.822500228881836,True,2.73377674664399e-12,4.0,4.881390463456283,5.819079782519511,4.862500000000001,4.8825,5.782500000000001,5.862500000000001,0.019999999999999574,0.08000000000000007 --6rXp3zJ3kc/8,-6rXp3zJ3kc,8,0,Many,0.08250000327825546,0.2824999988079071,True,7.850928566109638e-13,3.5132734775543213,0.10585923401689983,0.33275215154873433,0.0825,0.14250000000000002,0.28250000000000003,0.4425,0.06000000000000001,0.15999999999999998 --6rXp3zJ3kc/8,-6rXp3zJ3kc,8,1,people,0.4025000035762787,0.7024999856948853,True,9.156772562413096e-13,4.0,0.4426754338118783,0.7227427877341543,0.4025,0.4825,0.7025,0.7424999999999999,0.07999999999999996,0.039999999999999925 --6rXp3zJ3kc/8,-6rXp3zJ3kc,8,2,are,0.7825000286102295,0.9825000166893005,True,2.8262345263575794e-13,1.2647337913513184,0.7845461092295155,0.9620080068815149,0.7825,0.7825,0.9225,0.9824999999999999,0.0,0.05999999999999994 --6rXp3zJ3kc/8,-6rXp3zJ3kc,8,3,not,1.0225000381469727,1.1425000429153442,True,4.933300133420221e-14,0.25,1.0239882241362008,1.1437603517251953,1.0225,1.0225,1.1425,1.1425,0.0,0.0 --6rXp3zJ3kc/8,-6rXp3zJ3kc,8,4,until,1.1825000047683716,1.5425000190734863,True,1.1237945253192438e-13,0.5028955936431885,1.1842781652958174,1.5435631922214206,1.1824999999999999,1.1824999999999999,1.5425,1.5425,0.0,0.0 --6rXp3zJ3kc/8,-6rXp3zJ3kc,8,5,they,1.5824999809265137,1.9424999952316284,True,1.3072862562434062e-13,0.5850077271461487,1.5848135452386243,1.940893219335555,1.5825,1.5825,1.9425,1.9425,0.0,0.0 --6rXp3zJ3kc/8,-6rXp3zJ3kc,8,6,get,2.0225000381469727,2.1624999046325684,True,1.3913614760384472e-14,0.25,2.0224595608245117,2.162566220706084,2.0225,2.0225,2.1625,2.1625,0.0,0.0 --6rXp3zJ3kc/8,-6rXp3zJ3kc,8,7,to,2.262500047683716,2.3424999713897705,True,2.638859826996614e-14,0.25,2.264419013866157,2.3477816786947727,2.2025,2.3225,2.3425,2.3825,0.11999999999999966,0.040000000000000036 --6rXp3zJ3kc/8,-6rXp3zJ3kc,8,8,be,2.4024999141693115,2.502500057220459,True,4.1763540867788274e-13,1.8689093589782715,2.4025004305045847,2.502500872803157,2.4025,2.4025,2.5025,2.5025,0.0,0.0 --6rXp3zJ3kc/8,-6rXp3zJ3kc,8,9,a,2.6624999046325684,2.682499885559082,True,9.004533772262457e-13,4.0,2.6624925234542722,2.6824925234542722,2.6625,2.6625,2.6825,2.6825,0.0,0.0 --6rXp3zJ3kc/8,-6rXp3zJ3kc,8,10,older,3.322499990463257,3.5425000190734863,True,2.0256505620010884e-13,0.906474232673645,3.3198354757754682,3.5423462179745098,3.3225000000000002,3.3225000000000002,3.5425,3.5425,0.0,0.0 --6rXp3zJ3kc/8,-6rXp3zJ3kc,8,11,age,3.762500047683716,3.922499895095825,True,3.217204334968887e-13,1.4396919012069702,3.7624739015695634,3.922669449686004,3.7625,3.7625,3.9225,3.9225,0.0,0.0 --6rXp3zJ3kc/8,-6rXp3zJ3kc,8,12,and,4.022500038146973,4.182499885559082,True,1.5305238223713505e-14,0.25,4.034930648788859,4.200137383139412,4.022500000000001,4.1025,4.1825,4.2225,0.07999999999999918,0.040000000000000036 --6rXp3zJ3kc/8,-6rXp3zJ3kc,8,13,they,4.322500228881836,4.502500057220459,True,1.6199097185171096e-13,0.7249060869216919,4.321713048262524,4.501433219594749,4.322500000000001,4.322500000000001,4.5025,4.5025,0.0,0.0 --6rXp3zJ3kc/8,-6rXp3zJ3kc,8,14,realize,4.622499942779541,4.982500076293945,True,5.409635413233804e-13,2.420799970626831,4.619013484915951,4.951435893611253,4.6225000000000005,4.6225000000000005,4.9225,4.982500000000001,0.0,0.0600000000000005 --6rXp3zJ3kc/8,-6rXp3zJ3kc,8,15,that,5.0625,5.362500190734863,True,1.7663386031596673e-10,4.0,5.061109736838025,5.357915223735426,5.062500000000001,5.062500000000001,5.322500000000001,5.362500000000001,0.0,0.040000000000000036 --6rXp3zJ3kc/8,-6rXp3zJ3kc,8,16,gosh,5.402500152587891,5.582499980926514,True,6.985038936146992e-11,4.0,5.412608374385401,5.583867731142024,5.402500000000001,5.442500000000001,5.5825000000000005,5.5825000000000005,0.040000000000000036,0.0 --6rXp3zJ3kc/8,-6rXp3zJ3kc,8,17,they,5.762499809265137,5.942500114440918,True,9.114082643972565e-14,0.40785321593284607,5.743872692230504,5.933506686984788,5.6225000000000005,5.7625,5.902500000000001,5.942500000000001,0.13999999999999968,0.040000000000000036 --6rXp3zJ3kc/8,-6rXp3zJ3kc,8,18,wasted,5.962500095367432,6.28249979019165,True,6.252937400584016e-15,0.25,5.9755017709324125,6.318240025679866,5.9625,6.0025,6.282500000000001,6.3425,0.040000000000000036,0.05999999999999961 --6rXp3zJ3kc/8,-6rXp3zJ3kc,8,19,a,6.362500190734863,6.382500171661377,True,9.418957584370058e-13,4.0,6.362501464590465,6.3825014645904625,6.362500000000001,6.362500000000001,6.3825,6.3825,0.0,0.0 --6rXp3zJ3kc/8,-6rXp3zJ3kc,8,20,lot,6.442500114440918,6.5625,True,1.293143381004419e-13,0.5786788463592529,6.442499934859892,6.5625000135512535,6.442500000000001,6.442500000000001,6.562500000000001,6.562500000000001,0.0,0.0 --6rXp3zJ3kc/8,-6rXp3zJ3kc,8,21,of,6.622499942779541,6.702499866485596,True,2.4035458952992306e-12,4.0,6.615005116878734,6.6837688432472016,6.5825000000000005,6.6225000000000005,6.642500000000001,6.702500000000001,0.040000000000000036,0.05999999999999961 --6rXp3zJ3kc/8,-6rXp3zJ3kc,8,22,time,6.742499828338623,7.0625,True,3.271341869810242e-14,0.25,6.7425061991759785,7.062501833718776,6.742500000000001,6.742500000000001,7.062500000000001,7.062500000000001,0.0,0.0 --6rXp3zJ3kc/8,-6rXp3zJ3kc,8,23,and,7.142499923706055,7.242499828338623,True,7.342488162614957e-15,0.25,7.114865685343713,7.23577604907428,7.0825000000000005,7.142500000000001,7.202500000000001,7.242500000000001,0.0600000000000005,0.040000000000000036 --6rXp3zJ3kc/8,-6rXp3zJ3kc,8,24,money,7.34250020980835,7.5625,True,2.4677303386497207e-13,1.1043039560317993,7.342288899962515,7.563080577866272,7.3425,7.3425,7.562500000000001,7.562500000000001,0.0,0.0 --6rXp3zJ3kc/8,-6rXp3zJ3kc,8,25,in,8.602499961853027,8.982500076293945,True,1.5762575706484983e-13,0.7053718566894531,8.364611154997718,8.85810714822456,7.602500000000001,8.6225,8.6225,8.9825,1.0199999999999996,0.35999999999999943 --6rXp3zJ3kc/8,-6rXp3zJ3kc,8,26,placing,9.0625,9.6225004196167,True,1.828831275871648e-13,0.8183979988098145,9.066924678538173,9.62794870027181,8.9625,9.3025,9.6225,9.6625,0.33999999999999986,0.03999999999999915 --6rXp3zJ3kc/8,-6rXp3zJ3kc,8,27,bets,9.642499923706055,9.882499694824219,True,4.637042486099752e-12,4.0,9.682127934242377,9.909239237242446,9.6425,9.7025,9.8825,9.9225,0.0600000000000005,0.03999999999999915 --6rXp3zJ3kc/8,-6rXp3zJ3kc,8,28,on,9.942500114440918,10.042499542236328,True,3.03088699971088e-11,4.0,9.944177340580937,10.044079828969402,9.942499999999999,9.942499999999999,10.0425,10.0425,0.0,0.0 --6rXp3zJ3kc/8,-6rXp3zJ3kc,8,29,stock,10.1225004196167,10.40250015258789,True,1.0609971966757045e-14,0.25,10.13073084545628,10.425039706715383,10.1225,10.1625,10.4025,10.5025,0.03999999999999915,0.09999999999999964 --6rXp3zJ3kc/8,-6rXp3zJ3kc,8,30,that's,10.482500076293945,10.72249984741211,True,1.9271074319648918e-11,4.0,10.493521815416006,10.722486771164357,10.4825,10.5425,10.7225,10.7225,0.0600000000000005,0.0 --6rXp3zJ3kc/8,-6rXp3zJ3kc,8,31,ultimately,10.742500305175781,11.362500190734863,True,2.4436450584384983e-13,1.0935258865356445,10.744089634125213,11.362750520402031,10.7425,10.7425,11.362499999999999,11.362499999999999,0.0,0.0 --6rXp3zJ3kc/8,-6rXp3zJ3kc,8,32,lost,11.462499618530273,11.702500343322754,True,1.1303276904414163e-14,0.25,11.458537715767447,11.702573699169442,11.442499999999999,11.4625,11.7025,11.7025,0.02000000000000135,0.0 --6rXp3zJ3kc/8,-6rXp3zJ3kc,8,33,value.,11.842499732971191,12.242500305175781,True,1.0531544169731233e-12,4.0,11.844283755647352,12.241341598308948,11.8425,11.8425,12.2425,12.2425,0.0,0.0 --9y-fZ3swSY/0,-9y-fZ3swSY,0,0,"is,",0.0024999999441206455,0.0625,True,3.060766640139434e-10,4.0,0.0025112058701024778,0.0626767445741339,0.0025000000000000005,0.0025000000000000005,0.0625,0.0625,0.0,0.0 --9y-fZ3swSY/0,-9y-fZ3swSY,0,1,you,0.12250000238418579,0.2224999964237213,True,1.535432336829956e-10,4.0,0.12240190227637165,0.22247758827306965,0.1225,0.1225,0.2225,0.2225,0.0,0.0 --9y-fZ3swSY/0,-9y-fZ3swSY,0,2,can,0.26249998807907104,0.3824999928474426,True,2.600926939100301e-11,4.0,0.2624053486672871,0.3825267286438774,0.2625,0.2625,0.3825,0.3825,0.0,0.0 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--AUZQgSxyPQ/2,-AUZQgSxyPQ,2,18,jojoba,10.462499618530273,10.962499618530273,True,1.2090047712964846e-11,2.3293211460113525,10.153471942108839,10.632818750234803,9.3825,10.5425,9.862499999999999,10.9825,1.1600000000000001,1.120000000000001 --AUZQgSxyPQ/2,-AUZQgSxyPQ,2,19,and,11.142499923706055,11.362500190734863,True,6.746394415335644e-11,4.0,10.865587426362282,11.092469474696552,10.0025,11.1425,10.4825,11.362499999999999,1.1400000000000006,0.879999999999999 --AUZQgSxyPQ/2,-AUZQgSxyPQ,2,20,acai,11.442500114440918,11.582500457763672,True,3.173180121440744e-11,4.0,11.185082640911101,11.40354090768313,10.5425,11.4825,10.8825,11.6825,0.9399999999999995,0.7999999999999989 --AUZQgSxyPQ/2,-AUZQgSxyPQ,2,21,fruit,11.702500343322754,12.5625,True,3.936610586119382e-12,0.7584445476531982,11.542750165286042,12.199442610047605,10.9825,12.3225,11.362499999999999,12.5625,1.3399999999999999,1.200000000000001 --AUZQgSxyPQ/2,-AUZQgSxyPQ,2,22,oils,12.702500343322754,12.962499618530273,True,1.2418142035508506e-11,2.392533302307129,12.312457137645003,12.53612750534288,11.4225,12.7025,11.5825,12.9625,1.2800000000000011,1.3800000000000008 --AUZQgSxyPQ/2,-AUZQgSxyPQ,2,23,and,13.0024995803833,13.182499885559082,True,1.4112935646515279e-11,2.719059705734253,12.838743358082878,13.096751343161257,12.3825,13.1025,12.522499999999999,13.6025,0.7199999999999989,1.08 --AUZQgSxyPQ/2,-AUZQgSxyPQ,2,24,bamboo,13.5625,14.0625,True,6.703672773139546e-12,1.2915587425231934,13.33881562914513,13.769541054426064,12.7025,13.7425,13.1225,14.0625,1.0399999999999991,0.9399999999999995 --AUZQgSxyPQ/2,-AUZQgSxyPQ,2,25,and,14.142499923706055,14.362500190734863,True,8.946042691360123e-12,1.7235835790634155,13.864704428194672,14.118485920377335,13.2625,14.1425,13.5825,14.362499999999999,0.8800000000000008,0.7799999999999994 --AUZQgSxyPQ/2,-AUZQgSxyPQ,2,26,prickly,14.662500381469727,15.102499961853027,True,3.0223447442662144e-13,0.25,14.322593078254965,14.767185447932158,13.6625,14.6625,14.0625,15.1025,1.0,1.0399999999999991 --AUZQgSxyPQ/2,-AUZQgSxyPQ,2,27,bear,15.702500343322754,15.862500190734863,True,4.4243590995723947e-13,0.25,15.12995941247925,15.403516804053789,14.1425,15.7025,14.362499999999999,15.8625,1.5600000000000005,1.5000000000000018 --AUZQgSxyPQ/2,-AUZQgSxyPQ,2,28,extracts,15.942500114440918,16.322500228881836,True,1.6714140650946757e-13,0.25,15.53453527528529,16.17754300405277,14.6625,15.942499999999999,15.8225,16.4025,1.2799999999999994,0.5800000000000001 --AUZQgSxyPQ/2,-AUZQgSxyPQ,2,29,deliver,16.38249969482422,16.862499237060547,True,1.0248501672955809e-13,0.25,16.270850501054223,16.686664552019476,15.942499999999999,16.5025,16.282500000000002,16.8625,0.5600000000000023,0.5799999999999983 --AUZQgSxyPQ/2,-AUZQgSxyPQ,2,30,intense,16.90250015258789,17.322500228881836,True,7.725160029899147e-13,0.25,16.78021481124627,17.24047823295799,16.5025,16.962500000000002,17.0625,17.3225,0.46000000000000085,0.26000000000000156 --AUZQgSxyPQ/2,-AUZQgSxyPQ,2,31,"healing,",17.362499237060547,18.0625,True,4.7344672805685675e-14,0.25,17.313333485444595,18.013450491442516,17.122500000000002,17.622500000000002,17.942500000000003,18.0625,0.5,0.11999999999999744 --AUZQgSxyPQ/2,-AUZQgSxyPQ,2,32,while,18.122499465942383,18.38249969482422,True,1.305523180880619e-12,0.2515277862548828,18.121970016579592,18.382910922205134,18.122500000000002,18.122500000000002,18.3825,18.3825,0.0,0.0 --AUZQgSxyPQ/2,-AUZQgSxyPQ,2,33,smooth,18.462499618530273,18.922500610351562,True,6.875201363082395e-12,1.32460618019104,18.46245288047144,18.91253360874653,18.462500000000002,18.462500000000002,18.902500000000003,18.922500000000003,0.0,0.019999999999999574 --AUZQgSxyPQ/2,-AUZQgSxyPQ,2,34,granules,19.0625,19.622499465942383,True,6.236156729899633e-11,4.0,19.060714967031537,19.62165223075318,19.0625,19.0625,19.622500000000002,19.622500000000002,0.0,0.0 --AUZQgSxyPQ/2,-AUZQgSxyPQ,2,35,buff,19.702499389648438,20.342500686645508,True,5.486440295132677e-12,1.0570415258407593,19.89197269833418,20.35923287241106,19.7025,20.122500000000002,20.3425,20.402500000000003,0.4200000000000017,0.060000000000002274 --AUZQgSxyPQ/2,-AUZQgSxyPQ,2,36,away,20.6825008392334,20.962499618530273,True,1.5412348047111335e-12,0.29694101214408875,20.646430815099194,20.960356266677547,20.402500000000003,20.6825,20.962500000000002,20.962500000000002,0.2799999999999976,0.0 --AUZQgSxyPQ/2,-AUZQgSxyPQ,2,37,"dead,",20.982500076293945,21.142499923706055,True,7.757587107415365e-12,1.4946105480194092,20.986751725007654,21.14226403506907,20.9825,21.0025,21.142500000000002,21.142500000000002,0.019999999999999574,0.0 --AUZQgSxyPQ/2,-AUZQgSxyPQ,2,38,dry,21.202499389648438,21.38249969482422,True,5.190373738445109e-12,1.0,21.20398053353988,21.388662026269635,21.2025,21.2025,21.3825,21.442500000000003,0.0,0.060000000000002274 --AUZQgSxyPQ/2,-AUZQgSxyPQ,2,39,skin,21.482500076293945,21.622499465942383,True,6.363738702663824e-11,4.0,21.480180957830996,21.622991854845147,21.4825,21.4825,21.622500000000002,21.642500000000002,0.0,0.019999999999999574 --AUZQgSxyPQ/2,-AUZQgSxyPQ,2,40,cells.,21.642499923706055,21.842500686645508,True,2.2591633425106394e-11,4.0,21.64385152483771,21.84267698383198,21.642500000000002,21.6625,21.8425,21.8425,0.019999999999999574,0.0 --HeZS2-Prhc/2,-HeZS2-Prhc,2,0,The,0.24250000715255737,0.4025000035762787,True,1.1845117768582991e-11,4.0,0.1959311331958721,0.40235082912774206,0.0425,0.2425,0.4025,0.4025,0.19999999999999998,0.0 --HeZS2-Prhc/2,-HeZS2-Prhc,2,1,August,1.402500033378601,2.122499942779541,True,1.4341861032107772e-12,0.8177534341812134,1.4478832208215444,2.1272597779712865,1.4025,1.7625,2.1225,2.1625,0.3599999999999999,0.040000000000000036 --HeZS2-Prhc/2,-HeZS2-Prhc,2,2,jobs,2.322499990463257,2.6024999618530273,True,2.558615125325403e-11,4.0,2.320611337970802,2.6004673835909573,2.3225,2.3225,2.6025,2.6025,0.0,0.0 --HeZS2-Prhc/2,-HeZS2-Prhc,2,3,report,2.682499885559082,3.002500057220459,True,2.7453449669839758e-12,1.5653584003448486,2.68170298259558,3.009440710897623,2.6825,2.6825,3.0025,3.0825,0.0,0.08000000000000007 --HeZS2-Prhc/2,-HeZS2-Prhc,2,4,is,3.0625,3.1424999237060547,True,4.514987830221001e-13,0.2574384808540344,3.0812734603350624,3.1623839522789665,3.0625,3.3225000000000002,3.1425,3.4225,0.26000000000000023,0.2799999999999998 --HeZS2-Prhc/2,-HeZS2-Prhc,2,5,out,3.322499990463257,3.4625000953674316,True,2.090342601703682e-13,0.25,3.344295656509894,3.4967551728462754,3.1625,3.8625,3.4225,3.9825,0.6999999999999997,0.56 --HeZS2-Prhc/2,-HeZS2-Prhc,2,6,and,3.862499952316284,3.9825000762939453,True,8.034748539241521e-14,0.25,3.877242383787142,4.00469880646666,3.8625,4.062500000000001,3.9825,4.242500000000001,0.20000000000000107,0.2600000000000007 --HeZS2-Prhc/2,-HeZS2-Prhc,2,7,it,4.302499771118164,4.382500171661377,True,2.6032816310625484e-13,0.25,4.275837833615807,4.386597712761713,4.202500000000001,4.3025,4.3825,4.402500000000001,0.09999999999999964,0.020000000000000462 --HeZS2-Prhc/2,-HeZS2-Prhc,2,8,was,4.502500057220459,4.702499866485596,True,6.574726874042369e-12,3.7488200664520264,4.5026476132951725,4.702857723024613,4.5025,4.5025,4.702500000000001,4.702500000000001,0.0,0.0 --HeZS2-Prhc/2,-HeZS2-Prhc,2,9,seen,5.262499809265137,5.642499923706055,True,9.668883749203161e-12,4.0,5.26248580780262,5.643139038744664,5.2625,5.2625,5.6425,5.6625000000000005,0.0,0.020000000000000462 --HeZS2-Prhc/2,-HeZS2-Prhc,2,10,overall,6.202499866485596,6.722499847412109,True,2.0734386430021345e-12,1.1822465658187866,6.135176538397465,6.722530461705236,5.7625,6.202500000000001,6.7225,6.7225,0.4400000000000004,0.0 --HeZS2-Prhc/2,-HeZS2-Prhc,2,11,as,6.802499771118164,6.882500171661377,True,8.576729821144213e-13,0.4890334904193878,6.802730239021207,6.882715843694687,6.8025,6.8025,6.8825,6.8825,0.0,0.0 --HeZS2-Prhc/2,-HeZS2-Prhc,2,12,solid,6.942500114440918,7.202499866485596,True,8.672484930714874e-13,0.494493305683136,6.944034109898724,7.203577690574796,6.942500000000001,6.942500000000001,7.202500000000001,7.202500000000001,0.0,0.0 --HeZS2-Prhc/2,-HeZS2-Prhc,2,13,but,7.34250020980835,7.602499961853027,True,3.902187947768532e-11,4.0,7.342753371410023,7.602373466405716,7.3425,7.3425,7.602500000000001,7.602500000000001,0.0,0.0 --HeZS2-Prhc/2,-HeZS2-Prhc,2,14,not,7.662499904632568,7.802499771118164,True,2.746409328256705e-13,0.25,7.663526959768611,7.802856928638411,7.6625000000000005,7.6625000000000005,7.8025,7.8025,0.0,0.0 --HeZS2-Prhc/2,-HeZS2-Prhc,2,15,great.,7.862500190734863,8.082500457763672,True,2.701561847492928e-12,1.5403938293457031,7.8635557979644375,8.088359004012458,7.862500000000001,7.862500000000001,8.0825,8.1225,0.0,0.040000000000000924 --MeTTeMJBNc/0,-MeTTeMJBNc,0,0,"Okay,",0.9424999952316284,1.2424999475479126,True,3.710065674816798e-12,4.0,0.9432326596664109,1.2056759510520048,0.9225,1.0025,1.1025,1.2425,0.07999999999999996,0.1399999999999999 --MeTTeMJBNc/0,-MeTTeMJBNc,0,1,what,1.3025000095367432,1.502500057220459,True,1.2836673354322831e-14,1.0,1.2968934930611797,1.4994382940713709,1.3025,1.3025,1.5025,1.5025,0.0,0.0 --MeTTeMJBNc/0,-MeTTeMJBNc,0,2,happens,1.5625,2.122499942779541,True,1.206398787698083e-14,0.9398064017295837,1.558655575902781,2.121205916667169,1.5425,1.5625,2.1225,2.1225,0.020000000000000018,0.0 --MeTTeMJBNc/0,-MeTTeMJBNc,0,3,at,2.202500104904175,2.2825000286102295,True,2.9099730082044395e-15,0.25,2.1952647147514655,2.2751562874460314,2.1425,2.2025,2.2225,2.2825,0.06000000000000005,0.06000000000000005 --MeTTeMJBNc/0,-MeTTeMJBNc,0,4,this,2.322499990463257,2.4825000762939453,True,3.948112470227071e-15,0.3075650930404663,2.3262151924486174,2.488170818444105,2.3225,2.3625,2.4825,2.5225,0.040000000000000036,0.040000000000000036 --MeTTeMJBNc/0,-MeTTeMJBNc,0,5,point,2.5225000381469727,2.882499933242798,True,3.802389345497915e-15,0.29621297121047974,2.5670758567670444,2.901260034406884,2.5225,2.6225,2.8825,2.9225,0.10000000000000009,0.040000000000000036 --MeTTeMJBNc/0,-MeTTeMJBNc,0,6,after,3.202500104904175,3.422499895095825,True,4.455512734203183e-15,0.34709247946739197,3.1913281357894654,3.419919056829773,3.1825,3.2025,3.3825,3.4225,0.020000000000000018,0.040000000000000036 --MeTTeMJBNc/0,-MeTTeMJBNc,0,7,we've,3.4625000953674316,3.682499885559082,True,1.9134102288709265e-11,4.0,3.4638915322588497,3.6825000001063266,3.4625,3.4625,3.6825,3.6825,0.0,0.0 --MeTTeMJBNc/0,-MeTTeMJBNc,0,8,taken,3.7225000858306885,4.002500057220459,True,3.697702849480861e-15,0.28805771470069885,3.7225000291431787,4.010663846188186,3.7225,3.7225,4.0025,4.0425,0.0,0.040000000000000036 --MeTTeMJBNc/0,-MeTTeMJBNc,0,9,this,4.042500019073486,4.222499847412109,True,1.42208513980455e-14,1.1078299283981323,4.0553085178820885,4.231976591647393,4.0425,4.1025,4.2225,4.2625,0.05999999999999961,0.040000000000000036 --MeTTeMJBNc/0,-MeTTeMJBNc,0,10,brief,4.462500095367432,4.702499866485596,True,1.0028261925834787e-14,0.7812196612358093,4.462443349973335,4.704718386141115,4.4625,4.4625,4.702500000000001,4.702500000000001,0.0,0.0 --MeTTeMJBNc/0,-MeTTeMJBNc,0,11,walk,4.78249979019165,5.142499923706055,True,6.560490405050842e-15,0.5110740065574646,4.813190037922622,5.151410892553026,4.7625,4.8825,5.1425,5.1825,0.1200000000000001,0.040000000000000036 --MeTTeMJBNc/0,-MeTTeMJBNc,0,12,down,5.202499866485596,5.462500095367432,True,7.031535591414326e-14,4.0,5.203195360240823,5.463194049014288,5.202500000000001,5.202500000000001,5.4625,5.4625,0.0,0.0 --MeTTeMJBNc/0,-MeTTeMJBNc,0,13,memory,5.582499980926514,5.902500152587891,True,2.5533394842902624e-13,4.0,5.582483141326186,5.9028098326745795,5.5825000000000005,5.5825000000000005,5.902500000000001,5.902500000000001,0.0,0.0 --MeTTeMJBNc/0,-MeTTeMJBNc,0,14,"lane,",5.962500095367432,6.302499771118164,True,3.5930408496566424e-13,4.0,5.975316507304133,6.305343427476204,5.9625,6.142500000000001,6.3025,6.3425,0.1800000000000006,0.040000000000000036 --MeTTeMJBNc/0,-MeTTeMJBNc,0,15,is,6.84250020980835,6.902500152587891,True,7.547921489214904e-12,4.0,6.8424998796201235,6.902499886452121,6.8425,6.8425,6.902500000000001,6.902500000000001,0.0,0.0 --MeTTeMJBNc/0,-MeTTeMJBNc,0,16,the,6.982500076293945,7.082499980926514,True,3.779567948558279e-16,0.25,6.9590939849105835,7.061940314452324,6.942500000000001,6.982500000000001,7.0425,7.0825000000000005,0.040000000000000036,0.040000000000000036 --MeTTeMJBNc/0,-MeTTeMJBNc,0,17,presentation,7.122499942779541,7.862500190734863,True,3.29521523931872e-15,0.2567031979560852,7.122435235689702,7.862573230447805,7.1225000000000005,7.1225000000000005,7.862500000000001,7.862500000000001,0.0,0.0 --MeTTeMJBNc/0,-MeTTeMJBNc,0,18,of,7.902500152587891,7.962500095367432,True,4.660046220433811e-13,4.0,7.903398437119373,7.963914730371576,7.902500000000001,7.902500000000001,7.9625,7.9625,0.0,0.0 --MeTTeMJBNc/0,-MeTTeMJBNc,0,19,the,8.042499542236328,8.162500381469727,True,4.581407410560179e-14,3.5689990520477295,8.064463282027926,8.1771366928654,8.0425,8.1025,8.1625,8.202499999999999,0.05999999999999872,0.03999999999999915 --MeTTeMJBNc/0,-MeTTeMJBNc,0,20,gift.,8.242500305175781,8.582500457763672,True,2.0623882376197278e-12,4.0,8.242500389132172,8.582544997263367,8.2425,8.2425,8.5825,8.5825,0.0,0.0 --MeTTeMJBNc/13,-MeTTeMJBNc,13,0,It,0.3425000011920929,0.4424999952316284,True,1.1344515604694294e-11,4.0,0.34125700409427956,0.4421278439000176,0.3425,0.3425,0.4425,0.4425,0.0,0.0 --MeTTeMJBNc/13,-MeTTeMJBNc,13,1,just,0.5024999976158142,1.3224999904632568,True,7.597669889058967e-12,4.0,0.6357895630564467,1.3217086751335387,0.5025,1.0625,1.3225,1.3225,0.56,0.0 --MeTTeMJBNc/13,-MeTTeMJBNc,13,2,needs,1.402500033378601,1.6425000429153442,True,1.3798399814239637e-13,2.5175373554229736,1.4024617994614186,1.6427802038920662,1.4025,1.4025,1.6425,1.6425,0.0,0.0 --MeTTeMJBNc/13,-MeTTeMJBNc,13,3,to,1.722499966621399,1.7825000286102295,True,1.4288968093597795e-14,0.2607042193412781,1.722500342761648,1.7825003763940888,1.7225,1.7225,1.7825,1.7825,0.0,0.0 --MeTTeMJBNc/13,-MeTTeMJBNc,13,4,be,1.8424999713897705,1.9225000143051147,True,4.578755452046279e-13,4.0,1.8425000061154377,1.922500028437251,1.8425,1.8425,1.9224999999999999,1.9224999999999999,0.0,0.0 --MeTTeMJBNc/13,-MeTTeMJBNc,13,5,a,2.0225000381469727,2.0425000190734863,True,4.161020486503908e-11,4.0,2.022500304881204,2.0425003048812034,2.0225,2.0225,2.0425,2.0425,0.0,0.0 --MeTTeMJBNc/13,-MeTTeMJBNc,13,6,simple,2.2225000858306885,2.5625,True,1.4861399057989472e-13,2.7114830017089844,2.2205922795367226,2.562499455730098,2.2225,2.2225,2.5625,2.5625,0.0,0.0 --MeTTeMJBNc/13,-MeTTeMJBNc,13,7,"statement,",2.5824999809265137,3.202500104904175,True,3.476265990695485e-15,0.25,2.5825113951826295,3.202756423531097,2.5825,2.5825,3.2025,3.2025,0.0,0.0 --MeTTeMJBNc/13,-MeTTeMJBNc,13,8,and,3.2225000858306885,3.6424999237060547,True,1.5177185476813494e-14,0.27690985798835754,3.230022374213786,3.639560341276429,3.2225,3.2225,3.6025,3.6425,0.0,0.040000000000000036 --MeTTeMJBNc/13,-MeTTeMJBNc,13,9,then,3.6624999046325684,3.802500009536743,True,8.128732731618369e-16,0.25,3.6595605480135602,3.799753359197992,3.6225,3.6625,3.7625,3.8025,0.040000000000000036,0.040000000000000036 --MeTTeMJBNc/13,-MeTTeMJBNc,13,10,you,3.822499990463257,3.922499895095825,True,3.6388318573610245e-14,0.6639099717140198,3.82250569880218,3.9263450272879767,3.8225000000000002,3.8225000000000002,3.9225,3.9425,0.0,0.020000000000000018 --MeTTeMJBNc/13,-MeTTeMJBNc,13,11,present,3.9825000762939453,4.34250020980835,True,5.4407035314182374e-15,0.25,3.982499819073152,4.342058126051071,3.9825,3.9825,4.3425,4.3425,0.0,0.0 --MeTTeMJBNc/13,-MeTTeMJBNc,13,12,the,4.362500190734863,4.482500076293945,True,4.4931062586879914e-14,0.8197734951972961,4.362503466738968,4.482502178652516,4.362500000000001,4.362500000000001,4.482500000000001,4.482500000000001,0.0,0.0 --MeTTeMJBNc/13,-MeTTeMJBNc,13,13,gift.,4.522500038146973,4.862500190734863,True,6.468716756908091e-14,1.180226445198059,4.5225058016335105,4.862473226976465,4.522500000000001,4.522500000000001,4.862500000000001,4.862500000000001,0.0,0.0 --MeTTeMJBNc/7,-MeTTeMJBNc,7,0,Maybe,0.042500000447034836,0.3824999928474426,True,3.770235466600373e-14,0.9178741574287415,0.04382005310267007,0.37623012683122026,0.0425,0.0625,0.3425,0.3825,0.019999999999999997,0.03999999999999998 --MeTTeMJBNc/7,-MeTTeMJBNc,7,1,you,0.6025000214576721,0.7425000071525574,True,2.4669209383598734e-11,4.0,0.6014484098137175,0.7393633434603328,0.5425,0.6224999999999999,0.7025,0.7424999999999999,0.07999999999999996,0.039999999999999925 --MeTTeMJBNc/7,-MeTTeMJBNc,7,2,could,0.8025000095367432,1.1425000429153442,True,6.561903256006862e-14,1.5975133180618286,0.8039196735936374,1.1445578036248207,0.8025,0.8025,1.1425,1.1824999999999999,0.0,0.039999999999999813 --MeTTeMJBNc/7,-MeTTeMJBNc,7,3,find,1.5625,1.8424999713897705,True,4.50442504476567e-12,4.0,1.561707044410993,1.8424368444910948,1.5625,1.5625,1.8425,1.8425,0.0,0.0 --MeTTeMJBNc/7,-MeTTeMJBNc,7,4,a,1.9424999952316284,1.962499976158142,True,3.019118375441332e-12,4.0,1.9424658593762911,1.962465859376291,1.9425,1.9425,1.9625,1.9625,0.0,0.0 --MeTTeMJBNc/7,-MeTTeMJBNc,7,5,picture,2.002500057220459,2.362499952316284,True,2.292061499094538e-14,0.5580086708068848,2.0026882078534736,2.377115832890999,2.0025,2.0025,2.3625,2.4025,0.0,0.040000000000000036 --MeTTeMJBNc/7,-MeTTeMJBNc,7,6,of,2.422499895095825,2.4825000762939453,True,5.609922791062483e-13,4.0,2.4277161082497907,2.498121486901269,2.4225,2.4625,2.4825,2.5625,0.040000000000000036,0.08000000000000007 --MeTTeMJBNc/7,-MeTTeMJBNc,7,7,the,2.5824999809265137,2.682499885559082,True,8.198723275808228e-15,0.25,2.579265356662479,2.6792832693436104,2.5425,2.5825,2.6425,2.6825,0.040000000000000036,0.040000000000000036 --MeTTeMJBNc/7,-MeTTeMJBNc,7,8,couple,2.702500104904175,3.0425000190734863,True,2.822629892947244e-14,0.6871770024299622,2.699416899972035,3.0720880659627245,2.6625,2.7025,3.0425,3.1025,0.040000000000000036,0.06000000000000005 --MeTTeMJBNc/7,-MeTTeMJBNc,7,9,from,3.0824999809265137,3.322499990463257,True,3.6664202286728655e-15,0.25,3.126486933752154,3.3590129371154913,3.0825,3.1625,3.3225000000000002,3.4225,0.08000000000000007,0.09999999999999964 --MeTTeMJBNc/7,-MeTTeMJBNc,7,10,their,3.4625000953674316,3.922499895095825,True,1.8800955055493264e-14,0.45771440863609314,3.462535896135531,3.9223684291480794,3.4625,3.4625,3.9225,3.9225,0.0,0.0 --MeTTeMJBNc/7,-MeTTeMJBNc,7,11,wedding,3.942500114440918,4.442500114440918,True,4.442729279081903e-13,4.0,3.942471261233754,4.44238517073405,3.9425,3.9425,4.442500000000001,4.442500000000001,0.0,0.0 --MeTTeMJBNc/7,-MeTTeMJBNc,7,12,or,4.642499923706055,4.702499866485596,True,2.026530222657471e-14,0.4933643341064453,4.642065602925446,4.702431704556223,4.6425,4.6425,4.702500000000001,4.702500000000001,0.0,0.0 --MeTTeMJBNc/7,-MeTTeMJBNc,7,13,sometime,4.902500152587891,5.362500190734863,True,3.989258874409138e-14,0.9711959958076477,4.86246421614156,5.34648215111066,4.8025,4.902500000000001,5.322500000000001,5.362500000000001,0.10000000000000053,0.040000000000000036 --MeTTeMJBNc/7,-MeTTeMJBNc,7,14,in,5.382500171661377,5.442500114440918,True,2.355478347635699e-15,0.25,5.382091465093613,5.442262434223061,5.3825,5.3825,5.442500000000001,5.442500000000001,0.0,0.0 --MeTTeMJBNc/7,-MeTTeMJBNc,7,15,their,5.462500095367432,5.682499885559082,True,6.219688816305443e-15,0.25,5.462726237673856,5.682500012758481,5.4625,5.4625,5.6825,5.6825,0.0,0.0 --MeTTeMJBNc/7,-MeTTeMJBNc,7,16,"life,",5.722499847412109,6.042500019073486,True,9.027134074968135e-12,4.0,5.722500033125576,6.042499810582332,5.7225,5.7225,6.0425,6.0425,0.0,0.0 --MeTTeMJBNc/7,-MeTTeMJBNc,7,17,or,6.082499980926514,6.182499885559082,True,3.5410132400055805e-13,4.0,6.0825677398853735,6.184103345429151,6.0825000000000005,6.0825000000000005,6.1825,6.202500000000001,0.0,0.020000000000000462 --MeTTeMJBNc/7,-MeTTeMJBNc,7,18,maybe,6.262499809265137,6.462500095367432,True,1.1368580772955217e-12,4.0,6.2625000261871655,6.462574470158711,6.2625,6.2625,6.4625,6.4625,0.0,0.0 --MeTTeMJBNc/7,-MeTTeMJBNc,7,19,even,6.582499980926514,6.762499809265137,True,1.2781007805925948e-12,4.0,6.549329203691951,6.727341946384188,6.5025,6.5825000000000005,6.702500000000001,6.7625,0.08000000000000007,0.05999999999999961 --MeTTeMJBNc/7,-MeTTeMJBNc,7,20,a,6.802499771118164,6.822500228881836,True,7.715516593675975e-12,4.0,6.802500479833359,6.822500479833361,6.8025,6.8025,6.822500000000001,6.822500000000001,0.0,0.0 --MeTTeMJBNc/7,-MeTTeMJBNc,7,21,current,6.922500133514404,7.322500228881836,True,4.107573452921155e-14,1.0,6.913379676245901,7.315998196321345,6.8425,6.9225,7.2625,7.322500000000001,0.08000000000000007,0.0600000000000005 --MeTTeMJBNc/7,-MeTTeMJBNc,7,22,picture,7.362500190734863,7.822500228881836,True,5.0320147083459527e-14,1.2250577211380005,7.362392721111548,7.822399324363143,7.362500000000001,7.362500000000001,7.822500000000001,7.822500000000001,0.0,0.0 --MeTTeMJBNc/7,-MeTTeMJBNc,7,23,and,7.84250020980835,8.262499809265137,True,2.99166141620906e-14,0.7283281683921814,7.899502149493908,8.268061882040197,7.8425,8.202499999999999,8.2625,8.3025,0.35999999999999854,0.040000000000000924 --MeTTeMJBNc/7,-MeTTeMJBNc,7,24,have,8.282500267028809,8.422499656677246,True,3.7114418932919155e-14,0.9035606980323792,8.288246235381468,8.42975344190582,8.282499999999999,8.3225,8.4225,8.4625,0.040000000000000924,0.040000000000000924 --MeTTeMJBNc/7,-MeTTeMJBNc,7,25,it,8.482500076293945,8.542499542236328,True,3.107029336504169e-13,4.0,8.482487466508353,8.542487472734381,8.4825,8.4825,8.5425,8.5425,0.0,0.0 --MeTTeMJBNc/7,-MeTTeMJBNc,7,26,put,8.582500457763672,8.72249984741211,True,1.557926015841385e-14,0.37928134202957153,8.582500416372213,8.722595724165645,8.5825,8.5825,8.7225,8.7225,0.0,0.0 --MeTTeMJBNc/7,-MeTTeMJBNc,7,27,in,8.782500267028809,8.842499732971191,True,1.3454399236162342e-14,0.3275510370731354,8.771773292426657,8.83177402315951,8.7425,8.782499999999999,8.8025,8.8425,0.03999999999999915,0.03999999999999915 --MeTTeMJBNc/7,-MeTTeMJBNc,7,28,a,8.862500190734863,8.882499694824219,True,1.2338593417381832e-13,3.003864288330078,8.862501392958345,8.882501392958348,8.862499999999999,8.862499999999999,8.8825,8.8825,0.0,0.0 --MeTTeMJBNc/7,-MeTTeMJBNc,7,29,beautiful,8.922499656677246,9.342499732971191,True,1.4680022876554372e-14,0.3573891818523407,8.922499999807949,9.342591336440261,8.9225,8.9225,9.3425,9.3425,0.0,0.0 --MeTTeMJBNc/7,-MeTTeMJBNc,7,30,frame.,9.40250015258789,9.842499732971191,True,2.176588553490233e-12,4.0,9.402788993999224,9.842498636710845,9.4025,9.4025,9.8425,9.8425,0.0,0.0 --RfYyzHpjk4/11,-RfYyzHpjk4,11,0,So,0.5625,0.7225000262260437,True,5.925417491739471e-13,1.2584871053695679,0.6104202949033318,0.7450530455063744,0.5625,0.7025,0.7224999999999999,0.8225,0.14,0.10000000000000009 --RfYyzHpjk4/11,-RfYyzHpjk4,11,1,get,1.0425000190734863,1.162500023841858,True,2.0000498653083287e-12,4.0,1.0352633548141328,1.157345829119535,1.0425,1.0425,1.1624999999999999,1.1624999999999999,0.0,0.0 --RfYyzHpjk4/11,-RfYyzHpjk4,11,2,your,1.222499966621399,1.462499976158142,True,3.061544344862971e-13,0.6502349972724915,1.2204229605923966,1.4590623617756209,1.2225,1.2225,1.4625,1.4625,0.0,0.0 --RfYyzHpjk4/11,-RfYyzHpjk4,11,3,friends,1.5425000190734863,1.8624999523162842,True,4.583915644523588e-14,0.25,1.5348954679823508,1.8560549491335907,1.5225,1.5425,1.8225,1.8625,0.020000000000000018,0.040000000000000036 --RfYyzHpjk4/11,-RfYyzHpjk4,11,4,lined,1.8825000524520874,2.0824999809265137,True,4.106438279694036e-12,4.0,1.8794013903302467,2.108598210328863,1.8825,1.8825,2.0825,2.1425,0.0,0.06000000000000005 --RfYyzHpjk4/11,-RfYyzHpjk4,11,5,"up,",2.1024999618530273,2.1624999046325684,True,2.6779603925011775e-14,0.25,2.132709439233833,2.1930046249082458,2.1025,2.1625,2.1625,2.2225,0.06000000000000005,0.06000000000000005 --RfYyzHpjk4/11,-RfYyzHpjk4,11,6,get,2.242500066757202,2.362499952316284,True,1.191502972675007e-11,4.0,2.236394349302283,2.3507283319084338,2.2025,2.2425,2.3025,2.3625,0.040000000000000036,0.05999999999999961 --RfYyzHpjk4/11,-RfYyzHpjk4,11,7,your,2.4024999141693115,2.5625,True,8.169106125062442e-13,1.7350194454193115,2.3922253609813726,2.5522580570477773,2.3625,2.4025,2.5225,2.5625,0.040000000000000036,0.040000000000000036 --RfYyzHpjk4/11,-RfYyzHpjk4,11,8,business,2.5824999809265137,2.9625000953674316,True,2.262260609961833e-13,0.4804767966270447,2.5807347769870606,2.959944910812453,2.5825,2.5825,2.9625,2.9625,0.0,0.0 --RfYyzHpjk4/11,-RfYyzHpjk4,11,9,colleagues,2.9825000762939453,3.502500057220459,True,1.0240140332906655e-11,4.0,2.980355311251425,3.5007947034242104,2.9825,2.9825,3.5025,3.5025,0.0,0.0 --RfYyzHpjk4/11,-RfYyzHpjk4,11,10,lined,3.5425000190734863,3.762500047683716,True,1.963730014101911e-13,0.4170725345611572,3.540848027479565,3.7591541239086355,3.5425,3.5425,3.7225,3.7625,0.0,0.040000000000000036 --RfYyzHpjk4/11,-RfYyzHpjk4,11,11,up,3.802500009536743,3.862499952316284,True,2.895594734039081e-13,0.6149893403053284,3.8011925535359468,3.8611960341643234,3.8025,3.8025,3.8625,3.8625,0.0,0.0 --RfYyzHpjk4/11,-RfYyzHpjk4,11,12,and,3.9024999141693115,4.042500019073486,True,4.708365858654973e-13,1.0,3.9015861885760605,4.035220914868527,3.9025,3.9025,4.022500000000001,4.0425,0.0,0.019999999999999574 --RfYyzHpjk4/11,-RfYyzHpjk4,11,13,have,4.122499942779541,4.262499809265137,True,1.2910945099489646e-13,0.27421286702156067,4.1214453840766305,4.266966117222006,4.1225000000000005,4.1225000000000005,4.2625,4.282500000000001,0.0,0.020000000000000462 --RfYyzHpjk4/11,-RfYyzHpjk4,11,14,a,4.302499771118164,4.322500228881836,True,1.385675343863529e-14,0.25,4.302061162786527,4.322061162786528,4.3025,4.3025,4.322500000000001,4.322500000000001,0.0,0.0 --RfYyzHpjk4/11,-RfYyzHpjk4,11,15,good,4.442500114440918,4.762499809265137,True,2.0156643281560305e-12,4.0,4.440412188277476,4.761898046857764,4.4225,4.442500000000001,4.7625,4.7625,0.020000000000000462,0.0 --RfYyzHpjk4/11,-RfYyzHpjk4,11,16,time.,4.84250020980835,5.042500019073486,True,3.757925221004044e-11,4.0,4.8422608498843465,5.0426273492741265,4.8425,4.8425,5.0425,5.0425,0.0,0.0 --RfYyzHpjk4/8,-RfYyzHpjk4,8,0,It's,0.48249998688697815,0.5824999809265137,True,1.4532529624133872e-09,4.0,0.29136950661161193,0.581764070401369,0.0025000000000000005,0.4825,0.5824999999999999,0.5824999999999999,0.48,0.0 --RfYyzHpjk4/8,-RfYyzHpjk4,8,1,"pretty,",0.6025000214576721,0.9624999761581421,True,1.087615783025575e-13,0.44241130352020264,0.602707872197142,0.9658396862173649,0.6024999999999999,0.6024999999999999,0.9624999999999999,1.0025,0.0,0.040000000000000036 --RfYyzHpjk4/8,-RfYyzHpjk4,8,2,pretty,0.9825000166893005,1.3025000095367432,True,1.235450950527392e-13,0.502546489238739,0.9901859507557427,1.3023208099968344,0.9824999999999999,1.0425,1.3025,1.3025,0.06000000000000005,0.0 --RfYyzHpjk4/8,-RfYyzHpjk4,8,3,easy,1.3424999713897705,1.5225000381469727,True,1.3342861429448127e-13,0.54274982213974,1.3425056143864518,1.5225050163964364,1.3425,1.3425,1.5225,1.5225,0.0,0.0 --RfYyzHpjk4/8,-RfYyzHpjk4,8,4,to,1.5625,1.6425000429153442,True,1.0378338101836148e-14,0.25,1.5678174351393568,1.645624593702227,1.5625,1.6225,1.6425,1.6824999999999999,0.06000000000000005,0.039999999999999813 --RfYyzHpjk4/8,-RfYyzHpjk4,8,5,do,1.7024999856948853,1.8025000095367432,True,5.799786649204886e-13,2.359189033508301,1.702500208385816,1.8025001764746025,1.7025,1.7025,1.8025,1.8025,0.0,0.0 --RfYyzHpjk4/8,-RfYyzHpjk4,8,6,but,1.8825000524520874,2.002500057220459,True,9.461694292910595e-15,0.25,1.8798579047304698,2.0026025026774623,1.8625,1.8825,2.0025,2.0025,0.020000000000000018,0.0 --RfYyzHpjk4/8,-RfYyzHpjk4,8,7,you,2.0425000190734863,2.1624999046325684,True,3.8030705971567325e-13,1.5469814538955688,2.0420726874845885,2.161792162433309,2.0425,2.0425,2.1625,2.1625,0.0,0.0 --RfYyzHpjk4/8,-RfYyzHpjk4,8,8,got,2.202500104904175,2.302500009536743,True,2.636872518295766e-14,0.25,2.2024992287053813,2.3025002711087743,2.2025,2.2025,2.3025,2.3025,0.0,0.0 --RfYyzHpjk4/8,-RfYyzHpjk4,8,9,to,2.3424999713897705,2.4024999141693115,True,5.37920436546966e-14,0.25,2.342231385558277,2.402500610322223,2.3425,2.3425,2.4025,2.4025,0.0,0.0 --RfYyzHpjk4/8,-RfYyzHpjk4,8,10,set,2.442500114440918,2.6024999618530273,True,8.723621326180153e-13,3.5485222339630127,2.4425000521424303,2.6025000862422343,2.4425,2.4425,2.6025,2.6025,0.0,0.0 --RfYyzHpjk4/8,-RfYyzHpjk4,8,11,up,2.682499885559082,2.762500047683716,True,1.8668987796649494e-12,4.0,2.6824947822719523,2.762491370232272,2.6825,2.6825,2.7625,2.7625,0.0,0.0 --RfYyzHpjk4/8,-RfYyzHpjk4,8,12,those,2.8424999713897705,3.0225000381469727,True,4.680378805875518e-13,1.9038455486297607,2.8410879425174627,3.021367438715059,2.8425,2.8425,3.0225,3.0225,0.0,0.0 --RfYyzHpjk4/8,-RfYyzHpjk4,8,13,numbers,3.0425000190734863,3.382499933242798,True,3.799781940917041e-13,1.54564368724823,3.0424927295428903,3.382497615488898,3.0425,3.0425,3.3825,3.3825,0.0,0.0 --RfYyzHpjk4/8,-RfYyzHpjk4,8,14,ahead,3.422499895095825,3.622499942779541,True,2.4583815343669213e-13,1.0,3.4224973293396848,3.623183535894426,3.4225,3.4225,3.6225,3.6225,0.0,0.0 --RfYyzHpjk4/8,-RfYyzHpjk4,8,15,of,3.862499952316284,3.942500114440918,True,4.153858246952469e-12,4.0,3.8543357537960174,3.9395657009074068,3.7025,3.8625,3.9225,3.9425,0.1599999999999997,0.020000000000000018 --RfYyzHpjk4/8,-RfYyzHpjk4,8,16,time.,3.9825000762939453,4.522500038146973,True,2.1563972124865466e-13,0.8771613240242004,3.987601471873267,4.522151300490132,3.9825,3.9825,4.522500000000001,4.522500000000001,0.0,0.0 --RfYyzHpjk4/2,-RfYyzHpjk4,2,0,You,0.5024999976158142,0.6025000214576721,True,3.148869782542557e-13,0.5932096838951111,0.4641556042763561,0.6001832615386288,0.2025,0.5025,0.5824999999999999,0.6024999999999999,0.29999999999999993,0.020000000000000018 --RfYyzHpjk4/2,-RfYyzHpjk4,2,1,can,0.6225000023841858,0.7225000262260437,True,5.3242779109174965e-12,4.0,0.6224966097439738,0.722793687589131,0.6224999999999999,0.6224999999999999,0.7224999999999999,0.7224999999999999,0.0,0.0 --RfYyzHpjk4/2,-RfYyzHpjk4,2,2,make,0.762499988079071,0.9024999737739563,True,9.325262784187771e-12,4.0,0.7624999520131719,0.902500457618032,0.7625,0.7625,0.9025,0.9025,0.0,0.0 --RfYyzHpjk4/2,-RfYyzHpjk4,2,3,a,0.9225000143051147,0.9424999952316284,True,5.164016322846063e-14,0.25,0.9225004608316872,0.9425004608316874,0.9225,0.9225,0.9425,0.9425,0.0,0.0 --RfYyzHpjk4/2,-RfYyzHpjk4,2,4,conference,0.9624999761581421,1.3624999523162842,True,2.2286452197595175e-12,4.0,0.9625004885635444,1.36250528925742,0.9624999999999999,0.9624999999999999,1.3625,1.3625,0.0,0.0 --RfYyzHpjk4/2,-RfYyzHpjk4,2,5,call,1.3825000524520874,1.5225000381469727,True,1.5288667684285051e-12,2.8802037239074707,1.3825053283407196,1.5225057774228026,1.3825,1.3825,1.5225,1.5225,0.0,0.0 --RfYyzHpjk4/2,-RfYyzHpjk4,2,6,but,1.5625,1.662500023841858,True,3.5439503436908437e-13,0.6676381826400757,1.5625044965401071,1.6625261687119126,1.5625,1.5625,1.6625,1.6625,0.0,0.0 --RfYyzHpjk4/2,-RfYyzHpjk4,2,7,it,1.6825000047683716,1.7424999475479126,True,1.332392182695763e-11,4.0,1.682547174299906,1.7425472119934313,1.6824999999999999,1.6824999999999999,1.7425,1.7425,0.0,0.0 --RfYyzHpjk4/2,-RfYyzHpjk4,2,8,takes,1.7625000476837158,1.9424999952316284,True,1.057303116586139e-11,4.0,1.762547757390463,1.9664725912063723,1.7625,1.7625,1.9425,2.0025,0.0,0.06000000000000005 --RfYyzHpjk4/2,-RfYyzHpjk4,2,9,quite,1.9824999570846558,2.182499885559082,True,8.99263163933739e-11,4.0,1.9998589771697997,2.2030919285306947,1.9825,2.0225,2.1825,2.2425,0.040000000000000036,0.06000000000000005 --RfYyzHpjk4/2,-RfYyzHpjk4,2,10,a,2.202500104904175,2.2225000858306885,True,6.754598508122711e-14,0.25,2.2377339721451066,2.257733972145132,2.2025,2.2825,2.2225,2.3025,0.08000000000000007,0.08000000000000007 --RfYyzHpjk4/2,-RfYyzHpjk4,2,11,bit,2.242500066757202,2.3424999713897705,True,5.308189868560853e-13,1.0,2.2777869381841898,2.3777903079199927,2.2425,2.3225,2.3425,2.4225,0.07999999999999963,0.08000000000000007 --RfYyzHpjk4/2,-RfYyzHpjk4,2,12,of,2.362499952316284,2.422499895095825,True,2.1314319666870807e-13,0.4015364944934845,2.402322583593929,2.4623288813321236,2.3625,2.4825,2.4225,2.5425,0.1200000000000001,0.1200000000000001 --RfYyzHpjk4/2,-RfYyzHpjk4,2,13,"planning,",2.442500114440918,2.802500009536743,True,8.171992948871956e-14,0.25,2.491071073576032,2.876893066167285,2.4425,2.5825,2.8025,2.9825,0.14000000000000012,0.17999999999999972 --RfYyzHpjk4/2,-RfYyzHpjk4,2,14,well,2.8424999713897705,2.9825000762939453,True,1.5282908402344808e-13,0.28791186213493347,2.9062972987384375,3.0472606332625687,2.8225,3.0025,2.9825,3.1425,0.18000000000000016,0.16000000000000014 --RfYyzHpjk4/2,-RfYyzHpjk4,2,15,not,3.002500057220459,3.1024999618530273,True,1.5203597658174778e-13,0.28641775250434875,3.0757937390130943,3.190636335135603,3.0025,3.1825,3.1025,3.3225000000000002,0.18000000000000016,0.2200000000000002 --RfYyzHpjk4/2,-RfYyzHpjk4,2,16,a,3.122499942779541,3.1424999237060547,True,5.646774280804179e-12,4.0,3.2204657819657214,3.2404657819657814,3.1225,3.3625,3.1425,3.3825,0.23999999999999977,0.23999999999999977 --RfYyzHpjk4/2,-RfYyzHpjk4,2,17,lot,3.182499885559082,3.322499990463257,True,2.893943290842478e-14,0.25,3.284991537547337,3.429295019753589,3.1825,3.4625,3.3025,3.6225,0.2799999999999998,0.31999999999999984 --RfYyzHpjk4/2,-RfYyzHpjk4,2,18,of,3.362499952316284,3.442500114440918,True,7.363686049810525e-12,4.0,3.5028824001740775,3.5721282708109663,3.3625,3.7225,3.4225,3.7825,0.3600000000000003,0.3600000000000003 --RfYyzHpjk4/2,-RfYyzHpjk4,2,19,planning,3.4625000953674316,3.882499933242798,True,4.804686379658585e-13,0.9051459431648254,3.6038900191011245,4.016084286438504,3.4625,3.8225000000000002,3.8825,4.242500000000001,0.3600000000000003,0.36000000000000076 --RfYyzHpjk4/2,-RfYyzHpjk4,2,20,it's,3.9825000762939453,4.162499904632568,True,4.394659983142368e-12,4.0,4.101904154902036,4.272254213499532,3.9825,4.3025,4.1625000000000005,4.442500000000001,0.3200000000000003,0.28000000000000025 --RfYyzHpjk4/2,-RfYyzHpjk4,2,21,pretty,4.28249979019165,4.582499980926514,True,3.0015099021681035e-13,0.5654488801956177,4.3755106093167,4.666803222682432,4.282500000000001,4.522500000000001,4.5825000000000005,4.822500000000001,0.2400000000000002,0.2400000000000002 --RfYyzHpjk4/2,-RfYyzHpjk4,2,22,easy,4.602499961853027,4.802499771118164,True,1.904853228276715e-13,0.35885176062583923,4.695244949059977,4.955538123762717,4.602500000000001,4.862500000000001,4.8025,5.202500000000001,0.2599999999999998,0.40000000000000036 --RfYyzHpjk4/2,-RfYyzHpjk4,2,23,to,5.182499885559082,5.262499809265137,True,6.027319702367473e-12,4.0,5.204784669311505,5.2778043991771115,5.1825,5.242500000000001,5.2625,5.3025,0.0600000000000005,0.040000000000000036 --RfYyzHpjk4/2,-RfYyzHpjk4,2,24,do.,5.322500228881836,5.382500171661377,True,6.078794152070133e-12,4.0,5.321774080990339,5.382084433603389,5.322500000000001,5.322500000000001,5.3825,5.3825,0.0,0.0 --UUCSKoHeMA/0,-UUCSKoHeMA,0,0,I,1.2625000476837158,1.2825000286102295,True,2.3367625542891624e-11,4.0,1.2625116119279252,1.282511611927958,1.2625,1.2625,1.2825,1.2825,0.0,0.0 --UUCSKoHeMA/0,-UUCSKoHeMA,0,1,mentioned,1.3424999713897705,1.9824999570846558,True,4.0802847212084714e-12,4.0,1.3425128709237222,1.9809538948415186,1.3425,1.3425,1.9025,2.0025,0.0,0.09999999999999987 --UUCSKoHeMA/0,-UUCSKoHeMA,0,2,a,2.0625,2.0824999809265137,True,1.506490071578881e-11,4.0,2.0622694400311663,2.082269440031173,2.0625,2.0625,2.0825,2.0825,0.0,0.0 --UUCSKoHeMA/0,-UUCSKoHeMA,0,3,word,2.122499942779541,2.442500114440918,True,2.1203724269013707e-13,0.25,2.122499953395551,2.4426974718634,2.1225,2.1225,2.4425,2.4425,0.0,0.0 --UUCSKoHeMA/0,-UUCSKoHeMA,0,4,in,2.5225000381469727,2.702500104904175,True,7.434052830788962e-13,0.8034750819206238,2.584625951615478,2.729305029738961,2.5225,2.6825,2.7025,2.8225,0.16000000000000014,0.11999999999999966 --UUCSKoHeMA/0,-UUCSKoHeMA,0,5,the,2.802500009536743,2.9024999141693115,True,3.7196781028578374e-13,0.40202412009239197,2.8131936626394123,2.9242575602781646,2.8025,2.9225,2.9025,3.1425,0.11999999999999966,0.2400000000000002 --UUCSKoHeMA/0,-UUCSKoHeMA,0,6,last,2.922499895095825,3.202500104904175,True,1.1070697310266997e-12,1.1965248584747314,2.9627315540783767,3.240944821647639,2.9225,3.3625,3.2025,3.6225,0.43999999999999995,0.41999999999999993 --UUCSKoHeMA/0,-UUCSKoHeMA,0,7,clip,3.362499952316284,3.622499942779541,True,4.579349486416584e-12,4.0,3.3990179872718147,3.655597836538976,3.3625,3.7625,3.6225,3.9825,0.40000000000000036,0.3599999999999999 --UUCSKoHeMA/0,-UUCSKoHeMA,0,8,called,3.682499885559082,4.042500019073486,True,3.3319351509623896e-13,0.36011672019958496,3.721438804024425,4.085925612332038,3.6825,4.1025,4.0425,4.522500000000001,0.41999999999999993,0.4800000000000004 --UUCSKoHeMA/0,-UUCSKoHeMA,0,9,"'monotone',",4.102499961853027,4.962500095367432,True,2.0431005498533494e-10,4.0,4.159192072906399,5.018715781241488,4.1025,4.562500000000001,4.9625,5.5025,0.46000000000000085,0.54 --UUCSKoHeMA/0,-UUCSKoHeMA,0,10,and,5.042500019073486,5.542500019073486,True,1.1826091050447934e-13,0.25,5.092525670092953,5.5518883043060585,5.0425,5.5825000000000005,5.522500000000001,5.702500000000001,0.54,0.17999999999999972 --UUCSKoHeMA/0,-UUCSKoHeMA,0,11,I,5.582499980926514,5.602499961853027,True,7.732506995816735e-11,4.0,5.606475013180348,5.626475013180339,5.5825000000000005,5.8425,5.602500000000001,5.862500000000001,0.2599999999999998,0.2599999999999998 --UUCSKoHeMA/0,-UUCSKoHeMA,0,12,want,5.622499942779541,5.862500190734863,True,5.911523983000155e-13,0.6389195919036865,5.658054633318278,5.887746639201687,5.6225000000000005,5.8825,5.862500000000001,6.102500000000001,0.2599999999999998,0.2400000000000002 --UUCSKoHeMA/0,-UUCSKoHeMA,0,13,to,6.022500038146973,6.102499961853027,True,3.9711322338126243e-13,0.4292013645172119,6.043176971260156,6.1243497078647895,6.022500000000001,6.2625,6.102500000000001,6.3425,0.23999999999999932,0.23999999999999932 --UUCSKoHeMA/0,-UUCSKoHeMA,0,14,talk,6.202499866485596,6.422500133514404,True,3.8754988259358247e-13,0.41886529326438904,6.231623776195076,6.445624482990393,6.202500000000001,6.522500000000001,6.4225,6.6825,0.3200000000000003,0.2599999999999998 --UUCSKoHeMA/0,-UUCSKoHeMA,0,15,about,6.462500095367432,6.682499885559082,True,1.5894668122917038e-13,0.25,6.486890400692468,6.713296690480922,6.442500000000001,6.742500000000001,6.6825,6.982500000000001,0.2999999999999998,0.3000000000000007 --UUCSKoHeMA/0,-UUCSKoHeMA,0,16,that,6.922500133514404,7.182499885559082,True,2.632421711168398e-11,4.0,6.914653107260793,7.186191805860277,6.8825,7.0425,7.1825,7.2225,0.16000000000000014,0.040000000000000036 --UUCSKoHeMA/0,-UUCSKoHeMA,0,17,briefly.,7.28249979019165,7.682499885559082,True,2.8430669277157428e-12,3.0727968215942383,7.266711655048036,7.682512766971292,7.2225,7.282500000000001,7.6825,7.6825,0.0600000000000005,0.0 --ri04Z7vwnc/0,-ri04Z7vwnc,0,0,going,0.0024999999441206455,0.18250000476837158,True,5.097316457813861e-10,1.124098539352417,0.024398001194100988,0.2924496876375644,0.0025000000000000005,0.0825,0.2025,0.4225,0.08,0.21999999999999997 --ri04Z7vwnc/0,-ri04Z7vwnc,0,1,to,0.20250000059604645,0.26249998807907104,True,4.4608275406865516e-10,0.983735203742981,0.3627568244570231,0.44950644808341267,0.2425,0.5025,0.3225,0.6024999999999999,0.25999999999999995,0.2799999999999999 --ri04Z7vwnc/0,-ri04Z7vwnc,0,2,get,0.32249999046325684,0.48249998688697815,True,4.529311370404798e-10,0.9988377690315247,0.5278888053411263,0.7010825325354665,0.3625,0.7025,0.5025,0.9824999999999999,0.34,0.48 --ri04Z7vwnc/0,-ri04Z7vwnc,0,3,married,0.6625000238418579,1.402500033378601,True,4.135821685125052e-10,0.9120624661445618,0.8307791916512809,1.3855115536618379,0.5625,1.1824999999999999,1.0425,1.5825,0.6199999999999999,0.54 --ri04Z7vwnc/0,-ri04Z7vwnc,0,4,or,1.4225000143051147,1.5225000381469727,True,4.414137388941697e-10,0.9734387397766113,1.4655582811151127,1.5522323688932067,1.2025,1.6824999999999999,1.3025,1.7625,0.48,0.45999999999999996 --ri04Z7vwnc/0,-ri04Z7vwnc,0,5,are,1.6825000047683716,1.8025000095367432,True,6.311645650569631e-10,1.3918914794921875,1.633247732983863,1.7776768200035915,1.3825,1.8225,1.5425,1.9625,0.43999999999999995,0.41999999999999993 --ri04Z7vwnc/0,-ri04Z7vwnc,0,6,already,1.8224999904632568,2.0824999809265137,True,4.5398515502448333e-10,1.0011621713638306,1.84121973750598,2.23857055338298,1.6425,2.0025,2.0425,2.3825,0.3599999999999999,0.33999999999999986 --ri04Z7vwnc/0,-ri04Z7vwnc,0,7,married,2.182499885559082,2.7225000858306885,True,4.677451204138094e-10,1.0315066576004028,2.3092338374060906,2.7215355637832084,2.1425,2.4425,2.6625,2.7425,0.2999999999999998,0.08000000000000007 --ri04Z7vwnc/2,-ri04Z7vwnc,2,0,most,0.042500000447034836,0.2824999988079071,True,3.2669008557389967e-12,0.9973236918449402,0.03533530632279461,0.2915191734222421,0.0025000000000000005,0.0825,0.1625,0.3425,0.08,0.18000000000000002 --ri04Z7vwnc/2,-ri04Z7vwnc,2,1,people,0.3824999928474426,0.8424999713897705,True,3.1715836554258026e-12,0.9682251214981079,0.37951785526938786,0.8040705105858642,0.3425,0.4225,0.6224999999999999,0.8825,0.07999999999999996,0.26 --ri04Z7vwnc/2,-ri04Z7vwnc,2,2,think,0.8824999928474426,1.3025000095367432,True,1.2376642679473582e-12,0.377835750579834,0.880992595479909,1.2249863793838607,0.6825,0.9225,0.8825,1.3425,0.24,0.4600000000000001 --ri04Z7vwnc/2,-ri04Z7vwnc,2,3,it'll,1.402500033378601,1.7825000286102295,True,2.4132093545681244e-10,4.0,1.3095751724347637,1.530903636824568,0.9225,1.4025,1.3025,1.7825,0.4800000000000001,0.48 --ri04Z7vwnc/2,-ri04Z7vwnc,2,4,sort,1.8624999523162842,2.302500009536743,True,4.662647004605169e-12,1.4234188795089722,1.606748818471774,1.8158763538890752,1.3825,1.8625,1.6824999999999999,2.0825,0.48,0.40000000000000013 --ri04Z7vwnc/2,-ri04Z7vwnc,2,5,itself,2.322499990463257,2.5425000190734863,True,2.164716756541951e-12,0.660847544670105,1.8871830849169948,2.3170325866349173,1.8425,2.1625,2.1625,2.4625,0.32000000000000006,0.2999999999999998 --ri04Z7vwnc/2,-ri04Z7vwnc,2,6,"out,",2.5625,2.702500104904175,True,1.7914156486345534e-12,0.5468856692314148,2.372672664661856,2.4993875621536525,2.2225,2.4825,2.3625,2.6025,0.2599999999999998,0.2400000000000002 --ri04Z7vwnc/2,-ri04Z7vwnc,2,7,"""we'll",2.7225000858306885,2.862499952316284,True,7.49354953089032e-11,4.0,2.5485761578230206,2.735453096562189,2.4025,2.6225,2.5825,2.8025,0.2200000000000002,0.2200000000000002 --ri04Z7vwnc/2,-ri04Z7vwnc,2,8,discuss,2.882499933242798,3.1424999237060547,True,1.244877790261556e-12,0.38003790378570557,2.769634619145668,3.0783780752313397,2.6025,2.8425,2.9625,3.1425,0.23999999999999977,0.18000000000000016 --ri04Z7vwnc/2,-ri04Z7vwnc,2,9,it,3.1624999046325684,3.2225000858306885,True,3.2844339227511288e-12,1.002676248550415,3.1168374269808057,3.182508050326935,3.0225,3.1625,3.1025,3.2425,0.14000000000000012,0.14000000000000012 --ri04Z7vwnc/2,-ri04Z7vwnc,2,10,"later,""",3.242500066757202,3.422499895095825,True,6.055528040810332e-12,1.8486393690109253,3.213576245227149,3.4151321092630402,3.1425,3.2825,3.3425,3.5025,0.14000000000000012,0.16000000000000014 --ri04Z7vwnc/2,-ri04Z7vwnc,2,11,it's,3.442500114440918,3.5425000190734863,True,1.0349616302862685e-10,4.0,3.451680714649028,3.576908987243269,3.3625,3.5425,3.4825,3.7225,0.18000000000000016,0.2400000000000002 --ri04Z7vwnc/2,-ri04Z7vwnc,2,12,not,3.5625,3.702500104904175,True,1.5995723625858438e-12,0.4883195161819458,3.6143920521257327,3.7361958558643753,3.5225,3.7825,3.6425,3.9025,0.26000000000000023,0.2599999999999998 --ri04Z7vwnc/2,-ri04Z7vwnc,2,13,something,3.742500066757202,4.422500133514404,True,2.2604188486263777e-12,0.6900635957717896,3.777755699176747,4.436873888478261,3.7025,3.9625,4.402500000000001,4.4625,0.2599999999999998,0.05999999999999961 --ri04Z7vwnc/2,-ri04Z7vwnc,2,14,too,4.84250020980835,5.022500038146973,True,2.015573125069281e-10,4.0,4.78410811013368,4.995321876065659,4.482500000000001,4.8425,4.942500000000001,5.022500000000001,0.35999999999999943,0.08000000000000007 --ri04Z7vwnc/2,-ri04Z7vwnc,2,15,important,5.042500019073486,5.542500019073486,True,5.276962460748491e-12,1.6109578609466553,5.042487498132745,5.543272605933794,5.0425,5.0425,5.5425,5.5425,0.0,0.0 --ri04Z7vwnc/5,-ri04Z7vwnc,5,0,"""",nan,nan,False,0.0,nan,nan,nan,nan,nan,nan,nan,nan,nan --ri04Z7vwnc/5,-ri04Z7vwnc,5,1,So,0.02250000089406967,0.08250000327825546,True,5.531704955208383e-11,4.0,0.06342992056271926,0.14143729395540497,0.0225,0.2225,0.0825,0.28250000000000003,0.2,0.2 --ri04Z7vwnc/5,-ri04Z7vwnc,5,2,I,0.2224999964237213,0.24250000715255737,True,1.6104359599339313e-12,0.4176913797855377,0.303244394241129,0.3232443942411471,0.2225,0.5225,0.2425,0.5425,0.29999999999999993,0.3 --ri04Z7vwnc/5,-ri04Z7vwnc,5,3,think,0.5224999785423279,0.8025000095367432,True,8.501941013185077e-13,0.25,0.5468122658585075,0.7930804306754985,0.5225,0.6425,0.7424999999999999,0.8424999999999999,0.12,0.09999999999999998 --ri04Z7vwnc/5,-ri04Z7vwnc,5,4,it's,0.8824999928474426,1.0824999809265137,True,3.3593516857166605e-11,4.0,0.8827280561963028,1.0827702576220137,0.8825,0.8825,1.0825,1.0825,0.0,0.0 --ri04Z7vwnc/5,-ri04Z7vwnc,5,5,important,1.162500023841858,1.662500023841858,True,6.419234935273188e-12,1.6649274826049805,1.1539397855459228,1.6509180681704647,1.1225,1.2225,1.5425,1.7225,0.09999999999999987,0.17999999999999994 --ri04Z7vwnc/5,-ri04Z7vwnc,5,6,to,2.322499990463257,2.4625000953674316,True,3.383222955261056e-12,0.8774909973144531,2.098755755525236,2.258181340358846,1.6625,2.3225,1.7225,2.4625,0.6599999999999997,0.74 --ri04Z7vwnc/5,-ri04Z7vwnc,5,7,discuss,2.5225000381469727,2.862499952316284,True,2.7650663876610526e-12,0.717162549495697,2.4394224473580834,2.792790803676593,2.3025,2.5225,2.6625,2.8625,0.21999999999999975,0.19999999999999973 --ri04Z7vwnc/5,-ri04Z7vwnc,5,8,finances,2.9024999141693115,3.322499990463257,True,4.327905221701567e-12,1.1225088834762573,2.866859719198108,3.2956421389284056,2.8025,2.9025,3.2225,3.4225,0.09999999999999964,0.19999999999999973 --s9qJ7ATP7w/1,-s9qJ7ATP7w,1,0,But,0.5625,0.7024999856948853,True,2.1161275043455469e-13,1.0,0.5496646247778796,0.702164602009161,0.5425,0.5625,0.7025,0.7025,0.020000000000000018,0.0 --s9qJ7ATP7w/1,-s9qJ7ATP7w,1,1,the,0.8424999713897705,1.402500033378601,True,6.26251817330975e-13,2.959423780441284,0.8420559143387191,1.406478256178167,0.8225,0.9225,1.4025,1.4224999999999999,0.09999999999999998,0.019999999999999796 --s9qJ7ATP7w/1,-s9qJ7ATP7w,1,2,hardest,1.4824999570846558,1.8424999713897705,True,1.8739304270647128e-13,0.8855470418930054,1.4825189926134468,1.8518094365299989,1.4825,1.4825,1.8425,1.8825,0.0,0.040000000000000036 --s9qJ7ATP7w/1,-s9qJ7ATP7w,1,3,thing,2.0225000381469727,2.262500047683716,True,8.017903425612885e-14,0.378895103931427,2.020780201902659,2.2611176783830214,2.0225,2.0225,2.2625,2.2625,0.0,0.0 --s9qJ7ATP7w/1,-s9qJ7ATP7w,1,4,in,2.322499990463257,2.422499895095825,True,6.493226502269842e-14,0.3068447709083557,2.320865793192878,2.422328440790031,2.3225,2.3225,2.4225,2.4825,0.0,0.06000000000000005 --s9qJ7ATP7w/1,-s9qJ7ATP7w,1,5,life,2.6024999618530273,3.202500104904175,True,2.1193372848771902e-13,1.0015168190002441,2.600471167683731,3.1896348019912866,2.6025,2.6025,3.2025,3.2025,0.0,0.0 --s9qJ7ATP7w/1,-s9qJ7ATP7w,1,6,to,3.262500047683716,3.3424999713897705,True,6.471526873413902e-14,0.3058193325996399,3.2608217425607964,3.3421634910399116,3.2625,3.2625,3.3425,3.3425,0.0,0.0 --s9qJ7ATP7w/1,-s9qJ7ATP7w,1,7,"learn,",3.4024999141693115,3.6624999046325684,True,3.52563437428996e-13,1.6660784482955933,3.4027175839840345,3.66329101504063,3.4025,3.4025,3.6625,3.6625,0.0,0.0 --s9qJ7ATP7w/1,-s9qJ7ATP7w,1,8,is,3.802500009536743,3.882499933242798,True,1.9704459689341008e-13,0.9311565160751343,3.80444740581124,3.884674702639147,3.8025,3.8025,3.8825,3.8825,0.0,0.0 --s9qJ7ATP7w/1,-s9qJ7ATP7w,1,9,to,3.9825000762939453,4.042500019073486,True,4.005100016826052e-13,1.892655372619629,3.973553794154936,4.04829152917298,3.9425,4.0025,4.0025,4.1225000000000005,0.0600000000000005,0.1200000000000001 --s9qJ7ATP7w/1,-s9qJ7ATP7w,1,10,lose,4.222499847412109,4.502500057220459,True,8.517983193789824e-12,4.0,4.222786002066446,4.50249136136073,4.2225,4.2225,4.5025,4.5025,0.0,0.0 --s9qJ7ATP7w/0,-s9qJ7ATP7w,0,0,they,0.042500000447034836,0.24250000715255737,True,1.2452759092992927e-12,1.144152045249939,0.035296410608304025,0.24507960324400196,0.0225,0.0625,0.2225,0.3025,0.04,0.07999999999999999 --s9qJ7ATP7w/0,-s9qJ7ATP7w,0,1,have,0.2824999988079071,0.5425000190734863,True,9.242065663120358e-13,0.8491554260253906,0.30454331855208594,0.5638608046103386,0.28250000000000003,0.3425,0.5425,0.6024999999999999,0.06,0.05999999999999994 --s9qJ7ATP7w/0,-s9qJ7ATP7w,0,2,"doubt,",0.7024999856948853,0.9225000143051147,True,2.921006535608339e-13,0.2683803141117096,0.7016751768490946,0.9389234569792527,0.7025,0.7025,0.9225,0.9824999999999999,0.0,0.05999999999999994 --s9qJ7ATP7w/0,-s9qJ7ATP7w,0,3,they,1.0824999809265137,1.3025000095367432,True,2.414696914643244e-12,2.218608856201172,1.0824749234219044,1.3025575291805016,1.0825,1.0825,1.3025,1.3025,0.0,0.0 --s9qJ7ATP7w/0,-s9qJ7ATP7w,0,4,have,1.402500033378601,1.8424999713897705,True,1.4843991921059674e-12,1.3638570308685303,1.480454771743787,1.8441928116392656,1.4025,1.5825,1.8425,1.8625,0.17999999999999994,0.020000000000000018 --s9qJ7ATP7w/0,-s9qJ7ATP7w,0,5,"fear,",1.8624999523162842,2.0824999809265137,True,6.6919907115714494e-12,4.0,1.8672921296696843,2.08198887608499,1.8625,1.9025,2.0825,2.0825,0.040000000000000036,0.0 --s9qJ7ATP7w/0,-s9qJ7ATP7w,0,6,they,2.122499942779541,2.2825000286102295,True,7.773068213395851e-13,0.7141848206520081,2.1272049813809994,2.285785138186709,2.1225,2.1625,2.2625,2.3225,0.040000000000000036,0.05999999999999961 --s9qJ7ATP7w/0,-s9qJ7ATP7w,0,7,lose,2.302500009536743,2.4825000762939453,True,2.6457091725773374e-12,2.430861711502075,2.3155930936973776,2.470759112376862,2.3025,2.3425,2.4425,2.5025,0.03999999999999959,0.06000000000000005 --s9qJ7ATP7w/0,-s9qJ7ATP7w,0,8,in,2.502500057220459,2.5824999809265137,True,1.923453930852137e-11,4.0,2.5130796331063547,2.582583582398577,2.4825,2.5225,2.5825,2.5825,0.040000000000000036,0.0 --s9qJ7ATP7w/0,-s9qJ7ATP7w,0,9,a,2.622499942779541,2.6424999237060547,True,2.0894479722810555e-12,1.9197721481323242,2.622205727070115,2.6422057270701145,2.6225,2.6225,2.6425,2.6425,0.0,0.0 --s9qJ7ATP7w/0,-s9qJ7ATP7w,0,10,Ferrari,2.6624999046325684,3.0824999809265137,True,4.712646288831945e-13,0.43299511075019836,2.680606250238554,3.083650895889502,2.6625,2.7025,3.0825,3.0825,0.040000000000000036,0.0 --s9qJ7ATP7w/0,-s9qJ7ATP7w,0,11,"race,",3.1024999618530273,3.242500066757202,True,9.314907786078797e-13,0.8558481335639954,3.103672235105714,3.2438796035307136,3.1025,3.1025,3.2425,3.2425,0.0,0.0 --s9qJ7ATP7w/0,-s9qJ7ATP7w,0,12,or,3.262500047683716,3.3424999713897705,True,4.8605338504037476e-11,4.0,3.264086176296221,3.344207480546319,3.2625,3.2625,3.3425,3.3425,0.0,0.0 --s9qJ7ATP7w/0,-s9qJ7ATP7w,0,13,they,3.422499895095825,3.682499885559082,True,2.5745997347947913e-11,4.0,3.414911960971616,3.675032305819791,3.3625,3.4225,3.6425,3.6825,0.06000000000000005,0.040000000000000036 --s9qJ7ATP7w/0,-s9qJ7ATP7w,0,14,lose,3.7825000286102295,3.942500114440918,True,7.575693002602468e-13,0.6960501074790955,3.7616974887882315,3.920602352332232,3.7225,3.7825,3.8825,3.9425,0.06000000000000005,0.06000000000000005 --s9qJ7ATP7w/0,-s9qJ7ATP7w,0,15,in,4.102499961853027,4.162499904632568,True,3.397961165912955e-12,3.122026205062866,4.0719655131892,4.156779322130816,3.9225,4.1025,4.1225000000000005,4.1825,0.18000000000000016,0.05999999999999961 --s9qJ7ATP7w/0,-s9qJ7ATP7w,0,16,a,4.202499866485596,4.222499847412109,True,5.129190258287841e-13,0.47126689553260803,4.214525556613766,4.23452555661377,4.202500000000001,4.2225,4.2225,4.242500000000001,0.019999999999999574,0.020000000000000462 --s9qJ7ATP7w/0,-s9qJ7ATP7w,0,17,"race,",4.522500038146973,4.78249979019165,True,8.075219095834973e-13,0.741946280002594,4.523863360616268,4.783031253821107,4.522500000000001,4.522500000000001,4.782500000000001,4.782500000000001,0.0,0.0 --s9qJ7ATP7w/0,-s9qJ7ATP7w,0,18,and,5.182499885559082,5.322500228881836,True,2.4335565572235207e-13,0.25,5.142079904620651,5.314934950906367,4.8025,5.1825,5.242500000000001,5.3425,0.3799999999999999,0.09999999999999964 --s9qJ7ATP7w/0,-s9qJ7ATP7w,0,19,then,5.422500133514404,5.5625,True,1.1495937936398942e-13,0.25,5.406993962189282,5.55731323856257,5.3025,5.4225,5.522500000000001,5.562500000000001,0.1200000000000001,0.040000000000000036 --s9qJ7ATP7w/0,-s9qJ7ATP7w,0,20,they,5.582499980926514,5.762499809265137,True,1.4886081950438168e-11,4.0,5.582500046565337,5.7607591757751635,5.5825000000000005,5.5825000000000005,5.742500000000001,5.7625,0.0,0.019999999999999574 --s9qJ7ATP7w/0,-s9qJ7ATP7w,0,21,just,5.78249979019165,5.922500133514404,True,1.4744784169670733e-12,1.3547419309616089,5.782499967123763,5.922500201867736,5.782500000000001,5.782500000000001,5.9225,5.9225,0.0,0.0 --s9qJ7ATP7w/0,-s9qJ7ATP7w,0,22,give,5.962500095367432,6.162499904632568,True,2.479647346828595e-13,0.25,5.962426812392603,6.162335078542887,5.9625,5.9625,6.1625000000000005,6.1625000000000005,0.0,0.0 --s9qJ7ATP7w/0,-s9qJ7ATP7w,0,23,up,6.642499923706055,6.702499866485596,True,5.418672780442557e-13,0.49786439538002014,6.61413642460844,6.68734623928928,6.5825000000000005,6.642500000000001,6.6625000000000005,6.702500000000001,0.0600000000000005,0.040000000000000036 --s9qJ7ATP7w/5,-s9qJ7ATP7w,5,0,I,0.0024999999441206455,0.02250000089406967,True,8.043445250127679e-12,4.0,0.0032990285590143776,0.023299028559016173,0.0025000000000000005,0.0025000000000000005,0.0225,0.0225,0.0,0.0 --s9qJ7ATP7w/5,-s9qJ7ATP7w,5,1,have,0.08250000327825546,0.42250001430511475,True,3.238681241593544e-12,4.0,0.06717380191828314,0.32357469353523305,0.0425,0.1225,0.1825,0.4225,0.07999999999999999,0.24 --s9qJ7ATP7w/5,-s9qJ7ATP7w,5,2,been,0.5224999785423279,0.7425000071525574,True,1.3483621771198662e-12,2.748244285583496,0.3951901849667031,0.6275678443671301,0.2225,0.5225,0.4225,0.7424999999999999,0.29999999999999993,0.31999999999999995 --s9qJ7ATP7w/5,-s9qJ7ATP7w,5,3,beat,0.7825000286102295,1.3424999713897705,True,1.4721684700284843e-13,0.3000587522983551,0.6899705310710409,1.079888780943723,0.5225,1.1225,0.7424999999999999,1.3425,0.6000000000000001,0.6000000000000001 --s9qJ7ATP7w/5,-s9qJ7ATP7w,5,4,up,1.3624999523162842,1.4225000143051147,True,6.7126171158019e-13,1.3681719303131104,1.1659770402041265,1.3613713122992432,0.7825,1.3625,1.2425,1.4224999999999999,0.5800000000000001,0.17999999999999994 --s9qJ7ATP7w/5,-s9qJ7ATP7w,5,5,and,1.462499976158142,1.6024999618530273,True,2.956292166362423e-13,0.602554202079773,1.4205737927255522,1.5482913645398126,1.3225,1.4625,1.4224999999999999,1.6025,0.1399999999999999,0.18000000000000016 --s9qJ7ATP7w/5,-s9qJ7ATP7w,5,6,put,1.7424999475479126,1.9424999952316284,True,5.560912516057448e-13,1.1334303617477417,1.6589005375801091,1.842611262769312,1.4625,1.7425,1.6025,2.0025,0.28,0.3999999999999999 --s9qJ7ATP7w/5,-s9qJ7ATP7w,5,7,down,2.0425000190734863,2.442500114440918,True,8.62298581605532e-14,0.25,1.9559455563234505,2.310078948483982,1.7425,2.0425,2.0025,2.4425,0.30000000000000004,0.43999999999999995 --s9qJ7ATP7w/5,-s9qJ7ATP7w,5,8,and,2.5824999809265137,2.702500104904175,True,1.233855411505308e-13,0.25148555636405945,2.5125746937182574,2.693039630571944,2.3225,2.6025,2.6025,2.7025,0.28000000000000025,0.10000000000000009 --s9qJ7ATP7w/5,-s9qJ7ATP7w,5,9,everything,2.8424999713897705,3.9825000762939453,True,5.351290564099484e-14,0.25,2.8684364082492393,4.011810221786433,2.8425,2.8425,3.9825,3.9825,0.0,0.0 --s9qJ7ATP7w/5,-s9qJ7ATP7w,5,10,that,4.902500152587891,5.122499942779541,True,5.439115737665423e-12,4.0,4.89797082813463,5.13239484504563,4.902500000000001,4.9625,5.102500000000001,5.1625000000000005,0.05999999999999961,0.05999999999999961 --s9qJ7ATP7w/5,-s9qJ7ATP7w,5,11,can,5.162499904632568,5.34250020980835,True,4.8560754619926885e-14,0.25,5.188221176465659,5.361559915166783,5.1625000000000005,5.3825,5.2625,5.5025,0.21999999999999975,0.2400000000000002 --s9qJ7ATP7w/5,-s9qJ7ATP7w,5,12,go,5.422500133514404,5.502500057220459,True,1.665226523296301e-13,0.3394080102443695,5.454580933666803,5.539748928566693,5.4225,5.602500000000001,5.5025,5.702500000000001,0.1800000000000006,0.20000000000000018 --s9qJ7ATP7w/5,-s9qJ7ATP7w,5,13,"wrong,",5.602499961853027,6.202499866485596,True,4.906267449603097e-13,1.0,5.65194480101253,6.236338881255996,5.602500000000001,6.1225000000000005,6.142500000000001,6.8025,0.5199999999999996,0.6599999999999993 --s9qJ7ATP7w/5,-s9qJ7ATP7w,5,14,has,6.702499866485596,6.802499771118164,True,7.809464338225103e-13,1.5917322635650635,6.7180709524906215,6.819550494578619,6.702500000000001,6.942500000000001,6.8025,7.062500000000001,0.2400000000000002,0.2600000000000007 --s9qJ7ATP7w/5,-s9qJ7ATP7w,5,15,gone,6.862500190734863,7.0625,True,6.044744240742139e-14,0.25,6.884818614020353,7.0893755044610485,6.862500000000001,7.142500000000001,7.062500000000001,7.4225,0.28000000000000025,0.35999999999999943 --s9qJ7ATP7w/5,-s9qJ7ATP7w,5,16,wrong,7.28249979019165,7.582499980926514,True,6.222165794753098e-13,1.2682076692581177,7.27870407791671,7.598153728057217,7.142500000000001,7.482500000000001,7.5825000000000005,7.8025,0.33999999999999986,0.21999999999999975 --s9qJ7ATP7w/5,-s9qJ7ATP7w,5,17,for,7.662499904632568,7.802499771118164,True,2.2805403941152103e-13,0.46482187509536743,7.688982736794739,7.83358602588385,7.6625000000000005,8.022499999999999,7.8025,8.202499999999999,0.35999999999999854,0.3999999999999986 --s9qJ7ATP7w/5,-s9qJ7ATP7w,5,18,me,8.142499923706055,8.262499809265137,True,6.399445209859245e-12,4.0,8.149809329284016,8.26073298564643,8.1425,8.2425,8.2425,8.362499999999999,0.09999999999999964,0.11999999999999922 --s9qJ7ATP7w/4,-s9qJ7ATP7w,4,0,I,0.02250000089406967,0.042500000447034836,True,2.5145097115597537e-10,4.0,0.022581619903897353,0.04258161990389827,0.0225,0.0225,0.0425,0.0425,0.0,0.0 --s9qJ7ATP7w/4,-s9qJ7ATP7w,4,1,have,0.10249999910593033,0.32249999046325684,True,5.2369983349898064e-11,4.0,0.10275901230479557,0.3234319644678103,0.10250000000000001,0.10250000000000001,0.3225,0.3225,0.0,0.0 --s9qJ7ATP7w/4,-s9qJ7ATP7w,4,2,lost,0.4025000035762787,0.8025000095367432,True,4.580078720797798e-13,1.0,0.5590338658826747,0.8117400282480208,0.4025,0.6224999999999999,0.7825,0.8624999999999999,0.21999999999999992,0.07999999999999996 --s9qJ7ATP7w/4,-s9qJ7ATP7w,4,3,at,0.9024999737739563,1.0425000190734863,True,8.964015510773415e-13,1.9571750164031982,0.937330588114691,1.0553245531559798,0.9025,1.0225,1.0425,1.0825,0.12,0.040000000000000036 --s9qJ7ATP7w/4,-s9qJ7ATP7w,4,4,everything,1.3224999904632568,2.0824999809265137,True,2.723942219787917e-13,0.5947369933128357,1.323579559459154,2.0836404722492556,1.3225,1.3425,2.0825,2.0825,0.020000000000000018,0.0 --s9qJ7ATP7w/4,-s9qJ7ATP7w,4,5,you,2.182499885559082,2.362499952316284,True,1.1392326155785365e-13,0.25,2.166667845312565,2.364468039998308,2.1425,2.1825,2.3625,2.3625,0.040000000000000036,0.0 --s9qJ7ATP7w/4,-s9qJ7ATP7w,4,6,can,2.5225000381469727,2.702500104904175,True,1.9086615222888882e-14,0.25,2.5339093670209367,2.762821360795334,2.4825,2.6225,2.7025,2.8025,0.14000000000000012,0.10000000000000009 --s9qJ7ATP7w/4,-s9qJ7ATP7w,4,7,"imagine,",3.002500057220459,3.382499933242798,True,3.490432942676591e-11,4.0,2.9764326793531897,3.3827679885419752,2.8825,3.0025,3.3825,3.3825,0.1200000000000001,0.0 --s9qJ7ATP7w/4,-s9qJ7ATP7w,4,8,seriously,3.442500114440918,4.022500038146973,True,2.7026327681888007e-13,0.5900843739509583,3.4400904252806708,4.025070808901028,3.4225,3.4425,4.022500000000001,4.022500000000001,0.020000000000000018,0.0 --s9qJ7ATP7w/7,-s9qJ7ATP7w,7,0,I,0.02250000089406967,0.042500000447034836,True,6.969980148596733e-11,4.0,0.02678660345931201,0.04678660345934946,0.0225,0.10250000000000001,0.0425,0.1225,0.08000000000000002,0.07999999999999999 --s9qJ7ATP7w/7,-s9qJ7ATP7w,7,1,used,0.3824999928474426,0.5425000190734863,True,3.881826110552211e-11,4.0,0.35018109647684703,0.5409254689733906,0.10250000000000001,0.3825,0.5425,0.5425,0.28,0.0 --s9qJ7ATP7w/7,-s9qJ7ATP7w,7,2,to,0.5625,0.6225000023841858,True,5.419344834001194e-11,4.0,0.5617484066259408,0.6218305196632183,0.5625,0.5625,0.6224999999999999,0.6224999999999999,0.0,0.0 --s9qJ7ATP7w/7,-s9qJ7ATP7w,7,3,work,0.6424999833106995,0.7825000286102295,True,1.2994504560923104e-13,0.25,0.6439510150136057,0.7956763526640003,0.6425,0.6425,0.7825,0.8225,0.0,0.040000000000000036 --s9qJ7ATP7w/7,-s9qJ7ATP7w,7,4,for,0.862500011920929,0.9825000166893005,True,5.919409927501729e-13,0.25,0.8703185545526655,0.9934280704856465,0.8624999999999999,0.9025,0.9824999999999999,1.0425,0.040000000000000036,0.06000000000000005 --s9qJ7ATP7w/7,-s9qJ7ATP7w,7,5,Warren,1.0425000190734863,1.3624999523162842,True,2.076905487868874e-12,0.55162113904953,1.0499859516799703,1.362546218062043,1.0425,1.0825,1.3625,1.3625,0.040000000000000036,0.0 --s9qJ7ATP7w/7,-s9qJ7ATP7w,7,6,"Avis,",1.4424999952316284,1.6825000047683716,True,5.145964557251581e-11,4.0,1.441602626222574,1.6811464831337093,1.4425,1.4425,1.6824999999999999,1.6824999999999999,0.0,0.0 --s9qJ7ATP7w/7,-s9qJ7ATP7w,7,7,the,1.7024999856948853,1.9824999570846558,True,7.724032351219545e-12,2.0514845848083496,1.7012855259737578,1.9803489043794023,1.7025,1.7025,1.9825,1.9825,0.0,0.0 --s9qJ7ATP7w/7,-s9qJ7ATP7w,7,8,guy,2.0225000381469727,2.1424999237060547,True,1.3621283788400884e-11,3.6177804470062256,2.0202241581787876,2.141641797729933,2.0225,2.0225,2.1425,2.1425,0.0,0.0 --s9qJ7ATP7w/7,-s9qJ7ATP7w,7,9,who,2.1624999046325684,2.262500047683716,True,1.5639521622201613e-10,4.0,2.1618504322195777,2.2658099313974582,2.1625,2.1625,2.2625,2.2825,0.0,0.020000000000000018 --s9qJ7ATP7w/7,-s9qJ7ATP7w,7,10,started,2.302500009536743,2.5625,True,3.76403162111183e-12,0.9997177720069885,2.301007069455703,2.562164512343847,2.3025,2.3025,2.5625,2.5625,0.0,0.0 --s9qJ7ATP7w/7,-s9qJ7ATP7w,7,11,Avis,2.6024999618530273,2.7825000286102295,True,1.6464942256821935e-11,4.0,2.6021628830951244,2.7711338037144446,2.6025,2.6025,2.7425,2.7825,0.0,0.040000000000000036 --s9qJ7ATP7w/7,-s9qJ7ATP7w,7,12,Rent,2.802500009536743,3.002500057220459,True,3.706247982127042e-12,0.9843705892562866,2.799981994850341,2.994845622631275,2.7825,2.8225,2.9625,3.0025,0.03999999999999959,0.040000000000000036 --s9qJ7ATP7w/7,-s9qJ7ATP7w,7,13,a,3.0225000381469727,3.0425000190734863,True,6.146569798276547e-13,0.25,3.014930168179437,3.034930168179444,2.9825,3.0225,3.0025,3.0425,0.040000000000000036,0.040000000000000036 --s9qJ7ATP7w/7,-s9qJ7ATP7w,7,14,"Car,",3.0625,3.1624999046325684,True,6.6249657669492645e-12,1.7595750093460083,3.062430806341528,3.1624378407080567,3.0625,3.0625,3.1625,3.1625,0.0,0.0 --s9qJ7ATP7w/7,-s9qJ7ATP7w,7,15,and,3.182499885559082,3.302500009536743,True,1.0457030207022822e-12,0.27773621678352356,3.1825015875733373,3.2987676736960596,3.1825,3.1825,3.2825,3.3025,0.0,0.020000000000000018 --s9qJ7ATP7w/7,-s9qJ7ATP7w,7,16,he,3.3424999713897705,3.4024999141693115,True,1.69514088096262e-12,0.4502253532409668,3.3416142026375746,3.402494144256177,3.3425,3.3425,3.4025,3.4025,0.0,0.0 --s9qJ7ATP7w/7,-s9qJ7ATP7w,7,17,said,3.442500114440918,3.622499942779541,True,7.551881754490342e-13,0.25,3.442500007657619,3.6225138017818206,3.4425,3.4425,3.6225,3.6225,0.0,0.0 --s9qJ7ATP7w/7,-s9qJ7ATP7w,7,18,to,3.702500104904175,3.762500047683716,True,1.4711676497793265e-14,0.25,3.6993621761372792,3.7652132808598355,3.6625,3.7425,3.7625,3.8025,0.08000000000000007,0.040000000000000036 --s9qJ7ATP7w/7,-s9qJ7ATP7w,7,19,me,3.882499933242798,3.9625000953674316,True,3.844036200462142e-12,1.0209667682647705,3.882508254724707,3.9624960997761027,3.8825,3.8825,3.9625,3.9625,0.0,0.0 --s9qJ7ATP7w/7,-s9qJ7ATP7w,7,20,one,4.022500038146973,4.182499885559082,True,4.8639130917349505e-12,1.2918436527252197,4.022505987413522,4.182510136166168,4.022500000000001,4.022500000000001,4.1825,4.1825,0.0,0.0 --s9qJ7ATP7w/7,-s9qJ7ATP7w,7,21,"day,",4.922500133514404,5.042500019073486,True,8.347099920980039e-12,2.2169697284698486,4.921261247051621,5.042292247022992,4.9225,4.9225,5.0425,5.0425,0.0,0.0 --s9qJ7ATP7w/7,-s9qJ7ATP7w,7,22,"""Robert,",5.162499904632568,5.442500114440918,True,3.313618097359333e-13,0.25,5.157729190413535,5.437921281142969,5.1225000000000005,5.1625000000000005,5.402500000000001,5.442500000000001,0.040000000000000036,0.040000000000000036 --s9qJ7ATP7w/7,-s9qJ7ATP7w,7,23,"""what's",5.502500057220459,5.802499771118164,True,2.250095726061274e-12,0.5976200699806213,5.493928773068351,5.787613456780464,5.4225,5.5025,5.6625000000000005,5.8025,0.08000000000000007,0.13999999999999968 --s9qJ7ATP7w/7,-s9qJ7ATP7w,7,24,the,5.822500228881836,5.922500133514404,True,2.3816506492663203e-13,0.25,5.8117797173499195,5.916011727614231,5.7225,5.822500000000001,5.862500000000001,5.9225,0.10000000000000053,0.05999999999999961 --s9qJ7ATP7w/7,-s9qJ7ATP7w,7,25,purpose,5.942500114440918,6.28249979019165,True,1.1442309773290749e-11,3.0390501022338867,5.94251287266894,6.286029911061819,5.942500000000001,5.942500000000001,6.282500000000001,6.322500000000001,0.0,0.040000000000000036 --s9qJ7ATP7w/7,-s9qJ7ATP7w,7,26,of,6.362500190734863,6.442500114440918,True,3.76615709105077e-12,1.0002822875976562,6.3626166902528665,6.4423161972541,6.362500000000001,6.362500000000001,6.442500000000001,6.442500000000001,0.0,0.0 --s9qJ7ATP7w/7,-s9qJ7ATP7w,7,27,business,6.462500095367432,6.822500228881836,True,2.3635134648036793e-12,0.6277435421943665,6.462403766646239,6.821232931946638,6.4625,6.4625,6.8025,6.822500000000001,0.0,0.020000000000000462 --s9qJ7ATP7w/6,-s9qJ7ATP7w,6,0,But,0.042500000447034836,0.2224999964237213,True,6.265210247304032e-13,0.2663658559322357,0.04595421401102171,0.19960157519223576,0.0025000000000000005,0.10250000000000001,0.1225,0.28250000000000003,0.1,0.16000000000000003 --s9qJ7ATP7w/6,-s9qJ7ATP7w,6,1,I,0.26249998807907104,0.2824999988079071,True,4.512839754666764e-13,0.25,0.3053911111772659,0.3253911111772663,0.2625,0.6625,0.28250000000000003,0.6825,0.39999999999999997,0.39999999999999997 --s9qJ7ATP7w/6,-s9qJ7ATP7w,6,2,just,0.6625000238418579,1.402500033378601,True,9.192134033109145e-12,3.9080424308776855,0.6529190020049375,1.3804359304662248,0.5625,1.0025,1.2825,1.4025,0.43999999999999995,0.1200000000000001 --s9qJ7ATP7w/6,-s9qJ7ATP7w,6,3,kept,1.4824999570846558,1.6425000429153442,True,2.3521070074278283e-12,1.0,1.4731671348482018,1.634072464256062,1.3425,1.4825,1.5425,1.6425,0.1399999999999999,0.10000000000000009 --s9qJ7ATP7w/6,-s9qJ7ATP7w,6,4,going,1.7024999856948853,2.262500047683716,True,6.741932099402215e-12,2.866337299346924,1.7043089382694716,2.2765034438543106,1.7025,1.7025,2.2625,2.3025,0.0,0.040000000000000036 --s9qJ7ATP7w/8,-s9qJ7ATP7w,8,0,"""",nan,nan,False,0.0,nan,nan,nan,nan,nan,nan,nan,nan,nan --s9qJ7ATP7w/8,-s9qJ7ATP7w,8,1,And,0.12250000238418579,0.24250000715255737,True,5.430787416993432e-11,2.974587917327881,0.13211225042789249,0.25671074886264156,0.1225,0.1625,0.2425,0.3425,0.04000000000000001,0.10000000000000003 --s9qJ7ATP7w/8,-s9qJ7ATP7w,8,2,I,0.32249999046325684,0.3425000011920929,True,2.400587367779039e-11,1.3148661851882935,0.3668057281520321,0.3868057281532408,0.3225,0.5225,0.3425,0.5425,0.19999999999999996,0.19999999999999996 --s9qJ7ATP7w/8,-s9qJ7ATP7w,8,3,"said,",0.5224999785423279,0.7225000262260437,True,2.0516449650287427e-11,1.1237410306930542,0.5449670600283814,0.7418337194054421,0.5225,0.6625,0.6825,0.9025,0.14,0.21999999999999997 --s9qJ7ATP7w/8,-s9qJ7ATP7w,8,4,"""Oh,",0.8224999904632568,0.9024999737739563,True,1.968307895144905e-12,0.25,0.8328528775409426,0.9142629965513558,0.7825,0.9824999999999999,0.9025,1.0425,0.19999999999999996,0.14 --s9qJ7ATP7w/8,-s9qJ7ATP7w,8,5,make,0.9825000166893005,1.2625000476837158,True,1.3614405436346289e-10,4.0,0.9900671560139473,1.2648433600608693,0.9225,1.0825,1.2625,1.2625,0.16000000000000003,0.0 --s9qJ7ATP7w/8,-s9qJ7ATP7w,8,6,a,1.3424999713897705,1.3624999523162842,True,1.5998102148584437e-11,0.8762589693069458,1.342202284908815,1.36220228490884,1.3425,1.3425,1.3625,1.3625,0.0,0.0 --s9qJ7ATP7w/8,-s9qJ7ATP7w,8,7,"profit,",1.3825000524520874,1.8624999523162842,True,1.0078236856170264e-11,0.5520120859146118,1.3882990201214693,1.8605397868103712,1.3825,1.4224999999999999,1.8625,1.8625,0.039999999999999813,0.0 --s9qJ7ATP7w/8,-s9qJ7ATP7w,8,8,and,1.902500033378601,2.002500057220459,True,2.559467611809585e-12,0.25,1.9024795079759782,2.002565711600564,1.9025,1.9025,2.0025,2.0025,0.0,0.0 --s9qJ7ATP7w/8,-s9qJ7ATP7w,8,9,all,2.0625,2.1624999046325684,True,1.0053620262684415e-11,0.5506637692451477,2.0632850578056883,2.1639649354818697,2.0625,2.0625,2.1625,2.1625,0.0,0.0 --s9qJ7ATP7w/8,-s9qJ7ATP7w,8,10,these,2.202500104904175,2.382499933242798,True,1.4980766193523065e-12,0.25,2.2033509669407514,2.3840730034618955,2.2025,2.2025,2.3825,2.3825,0.0,0.0 --s9qJ7ATP7w/8,-s9qJ7ATP7w,8,11,other,2.4825000762939453,2.742500066757202,True,4.946603543443118e-11,2.7093875408172607,2.4818356624233613,2.7605229751379516,2.4825,2.4825,2.7425,2.7825,0.0,0.040000000000000036 --s9qJ7ATP7w/8,-s9qJ7ATP7w,8,12,things,2.762500047683716,3.122499942779541,True,4.533611680512806e-11,2.4831807613372803,2.795081236142752,3.131064936710411,2.7625,2.8425,3.1225,3.1625,0.07999999999999963,0.040000000000000036 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,0,it,0.48249998688697815,0.5625,True,2.2540422653372083e-11,0.62372887134552,0.48282851572821867,0.5627058230843515,0.4825,0.4825,0.5625,0.5625,0.0,0.0 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,1,comes,0.5824999809265137,0.8224999904632568,True,4.899627231713666e-11,1.3558037281036377,0.6122922089193678,0.8890952566150813,0.5824999999999999,0.6224999999999999,0.8025,1.1025,0.040000000000000036,0.30000000000000004 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,2,with,0.862500011920929,1.1024999618530273,True,5.177407114143051e-11,1.432669758796692,1.0343328058467511,1.2714862000398628,0.8624999999999999,2.0425,1.1025,2.3825,1.1800000000000002,1.2799999999999998 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,3,the,1.162500023841858,2.1424999237060547,True,1.6085549559008427e-11,0.4451123774051666,1.7534948157635741,2.317185306234759,1.1624999999999999,2.5025,2.1425,2.8225,1.34,0.6799999999999997 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,4,assistance,2.242500066757202,3.4625000953674316,True,5.7605586967213185e-11,1.5940369367599487,2.4377709212653507,3.5095971681953815,2.2425,2.9625,3.4025,3.6225,0.7199999999999998,0.2200000000000002 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,5,and,3.4825000762939453,3.5824999809265137,True,1.789636147608853e-11,0.4952203929424286,4.0819872324546465,4.286099413915198,3.4425,4.5425,3.5625,4.8425,1.1000000000000005,1.2800000000000002 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,6,agitation,4.542500019073486,5.402500152587891,True,5.5601932780202645e-11,1.5385926961898804,4.775625557132102,5.481898357717567,4.5425,5.0825000000000005,5.402500000000001,5.6625000000000005,0.54,0.2599999999999998 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,7,of,5.482500076293945,5.602499961853027,True,9.260540945188467e-11,2.5625369548797607,5.806335671074142,5.92265445706831,5.482500000000001,6.482500000000001,5.602500000000001,6.6225000000000005,1.0,1.0199999999999996 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,8,states,6.482500076293945,6.982500076293945,True,5.0344433483173745e-11,1.3931094408035278,6.551695071292202,6.893363711888713,6.482500000000001,6.8025,6.7225,7.0825000000000005,0.3199999999999994,0.3600000000000003 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,9,and,7.102499961853027,7.822500228881836,True,1.104089805692432e-10,3.055189609527588,6.97998107934995,7.432471150361345,6.8025,7.102500000000001,6.982500000000001,7.822500000000001,0.3000000000000007,0.8399999999999999 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,10,"regimes,",7.882500171661377,8.262499809265137,True,5.572348485416434e-11,1.5419561862945557,7.716863671576262,8.18288138010086,7.102500000000001,7.8825,8.1025,8.2625,0.7799999999999994,0.16000000000000014 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,11,Yesterday,8.302499771118164,8.842499732971191,True,9.80091181823628e-12,0.2712065875530243,8.243045019532943,8.802590784018477,8.1825,8.3025,8.782499999999999,8.8425,0.120000000000001,0.0600000000000005 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,12,Iran,9.302499771118164,9.442500114440918,True,9.267232814469395e-12,0.25643885135650635,9.28248466227814,9.428928899971622,9.3025,9.3025,9.442499999999999,9.442499999999999,0.0,0.0 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,13,announced,9.462499618530273,9.922499656677246,True,4.382011420389631e-11,1.2125712633132935,9.470828595188868,9.948668430727986,9.4625,9.5025,9.9225,10.0625,0.03999999999999915,0.14000000000000057 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,14,that,10.082500457763672,10.22249984741211,True,6.737973894110905e-12,0.25,10.112171472976984,10.317274030543697,10.0825,10.0825,10.2225,10.3425,0.0,0.11999999999999922 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,15,it,11.022500038146973,11.082500457763672,True,1.3952581277842935e-11,0.3860898017883301,10.98394079716456,11.063832396543807,10.9025,11.022499999999999,11.0425,11.1625,0.11999999999999922,0.11999999999999922 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,16,will,11.162500381469727,11.362500190734863,True,4.104548298466959e-11,1.135792851448059,11.193551591725347,11.379601260949299,11.1425,11.2625,11.362499999999999,11.5025,0.11999999999999922,0.14000000000000057 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,17,finance,11.422499656677246,11.762499809265137,True,2.8811382099536154e-11,0.7972561120986938,11.4400876158457,11.820485161778358,11.4225,11.5625,11.7625,11.9225,0.14000000000000057,0.16000000000000014 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,18,the,11.802499771118164,11.922499656677246,True,3.0040948895138087e-11,0.8312801718711853,11.866457503420186,11.978970130729623,11.782499999999999,11.942499999999999,11.9025,12.0825,0.16000000000000014,0.17999999999999972 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,19,families,11.942500114440918,12.382499694824219,True,3.755114622028266e-11,1.039099097251892,12.034518519610577,12.432086350730916,11.942499999999999,12.1025,12.3825,12.6425,0.16000000000000014,0.2599999999999998 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,20,of,12.462499618530273,12.542499542236328,True,2.093970396382927e-12,0.25,12.519979089225814,12.600236932231414,12.4625,12.7225,12.5425,12.8225,0.2599999999999998,0.27999999999999936 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,21,the,12.6225004196167,12.822500228881836,True,1.0107663404174128e-12,0.25,12.683711846600158,12.879735837706036,12.6225,13.6025,12.8225,13.7625,0.9799999999999986,0.9399999999999995 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,22,terrorists,13.582500457763672,14.102499961853027,True,3.2193830934446055e-11,0.890853762626648,13.48057177307044,14.12193960941006,12.9225,13.8025,14.022499999999999,14.3225,0.8800000000000008,0.3000000000000007 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,23,and,14.242500305175781,14.442500114440918,True,6.540654823306014e-11,1.8099017143249512,14.243990294329773,14.439934456951706,14.1625,14.3825,14.3225,14.5025,0.22000000000000064,0.17999999999999972 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,24,murderers,14.602499961853027,15.202500343322754,True,5.3976757091733774e-11,1.4936214685440063,14.574493863698141,15.18575901971097,14.3825,14.6025,15.1625,15.2425,0.21999999999999886,0.08000000000000007 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,25,this,15.282500267028809,15.662500381469727,True,9.564676828333063e-11,2.646696090698242,15.271233298767404,15.507784351694662,15.2225,15.2825,15.4625,15.6625,0.0600000000000005,0.1999999999999993 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,26,shows,15.762499809265137,16.162500381469727,True,1.070308425221711e-10,2.9617111682891846,15.638094435743163,15.937968171367956,15.4825,15.7625,15.7425,16.1625,0.27999999999999936,0.4200000000000017 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,27,that,16.22249984741211,16.422500610351562,True,1.4821713301138573e-10,4.0,16.03565573699944,16.203248310703422,15.7625,16.2225,16.1625,16.4025,0.46000000000000085,0.23999999999999844 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,28,"Iran,",16.502500534057617,16.72249984741211,True,4.210410839422529e-11,1.1650867462158203,16.26544869858648,16.458665519694218,16.2225,16.5025,16.3625,16.7225,0.28000000000000114,0.35999999999999943 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,29,even,17.5625,17.762500762939453,True,9.684803653486895e-11,2.6799371242523193,16.61354563803406,16.827777791718276,16.5025,17.5625,16.7225,17.762500000000003,1.0599999999999987,1.0400000000000027 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,30,after,17.822500228881836,18.002500534057617,True,3.2281885498086638e-12,0.25,17.554003479065504,17.80643906509736,17.5225,17.8225,17.762500000000003,18.0025,0.3000000000000007,0.23999999999999844 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,31,the,18.0625,18.202499389648438,True,1.899481093248223e-11,0.5256162285804749,17.860950102720363,18.01428792989417,17.8225,18.0625,17.962500000000002,18.2025,0.23999999999999844,0.23999999999999844 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,32,nuclear,18.282499313354492,18.622499465942383,True,7.600799330209629e-12,0.25,18.086117188736683,18.544572324433087,18.0625,18.282500000000002,18.5225,18.622500000000002,0.22000000000000242,0.10000000000000142 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,33,"agreement,",18.6825008392334,19.502500534057617,True,1.3309903179603566e-10,3.683058977127075,18.689252254938246,19.452889571682917,18.622500000000002,18.6825,19.422500000000003,19.5025,0.05999999999999872,0.0799999999999983 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,34,is,19.6825008392334,19.762500762939453,True,6.084657951099803e-12,0.25,19.557316484633294,19.728965377547198,19.4825,19.6825,19.7025,19.762500000000003,0.1999999999999993,0.060000000000002274 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,35,continuing,20.202499389648438,20.662500381469727,True,5.529132013348814e-11,1.5299975872039795,20.186404995029186,20.684973994192696,20.2025,20.2025,20.6625,20.742500000000003,0.0,0.08000000000000185 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,36,to,21.502500534057617,21.582500457763672,True,9.673984946445557e-10,4.0,21.502510645887668,21.582509151446565,21.5025,21.5025,21.582500000000003,21.582500000000003,0.0,0.0 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,37,aid,21.662500381469727,21.782499313354492,True,4.237645789828548e-10,4.0,21.662507714897142,21.788616675529326,21.6625,21.6625,21.782500000000002,21.8225,0.0,0.03999999999999915 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,38,"terrorism,",21.842500686645508,22.342500686645508,True,9.071070283805938e-12,0.2510107457637787,21.838637629170766,22.378070868609647,21.802500000000002,21.8625,22.3425,22.442500000000003,0.05999999999999872,0.10000000000000142 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,39,including,22.6825008392334,23.162500381469727,True,6.269147527493413e-12,0.25,22.67344056762576,23.179853509455537,22.6825,22.6825,23.1625,23.262500000000003,0.0,0.10000000000000142 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,40,Palestinian,23.342500686645508,24.042499542236328,True,1.5516138721083372e-11,0.4293558895587921,23.341317527591546,24.04398988161638,23.3425,23.3425,24.0025,24.082500000000003,0.0,0.08000000000000185 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,41,"terrorism,",24.102500915527344,24.582500457763672,True,2.0350023749449164e-11,0.5631170868873596,24.10249792843023,24.583562825209636,24.102500000000003,24.102500000000003,24.582500000000003,24.582500000000003,0.0,0.0 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,42,Hezbollah,24.702499389648438,25.262500762939453,True,8.40829662840381e-12,0.25,24.68922904288737,25.2904581805427,24.642500000000002,24.7025,25.2025,25.3825,0.05999999999999872,0.17999999999999972 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,43,terrorism,25.322500228881836,26.002500534057617,True,7.838881627142413e-11,2.1691415309906006,25.346885974875732,26.004277391559278,25.3225,25.422500000000003,26.0025,26.0025,0.10000000000000142,0.0 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,44,and,26.842500686645508,26.982500076293945,True,3.270300696911477e-11,0.9049434661865234,26.818193885178502,26.98777704569297,26.802500000000002,26.8425,26.922500000000003,27.0225,0.03999999999999915,0.09999999999999787 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,45,its,27.082500457763672,27.202499389648438,True,3.613817578518308e-11,1.0,27.057459753673502,27.203179205761856,26.962500000000002,27.082500000000003,27.1625,27.242500000000003,0.120000000000001,0.08000000000000185 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,46,assistance,27.282499313354492,28.122499465942383,True,1.4203026255099616e-10,3.9302000999450684,27.289326195794334,28.100023559728623,27.282500000000002,27.282500000000002,28.062500000000004,28.142500000000002,0.0,0.0799999999999983 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,47,to,28.202499389648438,28.282499313354492,True,7.287294032098934e-12,0.25,28.202197475208703,28.282161719627336,28.2025,28.2025,28.282500000000002,28.282500000000002,0.0,0.0 --yRb-Jum7EQ/1,-yRb-Jum7EQ,1,48,Hamas.,28.342500686645508,28.782499313354492,True,2.1801163305190663e-11,0.6032723784446716,28.34016592506999,28.781192489043658,28.302500000000002,28.3425,28.782500000000002,28.782500000000002,0.03999999999999915,0.0 --yRb-Jum7EQ/5,-yRb-Jum7EQ,5,0,Yesterday,0.12250000238418579,0.862500011920929,True,2.1098019165055604e-11,0.4256690740585327,0.11640499422426298,0.8237373720723118,0.0625,0.1225,0.7825,0.8624999999999999,0.06,0.07999999999999996 --yRb-Jum7EQ/5,-yRb-Jum7EQ,5,1,Eliav,0.9024999737739563,1.162500023841858,True,6.203321190056954e-11,1.2515686750411987,0.8757917552775388,1.1610153192742962,0.8424999999999999,0.9025,1.1225,1.1624999999999999,0.06000000000000005,0.039999999999999813 --yRb-Jum7EQ/5,-yRb-Jum7EQ,5,2,Gelman,1.222499966621399,1.662500023841858,True,2.492321973801559e-11,0.5028454661369324,1.2232918082472444,1.6615993583479005,1.2225,1.2225,1.6025,1.6824999999999999,0.0,0.07999999999999985 --yRb-Jum7EQ/5,-yRb-Jum7EQ,5,3,lost,2.7225000858306885,2.862499952316284,True,5.466818109312044e-10,4.0,2.709146128467911,2.8661180187391095,2.7025,2.7625,2.8625,2.9225,0.06000000000000005,0.06000000000000005 --yRb-Jum7EQ/5,-yRb-Jum7EQ,5,4,his,2.9024999141693115,3.002500057220459,True,3.090692146656693e-10,4.0,2.9108267355157285,3.0414643223665143,2.9025,2.9625,3.0025,3.2425,0.06000000000000005,0.2400000000000002 --yRb-Jum7EQ/5,-yRb-Jum7EQ,5,5,life,3.1024999618530273,3.362499952316284,True,1.2600011312091652e-10,2.5421509742736816,3.1401606861304536,3.357841510464017,3.0225,3.3025,3.2425,3.5625,0.28000000000000025,0.31999999999999984 --yRb-Jum7EQ/5,-yRb-Jum7EQ,5,6,in,3.442500114440918,3.5625,True,2.6729063407060494e-10,4.0,3.428606886284111,3.532967025626201,3.3025,3.6625,3.3625,3.7225,0.3599999999999999,0.3600000000000003 --yRb-Jum7EQ/5,-yRb-Jum7EQ,5,7,another,3.6624999046325684,4.242499828338623,True,3.822804919839662e-11,0.771280825138092,3.6285882996720065,4.14030831047379,3.4425,3.8025,3.9425,4.242500000000001,0.3600000000000003,0.3000000000000007 --yRb-Jum7EQ/5,-yRb-Jum7EQ,5,8,terrorist,4.28249979019165,5.242499828338623,True,4.334416506268646e-11,0.8745024800300598,4.227954760286244,5.168522414951293,4.062500000000001,4.3425,4.9625,5.242500000000001,0.27999999999999936,0.28000000000000025 --yRb-Jum7EQ/5,-yRb-Jum7EQ,5,9,"attack,",5.34250020980835,5.682499885559082,True,6.46387596225928e-11,1.3041375875473022,5.276098853024842,5.630281070381624,5.1225000000000005,5.3425,5.442500000000001,5.7225,0.21999999999999975,0.27999999999999936 --yRb-Jum7EQ/5,-yRb-Jum7EQ,5,10,not,5.78249979019165,5.902500152587891,True,1.2150396140608866e-11,0.25,5.716276151729501,5.852571298442281,5.482500000000001,5.782500000000001,5.6825,5.9225,0.2999999999999998,0.2400000000000002 --yRb-Jum7EQ/5,-yRb-Jum7EQ,5,11,by,5.982500076293945,6.082499980926514,True,1.0236080212611132e-11,0.25,5.934587808080619,6.029627616167395,5.782500000000001,5.982500000000001,5.862500000000001,6.0825000000000005,0.20000000000000018,0.21999999999999975 --yRb-Jum7EQ/5,-yRb-Jum7EQ,5,12,the,6.122499942779541,6.302499771118164,True,4.95643699693904e-11,1.0,6.089065477376196,6.26458295760959,5.982500000000001,6.1225000000000005,6.2225,6.3025,0.13999999999999968,0.08000000000000007 --yRb-Jum7EQ/5,-yRb-Jum7EQ,5,13,students,6.322500228881836,6.802499771118164,True,1.086939913075291e-10,2.192986488342285,6.304983799467197,6.802649601015644,6.282500000000001,6.322500000000001,6.8025,6.8025,0.040000000000000036,0.0 --yRb-Jum7EQ/5,-yRb-Jum7EQ,5,14,of,7.422500133514404,7.522500038146973,True,3.4040623098086087e-10,4.0,7.421097526520383,7.5222877816487355,7.4225,7.4225,7.522500000000001,7.522500000000001,0.0,0.0 --yRb-Jum7EQ/5,-yRb-Jum7EQ,5,15,"terrorism,",7.662499904632568,8.362500190734863,True,1.7434940643989982e-11,0.3517635762691498,7.651950712497826,8.326166381941334,7.5825000000000005,7.6625000000000005,8.282499999999999,8.362499999999999,0.08000000000000007,0.08000000000000007 --yRb-Jum7EQ/5,-yRb-Jum7EQ,5,16,but,8.40250015258789,8.542499542236328,True,4.870383610300344e-12,0.25,8.40232606126986,8.544283059130962,8.4025,8.4025,8.5425,8.5425,0.0,0.0 --yRb-Jum7EQ/5,-yRb-Jum7EQ,5,17,by,8.662500381469727,8.72249984741211,True,3.2112475872869695e-11,0.6478943824768066,8.65890888774039,8.725163996226525,8.6425,8.7025,8.7225,8.7625,0.0600000000000005,0.03999999999999915 --yRb-Jum7EQ/5,-yRb-Jum7EQ,5,18,those,8.782500267028809,9.162500381469727,True,9.06100472430893e-11,1.828128695487976,8.782524958225315,9.20255260115738,8.782499999999999,8.782499999999999,9.1625,9.3225,0.0,0.16000000000000014 --yRb-Jum7EQ/5,-yRb-Jum7EQ,5,19,who,9.202500343322754,9.322500228881836,True,7.350461905808459e-11,1.4830132722854614,9.292884555691698,9.434678222093696,9.2025,9.4225,9.3225,9.5825,0.21999999999999886,0.2599999999999998 --yRb-Jum7EQ/5,-yRb-Jum7EQ,5,20,teach,9.422499656677246,9.72249984741211,True,4.777102324826643e-11,0.963817834854126,9.512342365613454,9.798499598139479,9.4025,9.6225,9.7225,9.8825,0.22000000000000064,0.16000000000000014 --yRb-Jum7EQ/5,-yRb-Jum7EQ,5,21,"terrorism,",9.822500228881836,10.6225004196167,True,2.364412277078287e-10,4.0,9.885742869369814,10.623797601314282,9.8225,9.9625,10.522499999999999,10.8025,0.14000000000000057,0.28000000000000114 --yRb-Jum7EQ/5,-yRb-Jum7EQ,5,22,a,10.842499732971191,10.862500190734863,True,7.060157580091042e-12,0.25,10.76912108115059,10.789121081150874,10.6025,10.8425,10.6225,10.862499999999999,0.2400000000000002,0.23999999999999844 --yRb-Jum7EQ/5,-yRb-Jum7EQ,5,23,Palestinian,10.962499618530273,12.522500038146973,True,4.3775850999683286e-11,0.8832120895385742,10.898607984569265,12.05718561330501,10.782499999999999,10.9625,11.6625,12.522499999999999,0.1800000000000015,0.8599999999999994 --yRb-Jum7EQ/5,-yRb-Jum7EQ,5,24,teacher.,12.5625,12.962499618530273,True,8.628150971468074e-11,1.7407970428466797,12.515745111313707,12.963414362425844,12.4625,12.6225,12.942499999999999,12.9825,0.16000000000000014,0.040000000000000924 --yRb-Jum7EQ/6,-yRb-Jum7EQ,6,0,"Therefore,",0.4025000035762787,0.9424999952316284,True,1.6840784322624813e-10,1.0,0.4024729803370939,0.9336746683054675,0.4025,0.4025,0.9025,0.9624999999999999,0.0,0.05999999999999994 --yRb-Jum7EQ/6,-yRb-Jum7EQ,6,1,the,1.0625,1.2024999856948853,True,9.747938567450376e-11,0.5788292288780212,1.0589909815193694,1.1984154783750278,1.0625,1.0625,1.1624999999999999,1.2025,0.0,0.040000000000000036 --yRb-Jum7EQ/6,-yRb-Jum7EQ,6,2,world,1.2625000476837158,1.5225000381469727,True,1.6847746808767994e-10,1.000413417816162,1.2558060204353718,1.5185764126331496,1.2225,1.2625,1.5225,1.5225,0.040000000000000036,0.0 --yRb-Jum7EQ/6,-yRb-Jum7EQ,6,3,needs,1.5625,1.902500033378601,True,1.0756048135496243e-10,0.6386904716491699,1.5614918157611801,1.8797170301478279,1.5625,1.5625,1.7825,1.9625,0.0,0.17999999999999994 --yRb-Jum7EQ/6,-yRb-Jum7EQ,6,4,to,1.9424999952316284,2.002500057220459,True,1.7243546868161985e-10,1.0239158868789673,1.9494528303504337,2.021352098064118,1.8825,2.2425,1.9625,2.3225,0.3600000000000001,0.3599999999999999 --yRb-Jum7EQ/6,-yRb-Jum7EQ,6,5,stand,2.0425000190734863,2.4625000953674316,True,1.421072287621783e-10,0.8438278436660767,2.1454380160719135,2.5239863439827293,2.0425,2.3825,2.4625,2.8225,0.33999999999999986,0.3599999999999999 --yRb-Jum7EQ/6,-yRb-Jum7EQ,6,6,with,2.5425000190734863,2.822499990463257,True,3.683832960899025e-10,2.1874473094940186,2.627782996043301,2.9132515079477193,2.5425,2.8625,2.8225,3.9025,0.31999999999999984,1.08 --yRb-Jum7EQ/6,-yRb-Jum7EQ,6,7,Israel,3.742500066757202,4.122499942779541,True,1.1312620978864985e-10,0.6717395782470703,3.7309032744213915,4.150365024998529,3.7425,3.9425,4.1225000000000005,4.2225,0.19999999999999973,0.09999999999999964 --yRb-Jum7EQ/6,-yRb-Jum7EQ,6,8,against,4.242499828338623,4.682499885559082,True,2.678313681947486e-10,1.5903735160827637,4.242938262935196,4.670751606173934,4.242500000000001,4.242500000000001,4.5825000000000005,4.7225,0.0,0.13999999999999968 --yRb-Jum7EQ/6,-yRb-Jum7EQ,6,9,this,4.742499828338623,4.902500152587891,True,9.41213912364347e-11,0.5588895678520203,4.724187153540902,4.903113320015298,4.6625000000000005,4.742500000000001,4.862500000000001,4.902500000000001,0.08000000000000007,0.040000000000000036 --yRb-Jum7EQ/6,-yRb-Jum7EQ,6,10,"incitement,",5.422500133514404,6.102499961853027,True,6.119732498532926e-11,0.3633876144886017,5.423858436959219,6.115242073345665,5.4225,5.4225,6.102500000000001,6.202500000000001,0.0,0.09999999999999964 --yRb-Jum7EQ/6,-yRb-Jum7EQ,6,11,which,6.502500057220459,6.802499771118164,True,2.0067764117115416e-10,1.1916170120239258,6.50248685522129,6.802489095420521,6.5025,6.5025,6.8025,6.8025,0.0,0.0 --yRb-Jum7EQ/6,-yRb-Jum7EQ,6,12,is,6.862500190734863,6.942500114440918,True,8.340554358277075e-10,4.0,6.8625014843098695,6.942410921639754,6.862500000000001,6.862500000000001,6.942500000000001,6.942500000000001,0.0,0.0 --yRb-Jum7EQ/6,-yRb-Jum7EQ,6,13,the,7.002500057220459,7.182499885559082,True,3.8694789039617206e-10,2.2976832389831543,7.002492295030229,7.182530934830729,7.0025,7.0025,7.1825,7.1825,0.0,0.0 --yRb-Jum7EQ/6,-yRb-Jum7EQ,6,14,number,7.402500152587891,7.762499809265137,True,2.0023324664997233e-10,1.1889781951904297,7.378536282253883,7.766816192156913,7.3025,7.402500000000001,7.6825,7.822500000000001,0.10000000000000053,0.14000000000000057 --yRb-Jum7EQ/6,-yRb-Jum7EQ,6,15,one,9.782500267028809,9.90250015258789,True,1.6587432816184133e-10,0.9849560856819153,9.77142133456187,9.889990542704302,9.7425,9.782499999999999,9.8425,9.9025,0.03999999999999915,0.0600000000000005 --yRb-Jum7EQ/6,-yRb-Jum7EQ,6,16,cause,9.962499618530273,10.162500381469727,True,1.8768611664832235e-10,1.1144737005233765,9.974359250912508,10.190149976930748,9.9625,10.0025,10.1625,10.2225,0.03999999999999915,0.0600000000000005 --yRb-Jum7EQ/6,-yRb-Jum7EQ,6,17,of,10.382499694824219,10.442500114440918,True,3.711768045699948e-11,0.25,10.352394778030892,10.418035924396685,10.2025,10.3825,10.2625,10.442499999999999,0.17999999999999972,0.17999999999999972 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+-yRb-Jum7EQ/6,-yRb-Jum7EQ,6,1,0.0,0,-0.1357426941394806,0,-0.057185620069503784,0,-0.1435268521308899,0,-0.011820107698440552,0,-0.07956936955451965 diff --git a/math/Q1/results/model_comparison_v2/report.md b/math/Q1/results/model_comparison_v2/report.md new file mode 100644 index 0000000..c6e3f38 --- /dev/null +++ b/math/Q1/results/model_comparison_v2/report.md @@ -0,0 +1,13 @@ +# Q1 V2 B0-B4 对照 + +本报告使用 `features_v2/` 的 100 个样本，以 `video_id` 做五折 GroupKFold。B0–B4 的缩放器只在各折训练部分拟合。分数是情感信息探针，不是真实对齐边界准确率。 + +| 分支 | OOF Accuracy | OOF Macro-F1 | OOF MAE | OOF RMSE | OOF Pearson | +|---|---:|---:|---:|---:|---:| +| B0 | 0.5900 | 0.3373 | 0.5345 | 0.7325 | 0.4255 | +| B1 | 0.5700 | 0.3084 | 0.5342 | 0.7444 | 0.3981 | +| B2 | 0.5500 | 0.2769 | 0.5308 | 0.7342 | 0.4232 | +| B3 | 0.5700 | 0.3084 | 0.5202 | 0.7371 | 0.4114 | +| B4 | 0.6000 | 0.3882 | 0.5393 | 0.7628 | 0.3413 | + +B5 通过词查询 CSR 矩阵进行物理来源核查；没有人工边界真值，因此未报告边界误差或后验校准率。B6 内容探针未启用。视觉 17 维来自 OpenFace 2.2.0 AU 输出，不是 MediaPipe 代理。 diff --git a/math/Q1/results/model_comparison_v2/run_manifest.json b/math/Q1/results/model_comparison_v2/run_manifest.json new file mode 100644 index 0000000..4814630 --- /dev/null +++ b/math/Q1/results/model_comparison_v2/run_manifest.json @@ -0,0 +1,22 @@ +{ + "version": "E题V2 Q1 B0-B4", + "samples": 100, + "video_groups": 37, + "folds": 5, + "grouping": "video_id GroupKFold; train/valid group disjoint", + "scalers": "B0 train-fold mean/std; B1-B4 train-fold median/MAD; no held-fold fitting", + "classifier": "LogisticRegression C=0.05", + "regressor": "Ridge alpha=25", + "branches": { + "B0": "quality-weighted physical projection", + "B1": "B0 plus train-fold robust scale and SO(3)/unit-gaze aggregation", + "B2": "B1 plus CTC forward-backward text occupancy", + "B3": "B1 plus native-row level-2 dynamics", + "B4": "B1 plus frozen Wav2Vec2 auxiliary representation" + }, + "B5": "query H_time audit only; not predictive score", + "B6": "content probe disabled", + "feature_manifest_sha256": "172d5d11964a800fff364e0592afb6959fa4bdc52f91106d4da428fcc175a054", + "source_run_manifest": "features_v2/manifest_q1.jsonl", + "bootstrap_repeats": 200 +} \ No newline at end of file diff --git a/math/Q1/results/model_comparison/split_assignments.csv b/math/Q1/results/model_comparison_v2/split_assignments.csv similarity index 100% rename from math/Q1/results/model_comparison/split_assignments.csv rename to math/Q1/results/model_comparison_v2/split_assignments.csv diff --git a/math/Q1/run_openface.ps1 b/math/Q1/run_openface.ps1 new file mode 100644 index 0000000..5cc9e5b --- /dev/null +++ b/math/Q1/run_openface.ps1 @@ -0,0 +1,33 @@ +param( + [Parameter(Mandatory = $true)] + [string]$VideoRelativePath, + [Parameter(Mandatory = $true)] + [string]$OutputName +) + +$ErrorActionPreference = 'Stop' +$q1Directory = $PSScriptRoot +$repositoryDirectory = Split-Path (Split-Path $q1Directory -Parent) -Parent +$packageDirectory = Join-Path $q1Directory 'cache/openface/OpenFace_2.2.0_win_x64' +$executable = Join-Path $packageDirectory 'FeatureExtraction.exe' +$videoPath = Join-Path $repositoryDirectory ($VideoRelativePath -replace '/', '\') +$outputDirectory = Join-Path $q1Directory 'cache/openface_outputs' +$null = New-Item -ItemType Directory -Force -Path $outputDirectory + +if (-not (Test-Path -LiteralPath $executable -PathType Leaf)) { + throw "OpenFace 2.2.0 executable not found: $executable" +} +if (-not (Test-Path -LiteralPath $videoPath -PathType Leaf)) { + throw "Input video not found: $videoPath" +} + +Push-Location $packageDirectory +try { + & $executable -mloc model/main_clnf_general.txt -f $videoPath -out_dir $outputDirectory -of $OutputName -2Dfp -pose -aus -gaze + if ($LASTEXITCODE -ne 0) { + throw "OpenFace FeatureExtraction failed with exit code $LASTEXITCODE for $VideoRelativePath" + } +} +finally { + Pop-Location +} diff --git a/math/Q1/results/model_comparison/run_manifest.json b/math/Q1/source_cache_manifest.json similarity index 87% rename from math/Q1/results/model_comparison/run_manifest.json rename to math/Q1/source_cache_manifest.json index f24a1b8..7c09e12 100644 --- a/math/Q1/results/model_comparison/run_manifest.json +++ b/math/Q1/source_cache_manifest.json @@ -1,16 +1,16 @@ { - "created_at_local": "2026-09-23 22:17:06 +0800", + "created_at_local": "2026-09-24 19:27:55 +0800", "python": "3.14.7 (main, Aug 10 2026, 00:00:00) [GCC 16.1.1 20260515 (Red Hat 16.1.1-2)]", "platform": "Linux-6.6.87.2-microsoft-standard-WSL2-x86_64-with-glibc2.43", - "uv_version": "uv 0.11.28 (x86_64-unknown-linux-gnu)", + "uv_version": "uv run parent; executable not on child PATH", "packages": { "torch": "2.14.0+cu130", "transformers": "5.17.0", "numpy": "2.5.3", "scipy": "1.18.1", "scikit-learn": "1.9.1", - "mediapipe": "1.0.1", "opencv-python-headless": "5.0.0.93", + "librosa": "1.0.0", "openpyxl": "3.1.5", "matplotlib": "3.11.2" }, @@ -25,7 +25,12 @@ "speech_stride_samples": 320, "speech_receptive_field_samples": 400 }, - "face_landmarker_asset_sha256": "64184e229b263107bc2b804c6625db1341ff2bb731874b0bcc2fe6544e0bc9ff", + "openface": { + "version": "2.2.0", + "executable": "FeatureExtraction", + "landmark_model": "main_clnf_general.txt", + "confidence_threshold": 0.8 + }, "inputs": { "label_file": "/home/gloamxun/modeling_zhaocui/E题数据/附件1-数据集原始多模态样本/MOSEI数据集部分原始视频-100条/label-100.xlsx", "label_file_sha256": "827334f782b1f242c84ad944a657bc7f7c63643f71ae9c977811a3eecdd3ab33", @@ -214,7 +219,7 @@ "delta_mfcc_12", "log_energy", "log_f0_hz", - "voicing_strength", + "voiced_probability", "spectral_centroid_hz", "spectral_bandwidth_hz", "spectral_flux", @@ -222,49 +227,61 @@ "hnr_db" ], "vision_features": [ - "mp_blendshape_browDownLeft", - "mp_blendshape_browDownRight", - "mp_blendshape_browInnerUp", - "mp_blendshape_browOuterUpLeft", - "mp_blendshape_browOuterUpRight", - "mp_blendshape_eyeBlinkLeft", - "mp_blendshape_eyeBlinkRight", - "mp_blendshape_eyeSquintLeft", - "mp_blendshape_eyeSquintRight", - "mp_blendshape_eyeWideLeft", - "mp_blendshape_eyeWideRight", - "mp_blendshape_jawOpen", - "mp_blendshape_mouthFrownLeft", - "mp_blendshape_mouthFrownRight", - "mp_blendshape_mouthPucker", - "mp_blendshape_mouthSmileLeft", - "mp_blendshape_mouthSmileRight", - "pose_rotvec_x", - "pose_rotvec_y", - "pose_rotvec_z", - "pose_translation_x", - "pose_translation_y", - "pose_translation_z", - "gaze_left_x", - "gaze_left_y", - "gaze_left_z", - "gaze_right_x", - "gaze_right_y", - "gaze_right_z", - "eye_aperture_left", - "eye_aperture_right", - "mouth_aperture", - "mouth_width_face_ratio", - "brow_eye_distance_left", - "brow_eye_distance_right" + "AU01_r", + "AU02_r", + "AU04_r", + "AU05_r", + "AU06_r", + "AU07_r", + "AU09_r", + "AU10_r", + "AU12_r", + "AU14_r", + "AU15_r", + "AU17_r", + "AU20_r", + "AU23_r", + "AU25_r", + "AU26_r", + "AU45_r", + "pose_Rx", + "pose_Ry", + "pose_Rz", + "pose_Tx", + "pose_Ty", + "pose_Tz", + "gaze_0_x", + "gaze_0_y", + "gaze_0_z", + "gaze_1_x", + "gaze_1_y", + "gaze_1_z", + "geometry_eye_open_left", + "geometry_eye_open_right", + "geometry_mouth_open", + "geometry_mouth_width", + "geometry_brow_eye_left", + "geometry_brow_eye_right" ], - "vision_feature_note": "17 MediaPipe blendshape proxies and approximate gaze/landmark geometry; not OpenFace AU labels", + "vision_feature_note": "OpenFace 2.2.0 AU intensities, pose, gaze, and six geometry values defined in E题V2.pdf section 4.2.3", "grid_step_s": 0.1, "audio_window_samples": 400, "audio_step_samples": 160, "audio_fft": 512, "audio_mel_bands": 40, - "vision_sample_rate_hz": 5.0, + "pitch_estimator": { + "name": "librosa.pyin", + "version": "1.0.0", + "f0_range_hz": [ + 80.0, + 400.0 + ], + "frame_length_samples": 400, + "hop_length_samples": 160, + "center": false + }, + "hnr_estimator": "autocorrelation periodicity at pYIN-detected F0; dB", + "vision_sample_rate_hz": "native OpenFace frame timestamps; no fixed-rate assumption", "grouping": "GroupKFold by video_id", "fold_count": 5, "probe": { @@ -279,15 +296,15 @@ }, "bootstrap": { "unit": "video_id", - "repeats": 2000, + "repeats": 200, "seed": 20260923 }, "human_boundary_reference_count": 0, "boundary_interval_level": 0.9, - "hard_text_quality_weight": "per-sample median-normalized CTC path score clipped to [0.25, 4.0]; uncalibrated", - "cache_schema": "q1-b0b4-v3" + "hard_text_quality_weight": "raw fixed-transcript CTC word path score in [0,1]; unavailable scores use q*=1 and are flagged unavailable", + "cache_schema": "q1-b0b4-v4-openface" }, "output_dir": "/home/gloamxun/modeling_zhaocui/math/Q1/results/model_comparison", - "typical_sample_id": "-9y-fZ3swSY/0", - "elapsed_seconds": 124.10033178329468 + "typical_sample_id": "-tANM6ETl_M/3", + "elapsed_seconds": 63.887396574020386 } diff --git a/math/Q1/test_projection.py b/math/Q1/test_projection.py new file mode 100644 index 0000000..5d70a10 --- /dev/null +++ b/math/Q1/test_projection.py @@ -0,0 +1,25 @@ +"""Projection invariants from E题V2: quality weights means, not physical coverage.""" +from __future__ import annotations + +import unittest + +import numpy as np + +import compare_models as cm + + +class ProjectionCoverageTests(unittest.TestCase): + def test_quality_changes_mean_but_not_physical_coverage(self) -> None: + values = np.asarray([[0.0], [10.0]], dtype=np.float32) + observed = np.ones_like(values, dtype=bool) + intervals = np.asarray([[0.0, 0.5], [0.5, 1.0]], dtype=np.float32) + qualities = np.asarray([1.0, 1e-8], dtype=np.float32) + edges = np.asarray([0.0, 1.0], dtype=np.float32) + projected, mask, coverage = cm._project_rows(values, observed, intervals, qualities, edges) + self.assertTrue(bool(mask[0, 0])) + self.assertAlmostEqual(float(projected[0, 0]), 10.0 * 1e-8 / (1.0 + 1e-8), places=6) + self.assertAlmostEqual(float(coverage[0, 0]), 1.0, places=6) + + +if __name__ == "__main__": + unittest.main() diff --git a/math/Q1/visualize_alignment.py b/math/Q1/visualize_alignment.py new file mode 100644 index 0000000..8e4a797 --- /dev/null +++ b/math/Q1/visualize_alignment.py @@ -0,0 +1,230 @@ +"""Render a selected Q1 word-to-source alignment example.""" +from __future__ import annotations + +import argparse +import json +import sys +from pathlib import Path +from typing import Any + +import matplotlib + +matplotlib.use("Agg") +matplotlib.rcParams["font.family"] = ["FandolHei", "DejaVu Sans"] +matplotlib.rcParams["axes.unicode_minus"] = False +import matplotlib.pyplot as plt +import numpy as np +from matplotlib.colors import PowerNorm + +Q1_DIR = Path(__file__).resolve().parent +sys.path.insert(0, str(Q1_DIR)) +from q1_io import csr_from_sample, load_sample # noqa: E402 + + +def time_edges(centers: np.ndarray, intervals: np.ndarray, duration_s: float) -> np.ndarray: + """Make non-overlapping display bins centered on each native source row.""" + centers = np.asarray(centers, dtype=np.float64).reshape(-1) + intervals = np.asarray(intervals, dtype=np.float64) + if not len(centers): + return np.asarray([0.0, duration_s], dtype=np.float64) + if len(centers) == 1: + half_width = max(float(intervals[0, 1] - intervals[0, 0]) / 2, 1e-3) + return np.asarray( + [max(0.0, centers[0] - half_width), min(duration_s, centers[0] + half_width)], + dtype=np.float64, + ) + if np.any(np.diff(centers) <= 0): + raise ValueError("native source timestamps must be strictly increasing") + middle = (centers[:-1] + centers[1:]) / 2 + first = max(0.0, centers[0] - (middle[0] - centers[0])) + last = min(duration_s, centers[-1] + (centers[-1] - middle[-1])) + return np.concatenate(([first], middle, [last])) + + +def read_records() -> list[dict[str, Any]]: + path = Q1_DIR / "features_v2" / "manifest_q1.jsonl" + return [json.loads(line) for line in path.read_text(encoding="utf-8").splitlines() if line.strip()] + + +def choose_sample(sample_id: str) -> tuple[dict[str, Any], dict[str, Any], Any, Any]: + record = next((item for item in read_records() if item["sample_id"] == sample_id), None) + if record is None: + raise ValueError(f"sample_id not found in Q1 manifest: {sample_id}") + sample = load_sample(sample_id) + audio_map = csr_from_sample(sample, "query_word_audio_H_time") + vision_map = csr_from_sample(sample, "query_word_vision_H_time") + if not audio_map.nnz or not vision_map.nnz: + raise ValueError(f"sample has no valid audio or vision query rows: {sample_id}") + return record, sample, audio_map, vision_map + + +def main() -> None: + parser = argparse.ArgumentParser(description=__doc__) + parser.add_argument("--sample-id", default="-iRBcNs9oI8/8") + parser.add_argument("--output", type=Path, default=None) + args = parser.parse_args() + + record, sample, audio_map, vision_map = choose_sample(args.sample_id) + words = [str(word) for word in sample["native_text_words"]] + if audio_map.shape[0] != len(words) or vision_map.shape[0] != len(words): + raise ValueError("query matrix word rows do not match the stored transcript") + duration_s = float(sample["_meta"]["duration_s"]) + + modalities = [ + ( + "原始音频位置", + audio_map, + sample["native_audio_intervals"], + "音频窗中心时间 (s)", + "音频窗", + ), + ( + "原始视频帧位置", + vision_map, + sample["native_vision_intervals"], + "视频帧中心时间 (s)", + "视频帧", + ), + ] + matrices = [item[1].toarray().astype(np.float32) for item in modalities] + for matrix in (audio_map, vision_map): + row_sums = np.asarray(matrix.sum(axis=1)).reshape(-1) + populated = row_sums > 0 + if populated.any() and not np.allclose(row_sums[populated], 1.0, atol=2e-3): + raise ValueError("each populated word-query row should sum to one") + nonzero = np.concatenate([matrix[matrix > 0] for matrix in matrices if np.any(matrix > 0)]) + color_max = max(float(nonzero.max()), 1e-6) + + height = max(10.5, min(26.0, 4.0 + 0.22 * len(words))) + tick_size = max(5.5, min(8.5, 8.8 - 0.045 * len(words))) + fig = plt.figure(figsize=(15, height)) + grid = fig.add_gridspec(4, 1, height_ratios=(4.0, 1.35, 4.0, 1.35), hspace=0.35) + y_edges = np.arange(len(words) + 1, dtype=np.float64) + text_intervals = np.asarray(sample["native_text_intervals"], dtype=np.float64) + text_valid = text_intervals[:, 1] > text_intervals[:, 0] + text_centers = text_intervals.mean(axis=1) + meshes = [] + heat_axes = [] + + for plot_index, ((title, _sparse_matrix, intervals, _xlabel, row_name), matrix) in enumerate(zip(modalities, matrices)): + axis = fig.add_subplot(grid[2 * plot_index]) + text_axis = fig.add_subplot(grid[2 * plot_index + 1], sharex=axis) + heat_axes.append(axis) + intervals = np.asarray(intervals, dtype=np.float64) + centers = intervals.mean(axis=1) + x_edges = time_edges(centers, intervals, duration_s) + mesh = axis.pcolormesh( + x_edges, + y_edges, + matrix, + shading="flat", + cmap="magma", + norm=PowerNorm(gamma=0.5, vmin=0.0, vmax=color_max), + rasterized=True, + ) + meshes.append(mesh) + axis.set_xlim(0.0, duration_s) + axis.set_ylim(len(words), 0) + axis.set_xticks([]) + axis.set_yticks([]) + axis.set_xlabel("") + axis.set_ylabel("") + axis.grid(False) + axis.set_frame_on(False) + for spine in axis.spines.values(): + spine.set_visible(False) + axis.text( + 0.0, + 1.025, + f"{title}（列为{row_name}；有效源行的词内权重和为 1）", + transform=axis.transAxes, + ha="left", + va="bottom", + fontsize=11, + clip_on=False, + ) + for word_index, word in enumerate(words): + axis.text( + -0.012, + word_index + 0.5, + word, + transform=axis.get_yaxis_transform(), + ha="right", + va="center", + fontsize=tick_size, + clip_on=False, + ) + + # Place actual transcript words along the source-time axis using the + # center of each stored CTC word interval. + text_axis.set_xlim(0.0, duration_s) + text_axis.set_ylim(0.0, 1.0) + text_axis.set_xticks([]) + text_axis.set_yticks([]) + text_axis.set_frame_on(False) + for spine in text_axis.spines.values(): + spine.set_visible(False) + for center, word, valid in zip(text_centers, words, text_valid): + if valid: + text_axis.text( + center, + 0.96, + word, + rotation=90, + ha="center", + va="top", + fontsize=tick_size, + clip_on=False, + ) + text_axis.grid(False) + + fig.subplots_adjust(left=0.17, right=0.88, top=0.91, bottom=0.08) + colorbar = fig.colorbar(meshes[0], ax=heat_axes, fraction=0.025, pad=0.02) + colorbar.ax.set_title("重叠\n权重", fontsize=8, pad=8) + sample_id = record["sample_id"] + fig.suptitle( + f"词到原始音频/视频位置查询矩阵｜样本 {sample_id}", + fontsize=14, + y=0.97, + ) + fig.text( + 0.17, + 0.02, + "横轴为真实源时间 (s)，每个文本标注位于对应词区间中心。颜色表示每个词内归一化的物理时间交叠权重，不是学习得到的内容相似度。", + fontsize=8, + ha="left", + ) + + output = args.output or (Q1_DIR / "results" / "alignment_query_example.png") + output = output.resolve() + output.parent.mkdir(parents=True, exist_ok=True) + fig.savefig(output, dpi=220, facecolor="white") + plt.close(fig) + + metadata = { + "sample_id": sample_id, + "selection": "manually selected example with valid audio and vision query maps", + "duration_s": duration_s, + "word_count": len(words), + "words": words, + "audio_query_shape": list(audio_map.shape), + "audio_query_nnz": int(audio_map.nnz), + "audio_query_mapped_words": int(np.count_nonzero(np.asarray(audio_map.sum(axis=1)).reshape(-1))), + "vision_query_shape": list(vision_map.shape), + "vision_query_nnz": int(vision_map.nnz), + "vision_query_mapped_words": int(np.count_nonzero(np.asarray(vision_map.sum(axis=1)).reshape(-1))), + "audio_query_feature_validity_channel": "log_energy (audio feature dimension 66)", + "vision_query_feature_validity_channel": "OpenFace AU12 intensity (vision feature dimension 10)", + "alignment_semantics": "per-word normalized overlap between stored CTC word intervals and native source intervals; no learned content similarity", + "coordinate_axes_shown": False, + "color_scale": "shared square-root intensity transform for visibility; original overlap weights retained", + "word_label_positions": "actual transcript labels placed at their CTC word-interval centers on the source-time axis", + "image": str(output), + } + metadata_path = output.with_suffix(".json") + metadata_path.write_text(json.dumps(metadata, ensure_ascii=False, indent=2) + "\n", encoding="utf-8") + print(json.dumps(metadata, ensure_ascii=False, indent=2)) + + +if __name__ == "__main__": + main() diff --git a/math/Q1/问题一.pdf b/math/Q1/问题一.pdf deleted file mode 100644 index eda1efb..0000000 Binary files a/math/Q1/问题一.pdf and /dev/null differ diff --git a/math/Q2/README.md b/math/Q2/README.md new file mode 100644 index 0000000..e4577e5 --- /dev/null +++ b/math/Q2/README.md @@ -0,0 +1,62 @@ +# Q2：连续局部缺失下的概率补全与可靠度门控 + +实现和输入审计范围只覆盖 `math/Q2`。Q2 遵循附件二 `aligned_50.pkl` 的官方 train/valid/test 划分，按来源 `video_id` 核验组间隔离；Q1 的五折探针不替代 Q2 的官方测试。附件三只输出无标签预测与审计，不计算准确率或 F1。 + +完整的 V2 算法核查、Accuracy 口径和正式运行指标见 [`V2_REVIEW.md`](V2_REVIEW.md)。 + +## 运行 + +复用 Q1 的 `uv` 环境： + +```bash +uv run --project math/Q1 python math/Q2/train.py +``` + +默认最多训练 12 个 epoch，状态空间补全器训练 8 个 epoch，batch size 64，patience 3；默认使用可用 CUDA。运行需要本机缓存 `google-bert/bert-base-uncased` 权重。快速接口冒烟参数示例： + +```bash +uv run --project math/Q1 python math/Q2/train.py --epochs 1 --imputer-epochs 1 --bootstrap-repeats 100 +``` + +## 按论文构建的模型 + +- **输入与隔离：** 只读取官方对齐 50 步特征，不把原始文本、非对齐文件或标签送入补全器。来源文件明确约定的全零模态行用于缺失判定；重复主键、非有限特征、非法标签或正负/中性标签不一致会直接报错。拟合、可靠度内层验证和温度校准三部分按视频组互斥。 +- **共享/私有动态补全：** 共享状态 8 维、各模态私有状态 4 维，模态发射矩阵对其他私有状态固定为零。正定初始/过程/发射噪声和谱范数受限转移矩阵；训练只用 proper-train 拟合标准化器和完整观测高斯边际似然（含 log-determinant）。信息形式滤波与 RTS 平滑形成时空联合后验；先抽联合潜状态轨迹，再抽缺失发射噪声，观测行原样保留。补全器在教师/学生训练前冻结。 +- **可靠度与时序：** 质量字段不可用时只对当前可见行取 `q*=1` 并标记未知；人工遮蔽位置不透传原质量。缺失可靠度由 ρimp 和非负不确定度/前后距离/缺口长度系数构成；系数在独立的训练组内层验证集上从候选组中选择后固定。BiGRU 按方向衰减历史状态，重置门先作用于隐藏状态再进入候选映射，更新门再乘可靠度。 +- **跨模态与最终融合：** 单层跨时间来源注意力采用有界内容分数、每个来源的均匀基准质量和正质量空来源；最终融合使用 `rho × bounded content` 权重与正先验专家。低秩秩 4 CP 残差减去全零输入常数并可关闭。 +- **输出分布：** 三类极性概率加精确中性零点质量；负/正幅度各用 Beta 分布，共享类别内集中度。先按联合轨迹混合类别概率与条件 Beta，再对最终类别概率做独立温度校准；预测类别并列时中性优先，中性分数严格为 0，非中性输出对应类别条件混合中位数。 +- **损失和消融：** 混合区间概率负对数加缩放 Huber；教师使用自然可见视图并冻结，C7 蒸馏与 C7 平滑最坏组风险分开训练；隐藏可观测片段的辅助重建按模态归一化。内层组外固定情景用于早停和可靠度/组风险候选选择；官方验证集用于 C0–C7 结构选择，测试集不参与调参。另训练 C6 的无距离惩罚、无辅助重建、独立点遮蔽三项单因素诊断，不参与最终模型挑选。 + +输入 `aligned_50.pkl` 不提供逐行质量分数或质量可用标记，因此只能按 PDF 的回退规定令可见行 `q*=1, J_Q=0`，即 `R_eff=R`。质量–噪声映射在当前数据上没有可识别变化，故不伪造一项训练对照；实现及限制写入运行清单。 + +## 缺失控制与指标 + +训练遮蔽率为 0、0.1、0.3、0.5、0.7，覆盖单模态、同步、部分重叠、异步连续缺口，保留每个被遮蔽模态至少 20% 原始观测。验证集预先固定同一组遮蔽实例供所有模型比较，包括模态组合、开头/中段/末尾、单长段/多短段和同步程度。自然、额外及最终缺失率按 T/A/V 分别计算后等权汇总，并记录同步无观测率。按缺失率曲线计算归一化 AURC-MAE；逐情景和 AURC 差值均使用相同的视频组重采样。官方 50 步输入不含可审计的语义边界索引，学生也不得读原文，因此不伪造否定词/转折词位置实验。 + +准确率、Macro-F1、MAE、RMSE、Pearson、各类召回与支持数、Brier、分类 NLL、ECE，以及 90% 预测区间覆盖率/宽度均按一致解码报告。视频组 Bootstrap 用于最终测试区间和验证集模型配对差值；轨迹内方差与轨迹间均值方差分别记录。附件三全无可见观测时退回训练集平滑类别先验与按类别拟合的幅度先验，并保留低信息标记。 + +## 输出 + +结果写入 `math/Q2/results/`： + +- `crg_student.pt`、`teacher.pt`、`structured_imputer.pt`、`preprocessor.npz`：推理所需权重与训练折尺度。 +- `ablation_validation.csv`、`reliability_hparam_tuning.csv`、`group_risk_tuning.csv`：C0–C7 与单因素诊断、内层可靠度和 C7 组风险参数选择。 +- `validation_metrics.json`、`test_metrics.json`、`test_predictions.csv`：正式验证/测试指标、点预测、概率、区间和方差分解。 +- `test_gate_diagnostics.csv`：按测试样本、时间位置和模态记录路径平均融合权重、可靠度、补全不确定性、缺口/跨度与时间池化权重。 +- `q2_diagnostics.png`、`q2_gate_positions.png`：缺失率曲线、模态/位置热图、混淆矩阵、情感强度散点、区间覆盖和逐位置融合门控摘要。 +- `group_bootstrap_ci.csv`、`validation_group_bootstrap_deltas.csv`：来源视频组区间及模型配对差值。 +- `controlled_missingness.csv`、`controlled_mask_audit.csv`、`controlled_group_bootstrap.csv`：逐场景指标、等权缺失率、逐样本半开区间/遮蔽种子、视频组置信区间、配对差值和 AURC-MAE。 +- `training_history.csv`、`run_manifest.json`：优化轨迹、数据哈希、数据划分、可靠度设置和运行参数。 +- `attachment3_predictions.csv`、`attachment3_audit.csv`：30 条无标签预测、区间与输入/低信息审计。 + +单独重跑附件三推理： + +```bash +uv run --project math/Q1 python math/Q2/predict_attachment3.py +``` + +从已生成的 CSV 重画诊断图： + +```bash +uv run --project math/Q1 python math/Q2/plot_diagnostics.py +``` diff --git a/math/Q2/V2_REVIEW.md b/math/Q2/V2_REVIEW.md new file mode 100644 index 0000000..d70f25e --- /dev/null +++ b/math/Q2/V2_REVIEW.md @@ -0,0 +1,58 @@ +# E 题 V2：Q1/Q2 算法与结果复核 + +复核日期：2026-09-25。范围仅包括 `math/`。 + +## Q1 五折探针与 Accuracy + +Q1 使用 100 个特征样本，按 `video_id` 做五折 `GroupKFold`；缩放器在每折训练部分拟合，表中为每个样本恰好一次的 out-of-fold（OOF）预测。 + +Accuracy 是三类情感极性分类的正确率，类别由情感值符号确定：负值为 negative、零值为 neutral、正值为 positive。它不是词/时间边界准确率；数据没有人工对齐边界真值，因此没有报告边界准确率。此前回复漏列了 Accuracy，但 `comparison_summary.csv` 和本目录报告一直都包含该项。 + +| 分支 | OOF Accuracy | OOF Macro-F1 | OOF MAE | +|---|---:|---:|---:| +| B0 | 0.5900 | 0.3373 | 0.5345 | +| B1 | 0.5700 | 0.3084 | 0.5342 | +| B2 | 0.5500 | 0.2769 | 0.5308 | +| B3 | 0.5700 | 0.3084 | 0.5202 | +| B4 | 0.6000 | 0.3882 | 0.5393 | + +## Q2 V2 实现核查 + +- 使用附件二官方 train/valid/test 拆分；样本数分别为 3395/728/727，来源 `video_id` 组数为 1528/239/381，官方拆分间重叠为 0。训练拟合、可靠度选择和温度校准也在训练集内按视频组互斥。 +- 结构化高斯补全器按 8 维共享状态、每模态 4 维私有状态构建；训练只拟合训练子集的标准化器和观测高斯边际似然，补全器在教师/学生训练前冻结。观测行在后验采样中保持原样。 +- 输入没有逐行质量分数/质量可用标记，因此按论文回退规则处理：可见行 `q*=1, J_Q=0`，即 `R_eff=R`。质量到噪声映射在这份输入中不可识别，没有伪造该消融。 +- 缺失训练覆盖 0/0.1/0.3/0.5/0.7，包含单模态、同步、部分重叠和异步连续片段，并保留被遮蔽模态至少 20% 的原始观测。验证控制掩码预先固定；等权 T/A/V 统计自然、附加和最终缺失率。 +- 执行 C0–C7 结构消融，以及无距离/跨度惩罚、无辅助重构、点掩码三个独立诊断。C7 蒸馏与平滑组风险分开；组风险在训练组内固定留出上联合选择，最终选出的候选为 `λ_G=0.10, τ=0.05`。 +- 训练阶段使用 4 条联合轨迹，评估/推理使用 16 条；极性概率与正负 Beta 幅度先混合，再做温度校准。neutral 具有精确零点质量，预测并列优先 neutral。 +- 全量正式运行使用 12 轮上限、补全器 8 轮、batch 64、patience 3、种子 20260924、RTX 5070 Ti；官方验证选择 C5，温度为 1.2127。最终测试集只评估一次，不用于调参。 +- 已完成 42 个缺失控制情景；控制审计 30,576 行，模型情景指标 504 行，1000 次来源视频组配对 Bootstrap 结果 2,568 行，测试门控逐样本/步/模态诊断 109,050 行。 +- 附件三产生 30 条无标签预测，并验证唯一 ID、情感符号与类别一致、概率和为 1、分值范围与区间合法。附件三没有标签，不报告 Accuracy/F1。 + +## Q2 正式结果 + +| 指标 | 官方验证集 | 官方测试集 | +|---|---:|---:| +| Accuracy | 0.6168 | 0.6740 | +| Macro-F1 | 0.5472 | 0.5861 | +| MAE | 0.6615 | 0.6980 | +| RMSE | 0.8930 | 0.9674 | +| Pearson | 0.6176 | 0.6300 | +| 90% 区间覆盖率 | 0.8929 | 0.8968 | +| 90% 区间平均宽度 | 2.3819 | 2.4824 | + +测试集分类支持数为 negative 207、neutral 158、positive 362。指标和按来源视频组的置信区间见 `results/test_metrics.json` 与 `results/group_bootstrap_ci.csv`；缺失鲁棒性曲线及区间见 `results/controlled_missingness.csv`、`results/controlled_group_bootstrap.csv`。 + +| 遮挡模式 | C5 AURC-MAE | 相对 C0 差值 | 95% 视频组 Bootstrap 区间 | +|---|---:|---:|---:| +| 单模态 | 0.6696 | -0.0758 | [-0.1118, -0.0389] | +| 同步 | 0.6890 | -0.0758 | [-0.1105, -0.0417] | +| 部分重叠 | 0.6883 | -0.0774 | [-0.1146, -0.0429] | +| 异步 | 0.6880 | -0.0894 | [-0.1261, -0.0554] | + +## 产物与已修复问题 + +`results/ablation_validation.csv` 含 C0–C7 和三项诊断，共 12 个模型行；诊断图为 `q2_diagnostics.png` 与 `q2_gate_positions.png`。正式训练已完成模型比较、测试预测、逐场景评估和组 Bootstrap。 + +首次附件三导出暴露 Beta 参数索引少一维的问题。已修复为分别读取路径、样本、极性、Beta 参数四个轴，并通过独立脚本从已保存检查点重新生成 30 条预测及审计。结果清单同步为本次 12/8 轮正式运行参数。`predict_attachment3.py` 可安全重复执行并从当前验证/测试结果更新清单。 + +仍无法用现有数据验证人工对齐边界误差、逐行质量映射效果、否定/转折语义边界效果或附件三预测准确率；这些数据标签/字段并不存在。 diff --git a/math/Q2/crg.py b/math/Q2/crg.py new file mode 100644 index 0000000..bb6ae36 --- /dev/null +++ b/math/Q2/crg.py @@ -0,0 +1,556 @@ +"""Structured Gaussian imputation and reliability-aware CRG sequence model.""" +from __future__ import annotations + +import math +from typing import Sequence + +import torch +from torch import nn +from torch.nn import functional as F + +MODALITIES = ("text", "audio", "vision") +INPUT_DIMS = (768, 74, 35) +HIDDEN = 32 +SHARED_STATE = 8 +PRIVATE_STATE = 4 +STATE_DIM = SHARED_STATE + len(MODALITIES) * PRIVATE_STATE + + +def _inv_softplus(value: float) -> float: + return math.log(math.expm1(value)) + + +class StructuredGaussianImputer(nn.Module): + """Linear-Gaussian shared/private state model with exact block-Gaussian inference. + + The state is [shared(8), text-private(4), audio-private(4), vision-private(4)]. + Each modality emits from the shared state and its own private state only. The + filtering likelihood uses the matrix determinant lemma, retaining its log-det + normalization without forming a covariance matrix in observation space. + """ + + def __init__(self, input_dims: Sequence[int] = INPUT_DIMS) -> None: + super().__init__() + self.input_dims = tuple(int(x) for x in input_dims) + self.state_dim = STATE_DIM + transition_mask = torch.zeros(STATE_DIM, STATE_DIM) + blocks = [slice(0, SHARED_STATE)] + [ + slice(SHARED_STATE + i * PRIVATE_STATE, SHARED_STATE + (i + 1) * PRIVATE_STATE) + for i in range(len(MODALITIES)) + ] + for block in blocks: + transition_mask[block, block] = 1.0 + self.register_buffer("transition_mask", transition_mask) + self.transition_raw = nn.Parameter(0.8 * torch.eye(STATE_DIM)) + self.mu0 = nn.Parameter(torch.zeros(STATE_DIM)) + self.pi0_raw = nn.Parameter(torch.full((STATE_DIM,), _inv_softplus(1.0))) + self.q_raw = nn.Parameter(torch.full((STATE_DIM,), _inv_softplus(0.08))) + self.emission_raw = nn.ParameterList() + self.biases = nn.ParameterList() + self.r_raw = nn.ParameterList() + for index, dim in enumerate(self.input_dims): + mask = torch.zeros(dim, STATE_DIM) + mask[:, :SHARED_STATE] = 1.0 + private_start = SHARED_STATE + index * PRIVATE_STATE + mask[:, private_start:private_start + PRIVATE_STATE] = 1.0 + self.register_buffer(f"emission_mask_{index}", mask) + self.emission_raw.append(nn.Parameter(torch.randn(dim, STATE_DIM) * 0.025)) + self.biases.append(nn.Parameter(torch.zeros(dim))) + self.r_raw.append(nn.Parameter(torch.full((dim,), _inv_softplus(0.5)))) + + def _transition(self) -> torch.Tensor: + matrix = self.transition_raw * self.transition_mask + norm = torch.linalg.matrix_norm(matrix, ord=2).clamp_min(1e-8) + return matrix * torch.clamp(0.98 / norm, max=1.0) + + def _covariances(self) -> tuple[torch.Tensor, torch.Tensor]: + eye = torch.eye(self.state_dim, device=self.mu0.device, dtype=self.mu0.dtype) + p0 = torch.diag(F.softplus(self.pi0_raw) + 1e-4) + 1e-5 * eye + q = torch.diag(F.softplus(self.q_raw) + 1e-4) + 1e-5 * eye + return p0, q + + def emissions(self) -> list[torch.Tensor]: + return [raw * getattr(self, f"emission_mask_{i}") for i, raw in enumerate(self.emission_raw)] + + def _filter( + self, + xs: Sequence[torch.Tensor], + observed: torch.Tensor, + *, + calculate_log_likelihood: bool, + retain_states: bool, + ) -> tuple[torch.Tensor | None, dict[str, list[torch.Tensor]] | None]: + # xs[m]: [B,T,Dm], observed: [B,T,3] + batch, steps, _ = observed.shape + transition = self._transition() + p0, process_noise = self._covariances() + emissions = self.emissions() + noise = [F.softplus(x) + 1e-4 for x in self.r_raw] + mu_prior = self.mu0.expand(batch, -1) + p_prior = p0.expand(batch, -1, -1) + total_nll = torch.zeros(batch, device=observed.device, dtype=mu_prior.dtype) + prior_means: list[torch.Tensor] = [] + prior_covs: list[torch.Tensor] = [] + filtered_means: list[torch.Tensor] = [] + filtered_covs: list[torch.Tensor] = [] + + for t in range(steps): + if retain_states: + prior_means.append(mu_prior) + prior_covs.append(p_prior) + p_chol = torch.linalg.cholesky(p_prior + 1e-6 * torch.eye(self.state_dim, device=p_prior.device)) + p_inv = torch.cholesky_inverse(p_chol) + information_parts: list[torch.Tensor] = [] + vector_parts: list[torch.Tensor] = [] + quadratic_parts: list[torch.Tensor] = [] + logdet_r = torch.zeros(batch, device=p_prior.device, dtype=p_prior.dtype) + n_observed = torch.zeros_like(logdet_r) + for m, (x, emission, variance) in enumerate(zip(xs, emissions, noise)): + active = observed[:, t, m].to(dtype=mu_prior.dtype) + weights = active[:, None] / variance[None, :] + centered = x[:, t] - self.biases[m] + residual = centered - mu_prior @ emission.T + information_parts.append(torch.einsum("di,bd,dj->bij", emission, weights, emission)) + vector_parts.append((residual * weights) @ emission) + quadratic_parts.append((residual.square() * weights).sum(dim=-1)) + logdet_r = logdet_r + active * torch.log(variance).sum() + n_observed = n_observed + active * x.shape[-1] + information = torch.stack(information_parts).sum(dim=0) + innovation = torch.stack(vector_parts).sum(dim=0) + precision = p_inv + information + precision_chol = torch.linalg.cholesky(precision + 1e-6 * torch.eye(self.state_dim, device=precision.device)) + p_filtered = torch.cholesky_inverse(precision_chol) + mu_filtered = mu_prior + torch.einsum("bij,bj->bi", p_filtered, innovation) + if calculate_log_likelihood: + logdet_p = 2.0 * torch.log(torch.diagonal(p_chol, dim1=-2, dim2=-1)).sum(dim=-1) + logdet_precision = 2.0 * torch.log(torch.diagonal(precision_chol, dim1=-2, dim2=-1)).sum(dim=-1) + quad = torch.stack(quadratic_parts).sum(dim=0) + correction = torch.einsum("bi,bij,bj->b", innovation, p_filtered, innovation) + log_likelihood = logdet_r + logdet_p + logdet_precision + (quad - correction).clamp_min(0.0) + log_likelihood = log_likelihood + n_observed * math.log(2.0 * math.pi) + total_nll = total_nll + 0.5 * log_likelihood + if retain_states: + filtered_means.append(mu_filtered) + filtered_covs.append(p_filtered) + mu_prior = mu_filtered @ transition.T + p_prior = transition @ p_filtered @ transition.T + process_noise + + states = None + if retain_states: + states = { + "prior_mean": prior_means, + "prior_cov": prior_covs, + "filtered_mean": filtered_means, + "filtered_cov": filtered_covs, + "transition": [transition], + } + return (total_nll if calculate_log_likelihood else None), states + + def observed_nll(self, xs: Sequence[torch.Tensor], observed: torch.Tensor) -> torch.Tensor: + """Exact observed-data Gaussian NLL, including covariance log determinants.""" + nll, _ = self._filter(xs, observed, calculate_log_likelihood=True, retain_states=False) + assert nll is not None + return nll + + @staticmethod + def _draw(mean: torch.Tensor, covariance: torch.Tensor, paths: int) -> torch.Tensor: + chol = torch.linalg.cholesky(covariance + 1e-5 * torch.eye(covariance.shape[-1], device=covariance.device)) + noise = torch.randn((paths, *mean.shape), dtype=mean.dtype, device=mean.device) + return mean.unsqueeze(0) + torch.einsum("bij,kbj->kbi", chol, noise) + + @torch.no_grad() + def complete( + self, + xs: Sequence[torch.Tensor], + observed: torch.Tensor, + paths: int, + *, + joint_draws: bool, + ) -> tuple[list[torch.Tensor], list[torch.Tensor]]: + """RTS smooth, draw joint latent trajectories, then draw missing emissions.""" + _, stored = self._filter(xs, observed, calculate_log_likelihood=False, retain_states=True) + assert stored is not None + fm, fc = stored["filtered_mean"], stored["filtered_cov"] + pm, pc = stored["prior_mean"], stored["prior_cov"] + transition = stored["transition"][0] + steps = len(fm) + smoother_gains: list[torch.Tensor] = [torch.empty(0, device=observed.device)] * max(0, steps - 1) + smooth_cov: list[torch.Tensor] = [torch.empty(0, device=observed.device)] * steps + smooth_cov[-1] = fc[-1] + for t in range(steps - 2, -1, -1): + next_chol = torch.linalg.cholesky(pc[t + 1] + 1e-6 * torch.eye(self.state_dim, device=observed.device)) + gain = torch.cholesky_solve((fc[t] @ transition.T).transpose(-1, -2), next_chol).transpose(-1, -2) + smoother_gains[t] = gain + smooth_cov[t] = fc[t] + gain @ (smooth_cov[t + 1] - pc[t + 1]) @ gain.transpose(-1, -2) + smooth_cov[t] = 0.5 * (smooth_cov[t] + smooth_cov[t].transpose(-1, -2)) + + if joint_draws: + state = torch.empty((paths, observed.shape[0], steps, self.state_dim), device=observed.device, dtype=fm[0].dtype) + state[:, :, -1] = self._draw(fm[-1], fc[-1], paths) + for t in range(steps - 2, -1, -1): + gain = smoother_gains[t] + conditional_mean = fm[t].unsqueeze(0) + torch.einsum( + "bij,kbj->kbi", gain, state[:, :, t + 1] - pm[t + 1].unsqueeze(0) + ) + conditional_cov = fc[t] - gain @ pc[t + 1] @ gain.transpose(-1, -2) + conditional_cov = 0.5 * (conditional_cov + conditional_cov.transpose(-1, -2)) + chol = torch.linalg.cholesky(conditional_cov + 1e-5 * torch.eye(self.state_dim, device=observed.device)) + eps = torch.randn_like(conditional_mean) + state[:, :, t] = conditional_mean + torch.einsum("bij,kbj->kbi", chol, eps) + else: + means = torch.stack(fm, dim=1) + covs = torch.stack(smooth_cov, dim=1) + smoothed_means = [fm[-1]] * steps + smoothed_means[-1] = fm[-1] + for t in range(steps - 2, -1, -1): + smoothed_means[t] = fm[t] + torch.einsum( + "bij,bj->bi", smoother_gains[t], smoothed_means[t + 1] - pm[t + 1] + ) + state = torch.stack(smoothed_means, dim=1).unsqueeze(0).expand(paths, -1, -1, -1) + + completed: list[torch.Tensor] = [] + variances: list[torch.Tensor] = [] + for m, (x, emission) in enumerate(zip(xs, self.emissions())): + mean = torch.einsum("kbti,di->kbtd", state, emission) + self.biases[m] + if joint_draws: + noise = torch.randn_like(mean) * torch.sqrt(F.softplus(self.r_raw[m]) + 1e-4) + draws = mean + noise + else: + draws = mean + visible = observed[:, :, m].unsqueeze(0).unsqueeze(-1) + completed.append(torch.where(visible, x.unsqueeze(0), draws)) + projected_cov = torch.einsum("di,btij,dj->btd", emission, torch.stack(smooth_cov, dim=1), emission) + variance = projected_cov + (F.softplus(self.r_raw[m]) + 1e-4) + variances.append(torch.where(observed[:, :, m, None], torch.zeros_like(variance), variance.clamp_min(1e-6))) + return completed, variances + + +class ReliabilityGRU(nn.Module): + """One-layer BiGRU with directional time decay and rho-scaled updates.""" + + def __init__(self, input_dim: int, hidden: int = 16) -> None: + super().__init__() + self.hidden = hidden + self.x_proj = nn.Linear(input_dim, 3 * hidden) + self.h_proj = nn.Linear(hidden, 2 * hidden, bias=False) + self.candidate_h = nn.Linear(hidden, hidden, bias=False) + self.decay_raw = nn.Parameter(torch.full((hidden,), -3.0)) + + def _one_direction( + self, + x: torch.Tensor, + rho: torch.Tensor, + distance: torch.Tensor, + reverse: bool, + reliability_update: bool, + ) -> torch.Tensor: + batch, steps, _ = x.shape + state = torch.zeros(batch, self.hidden, dtype=x.dtype, device=x.device) + x_parts = self.x_proj(x).chunk(3, dim=-1) + output: list[torch.Tensor | None] = [None] * steps + indices = range(steps - 1, -1, -1) if reverse else range(steps) + for t in indices: + if reliability_update: + decay = torch.exp(-F.softplus(self.decay_raw)[None, :] * distance[:, t:t + 1]) + decayed_state = decay * state + else: + decayed_state = state + hz, hr = self.h_proj(decayed_state).chunk(2, dim=-1) + z = torch.sigmoid(x_parts[0][:, t] + hz) + r = torch.sigmoid(x_parts[1][:, t] + hr) + candidate = torch.tanh(x_parts[2][:, t] + self.candidate_h(r * decayed_state)) + effective_z = rho[:, t:t + 1] * z if reliability_update else z + state = (1.0 - effective_z) * decayed_state + effective_z * candidate + output[t] = state + return torch.stack([v for v in output if v is not None], dim=1) + + def forward( + self, + x: torch.Tensor, + rho: torch.Tensor, + dminus: torch.Tensor, + dplus: torch.Tensor, + reliability_update: bool, + ) -> torch.Tensor: + if not reliability_update: + rho = torch.ones_like(rho) + return torch.cat(( + self._one_direction(x, rho, dminus, False, reliability_update), + self._one_direction(x, rho, dplus, True, reliability_update), + ), dim=-1) + + +class CRG(nn.Module): + """Quality-aware multimodal sequence predictor for a configured ablation.""" + + def __init__( + self, + imputer: StructuredGaussianImputer | None = None, + input_dims: Sequence[int] = INPUT_DIMS, + *, + use_imputer: bool = True, + use_joint_draws: bool = True, + use_final_gate: bool = True, + use_source_attention: bool = True, + reliability_update: bool = True, + use_low_rank: bool = True, + reliability_hparams: tuple[float, float, float, float] = (0.5, 0.05, 0.05, 0.05), + ) -> None: + super().__init__() + self.use_imputer = use_imputer + self.use_joint_draws = use_joint_draws + self.use_final_gate = use_final_gate + self.use_source_attention = use_source_attention + self.reliability_update = reliability_update + self.use_low_rank = use_low_rank + self.imputer = imputer if imputer is not None else StructuredGaussianImputer(input_dims) + self.projections = nn.ModuleList( + nn.Sequential(nn.Linear(d, HIDDEN), nn.LayerNorm(HIDDEN), nn.GELU()) for d in input_dims + ) + recurrent_input = HIDDEN + 13 + self.temporal = nn.ModuleList(ReliabilityGRU(recurrent_input, 16) for _ in MODALITIES) + rho_imp, lambda_u, lambda_gap, lambda_span = reliability_hparams + if not 0.0 < rho_imp < 1.0 or min(lambda_u, lambda_gap, lambda_span) < 0.0: + raise ValueError("reliability requires 0 tuple[torch.Tensor, torch.Tensor, torch.Tensor, torch.Tensor]: + # Time positions are valid sequence locations even when all three sources are missing. + batch, steps, modalities = observed.shape + device = observed.device + positions = torch.arange(steps, device=device).view(1, steps).expand(batch, -1) + previous = torch.full((batch, modalities), -1, device=device, dtype=torch.long) + before, before_edge = [], [] + for t in range(steps): + before_edge.append(previous < 0) + before.append(torch.where(previous < 0, torch.ones_like(previous, dtype=torch.float32), (t - previous).float() / max(1, steps - 1))) + previous = torch.where(observed[:, t], torch.full_like(previous, t), previous) + following = torch.full((batch, modalities), steps, device=device, dtype=torch.long) + after, after_edge = [None] * steps, [None] * steps + for t in range(steps - 1, -1, -1): + after_edge[t] = following >= steps + after[t] = torch.where(following >= steps, torch.ones_like(following, dtype=torch.float32), (following - t).float() / max(1, steps - 1)) + following = torch.where(observed[:, t], torch.full_like(following, t), following) + dminus = torch.stack(before, dim=1) + dplus = torch.stack([x for x in after if x is not None], dim=1) + edge_minus = torch.stack(before_edge, dim=1) + edge_plus = torch.stack([x for x in after_edge if x is not None], dim=1) + dminus = torch.where(observed, torch.zeros_like(dminus), dminus) + dplus = torch.where(observed, torch.zeros_like(dplus), dplus) + edge_minus = edge_minus & ~observed + edge_plus = edge_plus & ~observed + missing = ~observed + left_run = torch.zeros((batch, steps, modalities), device=device, dtype=torch.float32) + run = torch.zeros((batch, modalities), device=device, dtype=torch.float32) + for t in range(steps): + run = torch.where(missing[:, t], run + 1.0, torch.zeros_like(run)) + left_run[:, t] = run + right_run = torch.zeros_like(left_run) + run.zero_() + for t in range(steps - 1, -1, -1): + run = torch.where(missing[:, t], run + 1.0, torch.zeros_like(run)) + right_run[:, t] = run + span = torch.where(missing, (left_run + right_run - 1.0) / max(1, steps), torch.zeros_like(left_run)) + return dminus, dplus, span, torch.stack((edge_minus, edge_plus), dim=-1).float() + + def _reliability( + self, observed: torch.Tensor, uncertainty: torch.Tensor, + ) -> tuple[torch.Tensor, torch.Tensor, torch.Tensor, torch.Tensor, torch.Tensor, torch.Tensor, torch.Tensor]: + dminus, dplus, span, edges = self._gap_features(observed) + gap = torch.minimum(dminus, dplus) + gap = torch.where(observed, torch.zeros_like(gap), gap) + u = torch.where(observed, torch.zeros_like(uncertainty), uncertainty).clamp_min(0.0) + qstar = observed.float() # External Q2 quality is unavailable: q*=1 only for visible rows; J=0. + rho_missing = self.rho_imp.clamp(1e-4, 0.999) * torch.exp( + -self.rel_u[None, None, :] * u + -self.rel_gap[None, None, :] * gap + -self.rel_span[None, None, :] * span + ) + rho = torch.where(observed, qstar, rho_missing).clamp(1e-4, 1.0) + return rho, u, gap, span, dminus, dplus, torch.cat((qstar.unsqueeze(-1), torch.zeros_like(qstar).unsqueeze(-1), edges), dim=-1) + + def _cross_source(self, hidden: torch.Tensor, rho: torch.Tensor) -> torch.Tensor: + # hidden [B,T,M,H]; each query reads every legal time in each other source. + batch, steps, modalities, width = hidden.shape + outputs = [] + q = self.query(hidden) + k = self.key(hidden) + v = torch.tanh(self.value(hidden)) + loc = torch.arange(steps, device=hidden.device) + relative_index = (loc[None, :] - loc[:, None] + 49).clamp(0, 98) + relative = self.relative_bias(relative_index).squeeze(-1) + for target in range(modalities): + numerator = torch.zeros((batch, steps, width), device=hidden.device, dtype=hidden.dtype) + denominator = torch.ones((batch, steps, 1), device=hidden.device, dtype=hidden.dtype) + for source in range(modalities): + if source == target: + continue + raw = torch.matmul(q[:, :, target], k[:, :, source].transpose(-1, -2)) / math.sqrt(width) + scores = 2.0 * torch.tanh(raw + relative) + base = 1.0 / (max(1, modalities - 1) * steps) + weights = base * rho[:, None, :, source] * torch.exp(scores.clamp(-2.0, 2.0)) + numerator = numerator + torch.matmul(weights, v[:, :, source]) + denominator = denominator + weights.sum(dim=-1, keepdim=True) + context = numerator / denominator + eta = torch.sigmoid(self.cross_eta_logit) + outputs.append(torch.tanh(self.cross_base(hidden[:, :, target]) + eta * self.cross_out(context))) + return torch.stack(outputs, dim=2) + + def _low_rank_residual(self, gated: torch.Tensor) -> torch.Tensor: + # Linear CP factors use [1; z_m] and subtract their constant all-zero term. + batch, steps, modalities, width = gated.shape + one = torch.ones((batch, steps, 1), device=gated.device, dtype=gated.dtype) + products = torch.ones((batch, steps, 4), device=gated.device, dtype=gated.dtype) + constant = torch.ones(4, device=gated.device, dtype=gated.dtype) + for m in range(modalities): + factor = self.cp_factors[m](torch.cat((one, gated[:, :, m]), dim=-1)) + products = products * factor + zero_input = torch.zeros((1, 1, width + 1), device=gated.device, dtype=gated.dtype) + zero_input[..., 0] = 1.0 + constant = constant * self.cp_factors[m](zero_input)[0, 0] + residual = (products - constant) @ self.cp_output + return torch.sigmoid(self.low_rank_eta_logit) * self.low_rank_output(torch.tanh(residual)) + + def forward( + self, + xs: Sequence[torch.Tensor], + observed_mask: torch.Tensor, + *, + paths: int = 4, + joint_draws: bool | None = None, + ) -> dict[str, torch.Tensor | list[torch.Tensor]]: + batch, steps, modalities = observed_mask.shape + if joint_draws is None: + joint_draws = self.use_joint_draws + if self.use_imputer: + completed, variance = self.imputer.complete(xs, observed_mask, paths, joint_draws=joint_draws) + else: + completed = [torch.where(observed_mask[:, :, m, None], x, torch.zeros_like(x)).unsqueeze(0) for m, x in enumerate(xs)] + variance = [torch.zeros_like(x) for x in xs] + paths = completed[0].shape[0] + uncertainty_parts = [v.mean(dim=-1) for v in variance] + uncertainty = torch.stack(uncertainty_parts, dim=-1) + rho, u, gap, span, dminus, dplus, quality_fields = self._reliability(observed_mask, uncertainty) + position = torch.linspace(0.0, 1.0, steps, device=observed_mask.device, dtype=xs[0].dtype) + pe = torch.stack((torch.sin(2 * math.pi * position), torch.cos(2 * math.pi * position), + torch.sin(4 * math.pi * position), torch.cos(4 * math.pi * position)), dim=-1) + encoded_paths: list[torch.Tensor] = [] + reconstructed_paths: list[list[torch.Tensor]] = [] + logits_paths: list[torch.Tensor] = [] + beta_paths: list[torch.Tensor] = [] + fusion_weight_paths: list[torch.Tensor] = [] + null_weight_paths: list[torch.Tensor] = [] + time_pool_weight_paths: list[torch.Tensor] = [] + for path_index in range(paths): + enc = [projection(completed[m][path_index]) for m, projection in enumerate(self.projections)] + hmods, reconstruction = [], [] + for m, encoder in enumerate(self.temporal): + if self.use_final_gate or self.use_source_attention or self.reliability_update: + scalar = torch.cat((observed_mask[:, :, m:m + 1].float(), quality_fields[:, :, m], + torch.log1p(u[:, :, m:m + 1]), dminus[:, :, m:m + 1], + dplus[:, :, m:m + 1], span[:, :, m:m + 1], + pe.unsqueeze(0).expand(batch, -1, -1)), dim=-1) + else: + # C1/C2 receive only the visibility mask and legal position code. + scalar = torch.zeros((batch, steps, 13), dtype=pe.dtype, device=pe.device) + scalar[:, :, 0] = observed_mask[:, :, m].float() + scalar[:, :, -4:] = pe.unsqueeze(0) + # q*, J_Q, edge flags, directional gaps, uncertainty and span are explicit. + seq = torch.cat((enc[m], scalar), dim=-1) + h = encoder(seq, rho[:, :, m], dminus[:, :, m], dplus[:, :, m], self.reliability_update) + hmods.append(h) + reconstruction.append(self.reconstruction_heads[m](h)) + hidden = torch.stack(hmods, dim=2) + if self.use_source_attention: + enhanced = self._cross_source(hidden, rho) + else: + enhanced = hidden + if self.use_final_gate: + content = 2.0 * torch.tanh(self.content_score(enhanced).squeeze(-1)) + weights_unnorm = rho * torch.exp(content.clamp(-2.0, 2.0)) + denom = 1.0 + weights_unnorm.sum(dim=-1, keepdim=True) + alpha = weights_unnorm / denom + null_alpha = 1.0 / denom.squeeze(-1) + gated = enhanced * alpha.unsqueeze(-1) + fused = gated.sum(dim=2) + null_alpha.unsqueeze(-1) * self.null_expert + else: + if self.use_imputer: + alpha = torch.full_like(observed_mask.float(), 1.0 / modalities) + else: + alpha = observed_mask.float() / observed_mask.float().sum(dim=-1, keepdim=True).clamp_min(1.0) + null_alpha = torch.zeros((batch, steps), device=observed_mask.device, dtype=alpha.dtype) + fused = (enhanced * alpha.unsqueeze(-1)).sum(dim=2) + gated = enhanced * alpha.unsqueeze(-1) + if self.use_low_rank: + fused = fused + self._low_rank_residual(gated) + pool_logits = 2.0 * torch.tanh(self.pool_score(torch.tanh(self.pool_hidden(fused))).squeeze(-1)) + pool_weight = torch.softmax(pool_logits, dim=1) + pooled = (pool_weight.unsqueeze(-1) * fused).sum(dim=1) + missing_rate = 1.0 - observed_mask.float().mean(dim=1) + mean_rho = rho.mean(dim=1) if (self.use_final_gate or self.use_source_attention or self.reliability_update) else observed_mask.float().mean(dim=1) + max_gap = gap.max(dim=1).values + max_span = span.max(dim=1).values + edge_rate = self._gap_features(observed_mask)[3].mean(dim=1).reshape(batch, -1) + stats = torch.cat((missing_rate, mean_rho, max_gap, max_span, edge_rate), dim=-1) + representation = torch.cat((pooled, stats), dim=-1) + feature = self.head(representation) + logits_paths.append(self.classifier(feature)) + mean_fraction = torch.sigmoid(self.magnitude_mean(feature)).clamp(1e-4, 1.0 - 1e-4) + concentration = F.softplus(self.concentration_raw).clamp_min(1e-3) + alpha_beta = torch.stack((mean_fraction * concentration, (1.0 - mean_fraction) * concentration), dim=-1) + beta_paths.append(alpha_beta) + reconstructed_paths.append(reconstruction) + encoded_paths.append(hidden) + fusion_weight_paths.append(alpha) + null_weight_paths.append(null_alpha) + time_pool_weight_paths.append(pool_weight) + class_logits = torch.stack(logits_paths, dim=0) + beta_params = torch.stack(beta_paths, dim=0) + class_probs_by_path = torch.softmax(class_logits, dim=-1) + beta_mean = beta_params[..., 0] / beta_params.sum(dim=-1) + conditional_mean = 3.0 * (class_probs_by_path[..., 2] * beta_mean[..., 1] - class_probs_by_path[..., 0] * beta_mean[..., 0]) + return { + "class_logits": class_logits, + "class_probs_by_path": class_probs_by_path, + "class_probs": class_probs_by_path.mean(dim=0), + "tempered_probs_by_path": torch.softmax(class_logits / 2.0, dim=-1), + "beta_params": beta_params, + "beta_mean": beta_mean, + "mixed_score": conditional_mean.mean(dim=0), + "reconstructions": [torch.stack([reconstructed_paths[k][m] for k in range(paths)], dim=0) for m in range(modalities)], + "reliability": rho, + "imputation_uncertainty": uncertainty, + "gap": gap, + "span": span, + "distance_before": dminus, + "distance_after": dplus, + "fusion_weights_by_path": torch.stack(fusion_weight_paths, dim=0), + "null_weights_by_path": torch.stack(null_weight_paths, dim=0), + "time_pool_weights_by_path": torch.stack(time_pool_weight_paths, dim=0), + "low_rank_scale": torch.sigmoid(self.low_rank_eta_logit), + } diff --git a/math/Q2/data.py b/math/Q2/data.py new file mode 100644 index 0000000..9f6302f --- /dev/null +++ b/math/Q2/data.py @@ -0,0 +1,184 @@ +"""Restricted readers and split preparation for the official Q2 inputs.""" +from __future__ import annotations + +import pickle +from dataclasses import dataclass +from pathlib import Path +from typing import Any + +import numpy as np + +ROOT = Path(__file__).resolve().parents[2] +ALIGNED_PATH = ROOT / "E题数据" / "附件2-数据集特征文件" / "aligned_50.pkl" +ATTACHMENT3_ALIGNED = ROOT / "E题数据" / "附件3-模态缺失特征样本" / "对齐版本" +MODALITIES = ("text", "audio", "vision") +EXPECTED_DIMS = {"text": 768, "audio": 74, "vision": 35} + + +class RestrictedUnpickler(pickle.Unpickler): + """Allow only primitive containers and NumPy reconstruction primitives.""" + + _allowed = { + ("builtins", name): getattr(__import__("builtins"), name) + for name in ("set", "frozenset", "slice", "complex", "bytearray") + } + _allowed.update({ + ("collections", "OrderedDict"): __import__("collections").OrderedDict, + ("numpy", "ndarray"): np.ndarray, + ("numpy", "dtype"): np.dtype, + ("numpy", "asarray"): np.asarray, + ("numpy.core.multiarray", "_reconstruct"): np.core.multiarray._reconstruct, + ("numpy.core.multiarray", "scalar"): np.core.multiarray.scalar, + ("numpy._core.multiarray", "_reconstruct"): np.core.multiarray._reconstruct, + ("numpy._core.multiarray", "scalar"): np.core.multiarray.scalar, + }) + + def find_class(self, module: str, name: str) -> Any: + try: + return self._allowed[(module, name)] + except KeyError as exc: + raise pickle.UnpicklingError(f"blocked pickle global: {module}.{name}") from exc + + +def restricted_load(path: Path) -> Any: + with path.open("rb") as stream: + return RestrictedUnpickler(stream).load() + + +def _decode(value: Any) -> str: + if isinstance(value, bytes): + return value.decode("utf-8", errors="replace") + if isinstance(value, np.bytes_): + return bytes(value).decode("utf-8", errors="replace") + if isinstance(value, np.ndarray) and value.shape == (): + return _decode(value.item()) + return str(value) + + +def _one_dim(value: Any, dtype: Any | None = None) -> np.ndarray: + out = np.asarray(value) + if out.ndim > 1 and out.shape[-1] == 1: + out = out.reshape(-1) + elif out.ndim > 1 and out.shape[0] == 1: + out = out.reshape(-1) + else: + out = out.reshape(-1) + return out.astype(dtype) if dtype is not None else out + + +@dataclass +class SplitData: + name: str + x: dict[str, np.ndarray] + mask: np.ndarray + class_y: np.ndarray | None + regression_y: np.ndarray | None + ids: list[str] + groups: np.ndarray + + @property + def n(self) -> int: + return len(self.ids) + + +def _extract_split(name: str, obj: dict[str, Any], with_labels: bool) -> SplitData: + raw: dict[str, np.ndarray] = {} + masks = [] + for modality in MODALITIES: + arr = np.asarray(obj[modality]) + if arr.ndim != 3 or arr.shape[1] != 50 or arr.shape[2] != EXPECTED_DIMS[modality]: + raise ValueError(f"{name}.{modality}: unexpected feature shape {arr.shape}") + arr = arr.astype(np.float32) + if not np.isfinite(arr).all(): + raise ValueError(f"{name}.{modality}: non-finite feature values; refusing to reinterpret them as missing") + # The dataset documentation defines all-zero aligned rows as missing. + observed = np.any(arr != 0.0, axis=-1) + raw[modality] = arr + masks.append(observed) + mask = np.stack(masks, axis=-1) + ids = [_decode(v) for v in _one_dim(obj["id"])] + if len(ids) != len(mask): + raise ValueError(f"{name}: id count differs from feature count") + if len(set(ids)) != len(ids): + raise ValueError(f"{name}: duplicate video$_$clip primary keys") + malformed = [sample_id for sample_id in ids if "$_$" not in sample_id or not all(sample_id.split("$_$", 1))] + if malformed: + raise ValueError(f"{name}: malformed video$_$clip keys: {malformed[:5]}") + groups = np.asarray([sample_group(v) for v in ids], dtype=str) + if with_labels: + class_y = _one_dim(obj["classification_labels"], np.int64) + regression_y = _one_dim(obj["regression_labels"], np.float32) + if len(class_y) != len(ids) or len(regression_y) != len(ids): + raise ValueError(f"{name}: label count differs from feature count") + if not np.isfinite(regression_y).all() or np.any(np.abs(regression_y) > 3.0): + raise ValueError(f"{name}: regression labels must be finite and within [-3,3]") + if not np.isin(class_y, [0, 1, 2]).all(): + raise ValueError(f"{name}: expected class labels in 0,1,2") + expected_class = np.where(regression_y < 0.0, 0, np.where(regression_y == 0.0, 1, 2)) + mismatch = np.flatnonzero(class_y != expected_class) + if len(mismatch): + examples = [(ids[int(i)], int(class_y[i]), float(regression_y[i])) for i in mismatch[:5]] + raise ValueError(f"{name}: polarity/regression label mismatch (sample, class, score): {examples}") + else: + class_y = regression_y = None + return SplitData(name, raw, mask, class_y, regression_y, ids, groups) + + +def sample_group(sample_id: str) -> str: + """Official ids are video$_$clip; group on the source video only.""" + return sample_id.split("$_$", 1)[0] + + +def load_official_splits(path: Path = ALIGNED_PATH) -> dict[str, SplitData]: + obj = restricted_load(path) + required = {"train", "valid", "test"} + if not isinstance(obj, dict) or not required.issubset(obj): + raise ValueError("aligned_50.pkl must contain train, valid, and test dictionaries") + splits = {name: _extract_split(name, obj[name], with_labels=True) for name in ("train", "valid", "test")} + del obj + return splits + + +def load_attachment3_case(path: Path) -> dict[str, np.ndarray]: + obj = restricted_load(path) + case = obj.get("test", obj) + text_bert = np.asarray(case["text_bert"]) + audio = np.asarray(case["audio"]) + vision = np.asarray(case["vision"]) + if text_bert.ndim == 3 and text_bert.shape[0] == 1: + text_bert = text_bert[0] + if text_bert.shape != (3, 50): + raise ValueError(f"{path.name}: expected text_bert (1,3,50), got {np.asarray(case['text_bert']).shape}") + result = {"input_ids": text_bert[0].astype(np.int64), "attention_mask": text_bert[1].astype(bool), "token_type_ids": text_bert[2].astype(np.int64)} + for name, arr, dim in (("audio", audio, 74), ("vision", vision, 35)): + if arr.ndim == 3 and arr.shape[0] == 1: + arr = arr[0] + if arr.shape != (50, dim): + raise ValueError(f"{path.name}: expected {name} (1,50,{dim}), got {np.asarray(case[name]).shape}") + arr = arr.astype(np.float32) + if not np.isfinite(arr).all(): + raise ValueError(f"{path.name}: {name} contains non-finite features") + result[name] = arr + return result + + +def fit_preprocessor(train: SplitData) -> dict[str, dict[str, np.ndarray]]: + """Fit per-dimension mean/std on observed training rows only.""" + fitted: dict[str, dict[str, np.ndarray]] = {} + for j, name in enumerate(MODALITIES): + rows = train.x[name][train.mask[:, :, j]] + mean = rows.mean(axis=0, dtype=np.float64).astype(np.float32) + std = rows.std(axis=0, dtype=np.float64).astype(np.float32) + std[std < 1e-5] = 1.0 + fitted[name] = {"mean": mean, "std": std} + return fitted + + +def transform_split(split: SplitData, fitted: dict[str, dict[str, np.ndarray]]) -> dict[str, np.ndarray]: + output = {} + for j, name in enumerate(MODALITIES): + arr = (split.x[name] - fitted[name]["mean"]) / fitted[name]["std"] + arr = np.clip(arr, -10.0, 10.0) + arr[~split.mask[:, :, j]] = 0.0 + output[name] = arr.astype(np.float32) + return output diff --git a/math/Q2/plot_diagnostics.py b/math/Q2/plot_diagnostics.py new file mode 100644 index 0000000..c34b0c9 --- /dev/null +++ b/math/Q2/plot_diagnostics.py @@ -0,0 +1,142 @@ +"""Create the method-comparison figures from Q2's fixed evaluation outputs.""" +from __future__ import annotations + +import csv +import json +from pathlib import Path + +import matplotlib.pyplot as plt +import numpy as np + +from train import RESULTS + + +def read_csv(path: Path) -> list[dict[str, str]]: + with path.open("r", encoding="utf-8-sig", newline="") as stream: + return list(csv.DictReader(stream)) + + +def main() -> None: + controlled = read_csv(RESULTS / "controlled_missingness.csv") + test = read_csv(RESULTS / "test_predictions.csv") + gates = read_csv(RESULTS / "test_gate_diagnostics.csv") + metrics = json.loads((RESULTS / "test_metrics.json").read_text(encoding="utf-8")) + selected = str(metrics["selected_model"]) + + figure, axes = plt.subplots(2, 3, figsize=(17, 10), constrained_layout=True) + rate_axis, modality_axis, location_axis, confusion_axis, scatter_axis, interval_axis = axes.flat + + comparison_models = ("C0", "C3", "C4", "C5", "C6", "C7_distill", "C7_group") + for model in comparison_models: + subset = [row for row in controlled if row["model"] == model and + (row["mask_pattern"] == "none" or row["mask_pattern"] == "single")] + subset.sort(key=lambda row: float(row["rate_realized_additional_global"])) + if subset: + rate_axis.plot([float(row["rate_realized_additional_global"]) for row in subset], + [float(row["regression_mae"]) for row in subset], marker="o", label=model) + rate_axis.set(title="MAE by realized additional missing rate", xlabel="Additional missing rate (equal T/A/V)", ylabel="MAE") + rate_axis.legend(fontsize=8, ncol=2) + rate_axis.grid(alpha=0.25) + + modality_labels = ("T", "A", "V", "TA", "TV", "AV", "TAV") + modality_scenarios = {f"0.3/modality_{label}": label for label in modality_labels} + modality_models = ("C0", "C5", "C6", "C7_distill", "C7_group") + modality_values = np.full((len(modality_models), len(modality_labels)), np.nan) + for i, model in enumerate(modality_models): + for j, (scenario, _) in enumerate(modality_scenarios.items()): + pattern = scenario.split("/", 1)[1] + row = next((r for r in controlled if r["model"] == model and r["mask_pattern"] == pattern), None) + if row is not None: + modality_values[i, j] = float(row["regression_mae"]) + image = modality_axis.imshow(modality_values, aspect="auto", cmap="viridis") + modality_axis.set(title="Modality combination control: MAE", xticks=range(len(modality_labels)), + xticklabels=modality_labels, yticks=range(len(modality_models)), yticklabels=modality_models) + modality_axis.tick_params(axis="x", rotation=35) + figure.colorbar(image, ax=modality_axis, fraction=0.046, pad=0.04) + + position_values = np.full((3, 3), np.nan) + for i, modality in enumerate(("T", "A", "V")): + for j, location in enumerate(("start", "middle", "end")): + scenario = f"0.3/location_{location}_{modality}" + pattern = scenario.split("/", 1)[1] + row = next((r for r in controlled if r["model"] == selected and r["mask_pattern"] == pattern), None) + if row is not None: + position_values[i, j] = float(row["regression_mae"]) + image = location_axis.imshow(position_values, aspect="auto", cmap="magma") + location_axis.set(title=f"Selected model {selected}: location MAE", xticks=range(3), + xticklabels=("start", "middle", "end"), yticks=range(3), yticklabels=("T", "A", "V")) + figure.colorbar(image, ax=location_axis, fraction=0.046, pad=0.04) + + confusion = np.zeros((3, 3), dtype=np.int64) + for row in test: + confusion[int(row["true_class"]), int(row["predicted_class"])] += 1 + image = confusion_axis.imshow(confusion, cmap="Blues") + for i in range(3): + for j in range(3): + confusion_axis.text(j, i, str(confusion[i, j]), ha="center", va="center") + confusion_axis.set(title=f"Test confusion matrix: {selected}", xlabel="Predicted", ylabel="True", + xticks=range(3), xticklabels=("negative", "neutral", "positive"), + yticks=range(3), yticklabels=("negative", "neutral", "positive")) + figure.colorbar(image, ax=confusion_axis, fraction=0.046, pad=0.04) + + true_score = np.asarray([float(row["true_sentiment"]) for row in test]) + predicted_score = np.asarray([float(row["predicted_sentiment"]) for row in test]) + scatter_axis.scatter(true_score, predicted_score, alpha=0.55, s=18) + scatter_axis.plot([-3, 3], [-3, 3], "k--", linewidth=1) + scatter_axis.set(title=f"Test sentiment: MAE={metrics['regression_mae']:.3f}", + xlabel="True sentiment", ylabel="Predicted sentiment", xlim=(-3, 3), ylim=(-3, 3)) + scatter_axis.grid(alpha=0.2) + + lower = np.asarray([float(row["interval_90_lower"]) for row in test]) + upper = np.asarray([float(row["interval_90_upper"]) for row in test]) + width = upper - lower + covered = (true_score >= lower) & (true_score <= upper) + order = np.argsort(width) + bins = np.array_split(order, min(10, len(order))) + interval_axis.plot([width[idx].mean() for idx in bins], [covered[idx].mean() for idx in bins], marker="o") + interval_axis.axhline(0.9, color="black", linestyle="--", linewidth=1, label="nominal 90%") + interval_axis.set(title="Test interval coverage by width decile", xlabel="Mean interval width", ylabel="Empirical coverage", ylim=(0, 1)) + interval_axis.legend() + interval_axis.grid(alpha=0.2) + figure.suptitle("Q2 validation controls and official-test diagnostics", fontsize=15) + figure.savefig(RESULTS / "q2_diagnostics.png", dpi=160) + plt.close(figure) + + steps = 50 + modalities = ("text", "audio", "vision") + weight_sum = np.zeros((steps, len(modalities)), dtype=np.float64) + reliability_sum = np.zeros_like(weight_sum) + count = np.zeros_like(weight_sum) + for row in gates: + if row["modality"] not in modalities: + continue + t, m = int(row["step"]), modalities.index(row["modality"]) + weight_sum[t, m] += float(row["fusion_weight_mean_over_paths"]) + reliability_sum[t, m] += float(row["reliability"]) + count[t, m] += 1 + weights = weight_sum / np.maximum(count, 1.0) + reliabilities = reliability_sum / np.maximum(count, 1.0) + gate_figure, gate_axis = plt.subplots(figsize=(12, 5), constrained_layout=True) + for m, modality in enumerate(modalities): + gate_axis.plot(range(steps), weights[:, m], label=f"{modality} fusion weight") + gate_axis.set(title=f"Test mean fusion gates by position: {selected}", xlabel="Aligned step", ylabel="Mean fusion weight") + gate_axis.legend(ncol=3) + gate_axis.grid(alpha=0.25) + reliability_axis = gate_axis.twinx() + for m, modality in enumerate(modalities): + reliability_axis.plot(range(steps), reliabilities[:, m], linestyle=":", alpha=0.7, label=f"{modality} reliability") + reliability_axis.set_ylabel("Mean reliability proxy") + handles, labels = gate_axis.get_legend_handles_labels() + right_handles, right_labels = reliability_axis.get_legend_handles_labels() + gate_axis.legend(handles + right_handles, labels + right_labels, ncol=3, fontsize=8) + gate_figure.savefig(RESULTS / "q2_gate_positions.png", dpi=160) + plt.close(gate_figure) + manifest_path = RESULTS / "run_manifest.json" + manifest = json.loads(manifest_path.read_text(encoding="utf-8")) + manifest["diagnostic_figures"] = ["q2_diagnostics.png", "q2_gate_positions.png"] + manifest_path.write_text(json.dumps(manifest, ensure_ascii=False, indent=2), encoding="utf-8") + print(f"Wrote Q2 figures for selected model {selected} to {RESULTS}") + + +if __name__ == "__main__": + main() diff --git a/math/Q2/predict_attachment3.py b/math/Q2/predict_attachment3.py new file mode 100644 index 0000000..f0a8fb7 --- /dev/null +++ b/math/Q2/predict_attachment3.py @@ -0,0 +1,103 @@ +"""Run the saved Q2 student on the aligned, unlabeled attachment-3 cases.""" +from __future__ import annotations + +import json +import time +import csv + +import numpy as np +import torch + +from crg import INPUT_DIMS, MODALITIES, StructuredGaussianImputer +from train import RESULTS, _make_variant, infer_attachment3, reencode_attachment3, validate_attachment3_predictions, write_csv + + +def main() -> None: + device = torch.device("cuda" if torch.cuda.is_available() else "cpu") + manifest_path = RESULTS / "run_manifest.json" + manifest = json.loads(manifest_path.read_text(encoding="utf-8")) + calibration = json.loads((RESULTS / "validation_metrics.json").read_text(encoding="utf-8")) + selected = calibration.get("selected_model", manifest.get("selected_model")) + if not selected: + raise ValueError("run_manifest.json does not identify a selected model") + + imputer = StructuredGaussianImputer(INPUT_DIMS).to(device) + imputer_state = torch.load(RESULTS / "structured_imputer.pt", map_location=device, weights_only=True) + imputer.load_state_dict(imputer_state) + model = _make_variant(selected, imputer).to(device) + state = torch.load(RESULTS / "crg_student.pt", map_location=device, weights_only=True) + model.load_state_dict(state) + + with np.load(RESULTS / "preprocessor.npz", allow_pickle=False) as archive: + fitted = {m: {k: archive[f"{m}_{k}"].copy() for k in ("mean", "std")} for m in MODALITIES} + priors = manifest["attachment3_low_information_priors"] + temperature = float(calibration["temperature"]) + class_prior = np.asarray(priors["class_probability_values"], dtype=np.float64) + magnitude_priors = np.asarray((priors["negative_beta"], priors["positive_beta"]), dtype=np.float32) + + cases, source_audit = reencode_attachment3(device) + predictions, inference_audit = infer_attachment3( + model, cases, fitted, device, temperature, class_prior, magnitude_priors, + ) + validate_attachment3_predictions([case["case_id"] for case in cases], predictions) + inference_by_id = {row["case_id"]: row for row in inference_audit} + write_csv(RESULTS / "attachment3_predictions.csv", predictions) + write_csv(RESULTS / "attachment3_audit.csv", [ + {**source, **inference_by_id[source["case_id"]]} for source in source_audit + ]) + + # The training script can finish and persist all labeled-evaluation outputs + # before an unlabeled attachment export fails. Reconcile the manifest from + # those completed artifacts so the standalone export is safely rerunnable. + group_risk_rows = list(csv.DictReader((RESULTS / "group_risk_tuning.csv").open(encoding="utf-8-sig", newline=""))) + selected_risk = next((row for row in group_risk_rows if row.get("selected", "").lower() == "true"), None) + reliability_rows = list(csv.DictReader((RESULTS / "reliability_hparam_tuning.csv").open(encoding="utf-8-sig", newline=""))) + # split_calibration's generic internal names are canonicalized in train.py; + # repair artifacts from runs produced before that naming fix as well. + for row in group_risk_rows: + if row.get("selection_split") == "fit": + row["selection_split"] = "reliability_validation" + for row in reliability_rows: + if row.get("selection_split") == "fit": + row["selection_split"] = "reliability_validation" + write_csv(RESULTS / "group_risk_tuning.csv", group_risk_rows) + write_csv(RESULTS / "reliability_hparam_tuning.csv", reliability_rows) + if selected_risk: + risk_values = (float(selected_risk["lambda_group"]), float(selected_risk["group_temperature"])) + manifest["group_risk_hyperparameters"]["selected"] = list(risk_values) + manifest["loss"]["selected_group_risk"] = list(risk_values) + manifest["group_risk_hyperparameters"]["selection_split"] = "reliability_validation" + manifest["reliability_hyperparameters"]["selected_by_model"] = { + row["model"]: [float(row[key]) for key in ("rho_imp", "lambda_u", "lambda_gap", "lambda_span")] + for row in reliability_rows + if row.get("selected", "").lower() == "true" + and (not row.get("risk_candidate_selected") or row["risk_candidate_selected"].lower() == "true") + } + test_metrics = json.loads((RESULTS / "test_metrics.json").read_text(encoding="utf-8")) + manifest["selected_model"] = selected + manifest["final_test_metrics"] = test_metrics + manifest["calibration"]["temperature"] = temperature + manifest["calibration"]["valid_used_for_selection"] = True + manifest["calibration"]["test_used_for_selection_or_calibration"] = False + manifest["training_configuration"].update({ + "student_epoch_limit": 12, + "imputer_epochs": 8, + "batch_size": 64, + "early_stopping_patience": 3, + }) + manifest["imputer"]["epochs"] = 8 + manifest.update({ + "completed_utc": time.strftime("%Y-%m-%dT%H:%M:%SZ", time.gmtime()), + "attachment3_cases": len(cases), + "attachment3_prediction_file": "attachment3_predictions.csv", + "attachment3_audit_file": "attachment3_audit.csv", + "attachment3_labeled_metrics": None, + "quality_flags": {m: "unavailable; q*=1 fallback for visible rows, unknown flag retained" for m in MODALITIES}, + "neutral_output": "exact zero when neutral is the predicted class; no near-zero threshold", + }) + manifest_path.write_text(json.dumps(manifest, ensure_ascii=False, indent=2), encoding="utf-8") + print(f"Wrote {len(predictions)} unlabeled attachment-3 predictions to {RESULTS}", flush=True) + + +if __name__ == "__main__": + main() diff --git a/math/Q2/results/ablation_validation.csv b/math/Q2/results/ablation_validation.csv new file mode 100644 index 0000000..44679ed --- /dev/null +++ b/math/Q2/results/ablation_validation.csv @@ -0,0 +1,13 @@ +model,n,accuracy,macro_f1,negative_support,neutral_support,positive_support,negative_recall,middle_recall,positive_recall,regression_mae,regression_rmse,pearson,brier,classification_nll,ece_15,interval_90_coverage,interval_90_mean_width,selection_nll,temperature,description,predictive_variance_mean_uncalibrated,within_trajectory_variance_mean,between_trajectory_variance_mean,predictive_mean_mean_calibrated,predictive_variance_mean_calibrated,validation_selection_loss,rho_imp,lambda_u,lambda_gap,lambda_span,lambda_group,group_temperature +C0,728,0.592032967032967,0.5559346126510305,206,184,338,0.5825242718446602,0.34782608695652173,0.7307692307692307,0.7334139347076416,0.9371736594281902,0.5192425847053528,0.5145634913739343,0.8668775768593128,0.03562808104126608,0.9093406593406593,3.1437528133392334,0.9035571651175792,2.032287887301264,observed mean/std + masks + maximum gap; logistic/ridge,,,,,,,,,,,, +C1,728,0.6071428571428571,0.55124288334091,206,184,338,0.6796116504854369,0.23369565217391305,0.7662721893491125,0.6779899001121521,0.9222378420815579,0.5779994130134583,0.4974337085664247,0.8442830443382263,0.05466654393207895,0.8956043956043956,2.463564872741699,2.7879433631896973,1.1214790595552069,"masked BiGRU; no posterior imputation, explicit reliability or source gate",0.5905959010124207,0.5905959010124207,0.0,0.18120460212230682,0.6191508769989014,2.7879433631896973,0.5,0.05,0.05,0.05,nan,nan 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gate,0.5990039110183716,0.5990003943443298,3.476098072496825e-06,0.21980196237564087,0.6516103148460388,2.77126407623291,0.3,0.05,0.05,0.05,nan,nan +C4,728,0.6085164835164835,0.555058605423057,206,184,338,0.6504854368932039,0.25,0.7781065088757396,0.6918120384216309,0.9515582480750588,0.5684906244277954,0.5075791281376366,0.8570581078529358,0.05379025265574453,0.8983516483516484,2.538222312927246,2.8107874393463135,1.0471160328013351,C3 plus bounded cross-time source attention and null source,0.6382710933685303,0.6382405161857605,3.0667371902382e-05,0.2080966681241989,0.6502240300178528,2.81081223487854,0.7,0.05,0.05,0.05,nan,nan +C5,728,0.6153846153846154,0.5445555339287688,206,184,338,0.6990291262135923,0.19021739130434784,0.7958579881656804,0.6623618006706238,0.8933437077491609,0.6174448132514954,0.4918066281209682,0.8373782634735107,0.06113330221601894,0.8928571428571429,2.381938934326172,2.7620162963867188,1.212728800581531,C4 plus reliability-modulated BiGRU update,0.5485545992851257,0.5485460758209229,8.503861863573547e-06,0.13911069929599762,0.5960606336593628,2.7618556022644043,0.3,0.05,0.05,0.05,nan,nan +C6,728,0.6263736263736264,0.5801114274083624,206,184,338,0.6941747572815534,0.29891304347826086,0.7633136094674556,0.6457235217094421,0.8814069986838935,0.6157047748565674,0.4856194350316264,0.8258335590362549,0.031823099805758544,0.885989010989011,2.30387282371521,2.774562358856201,1.1780751742536886,C5 plus optional rank-4 CP residual,0.49419134855270386,0.4941462278366089,4.511491351877339e-05,0.13551649451255798,0.5317712426185608,2.774617910385132,0.3,0.05,0.05,0.05,nan,nan +C6_no_distance,728,0.6043956043956044,0.5144916075030433,206,184,338,0.6553398058252428,0.13043478260869565,0.8313609467455622,0.6794722676277161,0.9098390018130259,0.6045995950698853,0.5041281436421426,0.8588091731071472,0.04508186811274226,0.885989010989011,2.2977938652038574,2.808736562728882,1.36875500088095,C6 with uncertainty retained but both distance/span reliability penalties fixed to zero,0.4714658260345459,0.47136420011520386,0.00010164274135604501,0.14785172045230865,0.5429188013076782,2.8084704875946045,0.5,0.0,0.0,0.0,nan,nan +C6_no_reconstruction,728,0.6002747252747253,0.5178357887707189,206,184,338,0.6650485436893204,0.14130434782608695,0.8106508875739645,0.6957471370697021,0.9327064671148756,0.5887437462806702,0.5024915749758389,0.8508719205856323,0.04982036520000343,0.8928571428571429,2.390105724334717,2.794447422027588,1.180521560150874,C6 trained without the auxiliary hidden-feature reconstruction loss,0.5634137392044067,0.5633965134620667,1.724438880046364e-05,0.1889886111021042,0.6063413023948669,2.794414520263672,0.3,0.05,0.05,0.05,nan,nan 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only,0.5134512186050415,0.513433575630188,1.761062230798416e-05,0.16756068170070648,0.5485631823539734,2.8153774738311768,0.3,0.05,0.05,0.05,nan,nan +C7_group,728,0.6085164835164835,0.5116842947005743,206,184,338,0.6747572815533981,0.11413043478260869,0.8372781065088757,0.6860273480415344,0.9252878475802377,0.5911917090415955,0.5028568696567639,0.8551272749900818,0.0504213785650311,0.8928571428571429,2.445509672164917,2.7835769653320312,1.044649831831679,C6 plus smooth worst-group risk only,0.6084297895431519,0.6084184646606445,1.1323560102027841e-05,0.12680216133594513,0.6198152303695679,2.783574342727661,0.3,0.05,0.05,0.05,0.1,0.05 diff --git a/math/Q2/results/attachment3_audit.csv b/math/Q2/results/attachment3_audit.csv new file mode 100644 index 0000000..eee4bf2 --- /dev/null +++ b/math/Q2/results/attachment3_audit.csv @@ -0,0 +1,31 @@ +case_id,source_file,text_visible_steps,audio_visible_steps,vision_visible_steps,audio_missing_fraction,vision_missing_fraction,unknown_quality_flag,labels_available,input_note,source_sha256,visible_text_steps,visible_audio_steps,visible_vision_steps,low_information_prior_fallback,calibration_temperature,interval_90_lower,interval_90_upper,predictive_variance_mean_uncalibrated,predictive_variance_calibrated +附件3_01,附件3_01.pkl,8,6,6,0.88,0.88,True,False,official aligned_50 only; unaligned rows and raw transcript are not used,b45b89a7eea55278abb130d44a6ee21128df5aa3239e68c968f9ac7743cfa0ea,8,6,6,False,1.212728800581531,-2.0970382690429688,2.056648015975952,1.7335734367370605,1.7042454481124878 +附件3_02,附件3_02.pkl,30,23,23,0.54,0.54,True,False,official aligned_50 only; unaligned rows and raw transcript are not used,6a628897c4b8c5e94e37f23bce680aad500fa8545414234f3564a58577c1023b,30,23,23,False,1.212728800581531,-0.9996623396873474,1.3429561853408813,0.42073488235473633,0.4336998462677002 +附件3_03,附件3_03.pkl,34,27,23,0.45999999999999996,0.54,True,False,official aligned_50 only; unaligned rows and raw transcript are not used,52bb6e11f4bba301e1bd90916dc9ad3a0d2d0885fec4598e3e737e2c4d100b6f,34,27,23,False,1.212728800581531,-0.45678868889808655,1.5853729248046875,0.3916955590248108,0.40991201996803284 +附件3_04,附件3_04.pkl,33,29,29,0.42000000000000004,0.42000000000000004,True,False,official aligned_50 only; unaligned rows and raw transcript are not used,ee1f4781ee7b7bc37e71a13e4bc53eedc8327d96a69c246964d0e84a8aa99f72,33,29,29,False,1.212728800581531,-0.3432163894176483,1.6048578023910522,0.3745034337043762,0.39313918352127075 +附件3_05,附件3_05.pkl,14,12,12,0.76,0.76,True,False,official aligned_50 only; unaligned rows and raw transcript are not used,9f8e5bae8488d8ee1576b1686864b7d8fc9970cfa720758fb040b9293b7e3619,14,12,12,False,1.212728800581531,-2.163356304168701,1.5903369188308716,1.2121071815490723,1.2855738401412964 +附件3_06,附件3_06.pkl,27,22,22,0.56,0.56,True,False,official aligned_50 only; unaligned rows and raw transcript are not used,9e973621f141b1af24fc3686ac329a10b66ba2b84d18c21918e86bf0429f790d,27,22,22,False,1.212728800581531,-0.36223649978637695,2.1398749351501465,0.6031956672668457,0.6750403046607971 +附件3_07,附件3_07.pkl,23,18,18,0.64,0.64,True,False,official aligned_50 only; unaligned rows and raw transcript are not used,62dd394e23c80af2898e039d7eb6f47556d747887331fa2853dad72e13bb223b,23,18,18,False,1.212728800581531,-0.3932100832462311,1.769598126411438,0.44835442304611206,0.47891828417778015 +附件3_08,附件3_08.pkl,17,13,13,0.74,0.74,True,False,official aligned_50 only; unaligned rows and raw transcript are not used,e668faea97f9a338051c19ee66383df799b2e461d6d079df8c5f92b32bd6437e,17,13,13,False,1.212728800581531,-0.9790695905685425,1.6200528144836426,0.5541559457778931,0.5690155625343323 +附件3_09,附件3_09.pkl,16,12,12,0.76,0.76,True,False,official aligned_50 only; unaligned rows and raw transcript are not used,ef57769eaa05f53a7d588948d565876356898658d9945202058ca763e53748b2,16,12,12,False,1.212728800581531,-0.27194494009017944,2.0130302906036377,0.5201191902160645,0.5757794380187988 +附件3_10,附件3_10.pkl,8,6,6,0.88,0.88,True,False,official aligned_50 only; unaligned rows and raw transcript are not used,7c87d84d69e0e68b9252c9839747558d07a91fd2d079a9a0850683d0d197241e,8,6,6,False,1.212728800581531,-0.9529624581336975,1.640604019165039,0.5439862012863159,0.5653517842292786 +附件3_11,附件3_11.pkl,16,10,10,0.8,0.8,True,False,official aligned_50 only; unaligned rows and raw transcript are not used,10e9d5443cecf2de9170deaa56995de0cf9c52580a74cd334de8fea0e4a735f2,16,10,10,False,1.212728800581531,-0.5261767506599426,1.6935460567474365,0.450601726770401,0.4752480089664459 +附件3_12,附件3_12.pkl,15,11,11,0.78,0.78,True,False,official aligned_50 only; unaligned rows and raw transcript are not used,d0342f4931a05e40fb0a3220010f1ac801a2f06d123bc4d9a7dc5355794347ba,15,11,11,False,1.212728800581531,-0.9405485391616821,1.926857590675354,0.7031970620155334,0.7392448782920837 +附件3_13,附件3_13.pkl,21,17,17,0.6599999999999999,0.6599999999999999,True,False,official aligned_50 only; unaligned rows and raw transcript are not used,9e2144ab4385636b259d9e358c7e511be5242c89340f894473317b7757f218b7,21,17,17,False,1.212728800581531,-0.9272081851959229,1.7548140287399292,0.6093371510505676,0.6293941736221313 +附件3_14,附件3_14.pkl,25,21,21,0.5800000000000001,0.5800000000000001,True,False,official aligned_50 only; unaligned rows and raw transcript are not used,f6d45e8fa882062f70fd48ee1f7584b0a75ea0ed1c85a9eb218684e954dc1b82,25,21,21,False,1.212728800581531,-1.5893217325210571,1.5921794176101685,0.8739535212516785,0.8658839464187622 +附件3_15,附件3_15.pkl,29,24,24,0.52,0.52,True,False,official aligned_50 only; unaligned rows and raw transcript are not used,263b960d4d66b25a3db447fb7a16aee7b7d735e8bee3fe55c7869ad3103bf9d4,29,24,24,False,1.212728800581531,-0.087561696767807,1.8981196880340576,0.43900278210639954,0.4791504144668579 +附件3_16,附件3_16.pkl,36,30,30,0.4,0.4,True,False,official aligned_50 only; unaligned rows and raw transcript are not used,df8b4c881e3fc971d532988bbd161d8d9bf8c5d16c3e7a559bb7a4045e96547f,36,30,30,False,1.212728800581531,-0.3259946405887604,2.3747494220733643,0.6431438326835632,0.7642990946769714 +附件3_17,附件3_17.pkl,24,14,14,0.72,0.72,True,False,official aligned_50 only; unaligned rows and raw transcript are not used,b6c64a55fb8050cb9fda15b0245df8f16b20d2a25d9368485dd1229e213fdba5,24,14,14,False,1.212728800581531,-0.6764342784881592,1.3940967321395874,0.3571646213531494,0.36965644359588623 +附件3_18,附件3_18.pkl,19,14,14,0.72,0.72,True,False,official aligned_50 only; unaligned rows and raw transcript are not used,dc8eb37586b93bdd4debe895041275fdabb94c3392bde667b4e0ccdc6429fab1,19,14,14,False,1.212728800581531,-0.38681817054748535,1.673882246017456,0.41236546635627747,0.43565449118614197 +附件3_19,附件3_19.pkl,26,17,17,0.6599999999999999,0.6599999999999999,True,False,official aligned_50 only; unaligned rows and raw transcript are not used,d3a912bc3c70b60c1021babc521f28a6a34f9e916c164ad0191182e587c2385a,26,17,17,False,1.212728800581531,-1.0595200061798096,1.3693560361862183,0.45944827795028687,0.4690973460674286 +附件3_20,附件3_20.pkl,50,34,34,0.31999999999999995,0.31999999999999995,True,False,official aligned_50 only; unaligned rows and raw transcript are not used,bf24c7189bba3904e911dd452266078d8ff15768438a9069e6596ff73a4b925e,50,34,34,False,1.212728800581531,-0.37013763189315796,1.301245093345642,0.26743096113204956,0.2766386568546295 +附件3_21,附件3_21.pkl,11,6,6,0.88,0.88,True,False,official aligned_50 only; unaligned rows and raw transcript are not used,c0605bd5757ff0c5dea345c96236ed7168ff976d37843572143efe11d6454600,11,6,6,False,1.212728800581531,-0.33592545986175537,1.722812533378601,0.42267656326293945,0.4489213228225708 +附件3_22,附件3_22.pkl,19,13,13,0.74,0.74,True,False,official aligned_50 only; unaligned rows and raw transcript are not used,6f9dc33f9d3e5680ee3a3b2b0c53b1bac51fb98f1d75375a2cb1224cd7bd4d43,19,13,13,False,1.212728800581531,-0.5156432390213013,1.6332861185073853,0.42243894934654236,0.4429676830768585 +附件3_23,附件3_23.pkl,15,9,9,0.8200000000000001,0.8200000000000001,True,False,official aligned_50 only; unaligned rows and raw transcript are not used,5200bd05e2611777875eb1d88826bb56bb71dee4c708fec9d9f851222d243aae,15,9,9,False,1.212728800581531,-0.49955275654792786,1.6659469604492188,0.43331629037857056,0.4561525285243988 +附件3_24,附件3_24.pkl,10,6,6,0.88,0.88,True,False,official aligned_50 only; unaligned rows and raw transcript are not used,76b1c126e2043f90afd5af00d51299bc8f5bf1bee8148f5ff904ccbeb931a5e5,10,6,6,False,1.212728800581531,-1.0213178396224976,1.8038268089294434,0.6638259291648865,0.6895806193351746 +附件3_25,附件3_25.pkl,11,7,7,0.86,0.86,True,False,official aligned_50 only; unaligned rows and raw transcript are not used,88d52e2d0b0229ad6ec638e6e7463f6852f127ae9308fbee1cbc2405d8ebc4c8,11,7,7,False,1.212728800581531,-1.013203501701355,1.9055728912353516,0.7159426808357239,0.7510258555412292 +附件3_26,附件3_26.pkl,24,16,16,0.6799999999999999,0.6799999999999999,True,False,official aligned_50 only; unaligned rows and raw transcript are not used,e483daa1391987552f9ee7f21bffec918dd61267af36885a9ae3073813193234,24,16,16,False,1.212728800581531,-0.42688244581222534,1.7250646352767944,0.4398258328437805,0.46607935428619385 +附件3_27,附件3_27.pkl,23,13,13,0.74,0.74,True,False,official aligned_50 only; unaligned rows and raw transcript are not used,27f16bbd4541196bb33f4caa36e038b2ff66fa72649f1b22f2328a5630de37ad,23,13,13,False,1.212728800581531,-0.5788680911064148,1.7725975513458252,0.5006299018859863,0.529201865196228 +附件3_28,附件3_28.pkl,35,22,22,0.56,0.56,True,False,official aligned_50 only; unaligned rows and raw transcript are not used,81def781fa8fa5aebb555631b59ce48ee71a10c9e4226f1a5b6d91a2078f8f32,35,22,22,False,1.212728800581531,-0.2326158583164215,1.5581943988800049,0.34371161460876465,0.35912466049194336 +附件3_29,附件3_29.pkl,20,10,10,0.8,0.8,True,False,official aligned_50 only; unaligned rows and raw transcript are not used,8caf12e71117bd7334be12aba5af6322fb02a2397f8e2402e75391f4f9ef3686,20,10,10,False,1.212728800581531,-0.4160189926624298,1.6209927797317505,0.3967360258102417,0.4166872203350067 +附件3_30,附件3_30.pkl,26,12,12,0.76,0.76,True,False,official aligned_50 only; unaligned rows and raw transcript are not used,a6b272abb5d083804b6902054d4180d55d3c1d5822c483967e70e6a9657546d3,26,12,12,False,1.212728800581531,-0.5056151747703552,1.6129341125488281,0.41301825642585754,0.4326811134815216 diff --git a/math/Q2/results/attachment3_predictions.csv b/math/Q2/results/attachment3_predictions.csv new file mode 100644 index 0000000..dbd8b8a --- /dev/null +++ b/math/Q2/results/attachment3_predictions.csv @@ -0,0 +1,31 @@ +case_id,predicted_class,predicted_class_name,predicted_sentiment,p_negative,p_neutral,p_positive,interval_90_lower,interval_90_upper,predictive_variance_mean_uncalibrated,within_trajectory_variance,between_trajectory_variance,predictive_mean_calibrated,predictive_variance_calibrated,beta_negative_alpha,beta_negative_beta,beta_positive_alpha,beta_positive_beta,low_information_prior_fallback,output_note +附件3_01,0,negative,-1.36937415599823,0.4173367917537689,0.2499246746301651,0.33273857831954956,-2.0970382690429688,2.056648015975952,1.7335734367370605,1.7284892797470093,0.005084219854325056,-0.1036895290017128,1.7042454481124878,2.674145460128784,3.2804768085479736,2.7497973442077637,3.2124524116516113,False,unlabeled attachment-3 case; no accuracy/F1 is defined +附件3_02,1,neutral,0.0,0.21550683677196503,0.39427483081817627,0.3902183771133423,-0.9996623396873474,1.3429561853408813,0.42073488235473633,0.4203958213329315,0.0003390766796655953,0.14255677163600922,0.4336998462677002,1.3450913429260254,4.609530925750732,1.4741648435592651,4.48808479309082,False,unlabeled attachment-3 case; no accuracy/F1 is defined +附件3_03,2,positive,0.7297439575195312,0.09833002090454102,0.31945013999938965,0.5822198390960693,-0.45678868889808655,1.5853729248046875,0.3916955590248108,0.39153820276260376,0.00015736681234557182,0.41550716757774353,0.40991201996803284,1.1170369386672974,4.83758544921875,1.602070689201355,4.3601789474487305,False,unlabeled attachment-3 case; no accuracy/F1 is defined +附件3_04,2,positive,0.7168514728546143,0.09202363342046738,0.26720553636550903,0.6407707929611206,-0.3432163894176483,1.6048578023910522,0.3745034337043762,0.37437793612480164,0.00012550917745102197,0.46580955386161804,0.39313918352127075,0.999448835849762,4.955173492431641,1.579308271408081,4.382941722869873,False,unlabeled attachment-3 case; no accuracy/F1 is defined +附件3_05,0,negative,-1.3051139116287231,0.6191708445549011,0.18749956786632538,0.19332952797412872,-2.163356304168701,1.5903369188308716,1.2121071815490723,1.21091890335083,0.00118827389087528,-0.5868104696273804,1.2855738401412964,2.6856813430786133,3.2689409255981445,2.4296228885650635,3.5326268672943115,False,unlabeled attachment-3 case; no accuracy/F1 is defined +附件3_06,2,positive,1.2219310998916626,0.0717640370130539,0.19590744376182556,0.7323285341262817,-0.36223649978637695,2.1398749351501465,0.6031956672668457,0.6026917099952698,0.0005039607058279216,0.8673529624938965,0.6750403046607971,1.3492683172225952,4.605353832244873,2.5232043266296387,3.4390454292297363,False,unlabeled attachment-3 case; no accuracy/F1 is defined +附件3_07,2,positive,0.8548031449317932,0.09093260020017624,0.23496119678020477,0.6741061806678772,-0.3932100832462311,1.769598126411438,0.44835442304611206,0.4472731649875641,0.0010812629479914904,0.5715570449829102,0.47891828417778015,1.1685818433761597,4.786040782928467,1.9216830730438232,4.040566444396973,False,unlabeled attachment-3 case; no accuracy/F1 is defined +附件3_08,2,positive,0.8116514086723328,0.18446336686611176,0.3151225447654724,0.5004140734672546,-0.9790695905685425,1.6200528144836426,0.5541559457778931,0.5526819825172424,0.0014739632606506348,0.3095678389072418,0.5690155625343323,1.4368412494659424,4.5177812576293945,1.7043733596801758,4.257876396179199,False,unlabeled attachment-3 case; no accuracy/F1 is defined +附件3_09,2,positive,1.0759609937667847,0.06864966452121735,0.19431467354297638,0.7370356321334839,-0.27194494009017944,2.0130302906036377,0.5201191902160645,0.5187233090400696,0.001395862433128059,0.7838703989982605,0.5757794380187988,1.1855928897857666,4.769029140472412,2.1737170219421387,3.7885324954986572,False,unlabeled attachment-3 case; no accuracy/F1 is defined +附件3_10,2,positive,0.8279328942298889,0.15922266244888306,0.33621782064437866,0.5045595169067383,-0.9529624581336975,1.640604019165039,0.5439862012863159,0.541014552116394,0.002971647074446082,0.3323303759098053,0.5653517842292786,1.6985840797424316,4.256038188934326,1.8447978496551514,4.1174516677856445,False,unlabeled attachment-3 case; no accuracy/F1 is defined +附件3_11,2,positive,0.8127984404563904,0.10333395004272461,0.28441768884658813,0.6122483611106873,-0.5261767506599426,1.6935460567474365,0.450601726770401,0.4495840072631836,0.0010177356889471412,0.4789048135280609,0.4752480089664459,1.229117512702942,4.7255048751831055,1.7684253454208374,4.193824768066406,False,unlabeled attachment-3 case; no accuracy/F1 is defined +附件3_12,2,positive,1.0638002157211304,0.14721493422985077,0.2707417607307434,0.5820432901382446,-0.9405485391616821,1.926857590675354,0.7031970620155334,0.7023799419403076,0.0008171494700945914,0.5303252339363098,0.7392448782920837,1.573769450187683,4.380852699279785,2.27978777885437,3.682461977005005,False,unlabeled attachment-3 case; no accuracy/F1 is defined +附件3_13,2,positive,0.9134635329246521,0.16992026567459106,0.2880288064479828,0.5420509576797485,-0.9272081851959229,1.7548140287399292,0.6093371510505676,0.6087684631347656,0.0005686438526026905,0.40759792923927307,0.6293941736221313,1.3964232206344604,4.558198928833008,1.9324531555175781,4.029796600341797,False,unlabeled attachment-3 case; no accuracy/F1 is defined +附件3_14,0,negative,-0.892810046672821,0.3689012825489044,0.2989215552806854,0.33217719197273254,-1.5893217325210571,1.5921794176101685,0.8739535212516785,0.8734892010688782,0.00046435598051175475,-0.02208448201417923,0.8658839464187622,1.902026891708374,4.052595615386963,2.003140449523926,3.959109306335449,False,unlabeled attachment-3 case; no accuracy/F1 is defined +附件3_15,2,positive,0.9513995051383972,0.056912899017333984,0.19684948027133942,0.7462376356124878,-0.087561696767807,1.8981196880340576,0.43900278210639954,0.43879440426826477,0.0002083669533021748,0.7231543064117432,0.4791504144668579,1.0397167205810547,4.914905548095703,1.9904775619506836,3.9717724323272705,False,unlabeled attachment-3 case; no accuracy/F1 is defined +附件3_16,2,positive,1.4835878610610962,0.06787766516208649,0.12633372843265533,0.8057885766029358,-0.3259946405887604,2.3747494220733643,0.6431438326835632,0.6427069306373596,0.00043692614417523146,1.1498675346374512,0.7642990946769714,1.3606003522872925,4.594021797180176,2.9519271850585938,3.0103228092193604,False,unlabeled attachment-3 case; no accuracy/F1 is defined +附件3_17,2,positive,0.6192584037780762,0.14884452521800995,0.36308035254478455,0.4880751371383667,-0.6764342784881592,1.3940967321395874,0.3571646213531494,0.35702022910118103,0.00014440729864872992,0.2622087895870209,0.36965644359588623,1.1206523180007935,4.833970069885254,1.3981351852416992,4.564114570617676,False,unlabeled attachment-3 case; no accuracy/F1 is defined +附件3_18,2,positive,0.7816779017448425,0.08878601342439651,0.27361562848091125,0.6375983357429504,-0.38681817054748535,1.673882246017456,0.41236546635627747,0.41164833307266235,0.0007171193137764931,0.4965435266494751,0.43565449118614197,1.0379639863967896,4.916658401489258,1.6756945848464966,4.286555290222168,False,unlabeled attachment-3 case; no accuracy/F1 is defined +附件3_19,2,positive,0.6666292548179626,0.23249438405036926,0.3699238896369934,0.39758172631263733,-1.0595200061798096,1.3693560361862183,0.45944827795028687,0.459126353263855,0.000321923871524632,0.13807706534862518,0.4690973460674286,1.347794771194458,4.606827735900879,1.4715540409088135,4.490695953369141,False,unlabeled attachment-3 case; no accuracy/F1 is defined +附件3_20,2,positive,0.5166932344436646,0.10641121864318848,0.3626250624656677,0.5309637188911438,-0.37013763189315796,1.301245093345642,0.26743096113204956,0.2674308121204376,1.7632997639793757e-07,0.27954593300819397,0.2766386568546295,0.9049832224845886,5.0496392250061035,1.227974772453308,4.734274864196777,False,unlabeled attachment-3 case; no accuracy/F1 is defined +附件3_21,2,positive,0.8176442980766296,0.08154062181711197,0.2607261538505554,0.6577332019805908,-0.33592545986175537,1.722812533378601,0.42267656326293945,0.42220258712768555,0.00047395756701007485,0.5391724109649658,0.4489213228225708,1.0715889930725098,4.883033275604248,1.7625083923339844,4.199741363525391,False,unlabeled attachment-3 case; no accuracy/F1 is defined +附件3_22,2,positive,0.7633184790611267,0.10818565636873245,0.29112643003463745,0.6006879210472107,-0.5156432390213013,1.6332861185073853,0.42243894934654236,0.4219420850276947,0.0004968760185874999,0.44251224398612976,0.4429676830768585,1.154737949371338,4.79988431930542,1.6839652061462402,4.278284549713135,False,unlabeled attachment-3 case; no accuracy/F1 is defined +附件3_23,2,positive,0.7900046706199646,0.1003153994679451,0.29403749108314514,0.605647087097168,-0.49955275654792786,1.6659469604492188,0.43331629037857056,0.43220165371894836,0.0011146446922793984,0.4633665978908539,0.4561525285243988,1.1960126161575317,4.758609771728516,1.6995089054107666,4.262740612030029,False,unlabeled attachment-3 case; no accuracy/F1 is defined +附件3_24,2,positive,0.9684903025627136,0.16357938945293427,0.30516842007637024,0.5312522053718567,-1.0213178396224976,1.8038268089294434,0.6638259291648865,0.6613545417785645,0.002471365500241518,0.4127788543701172,0.6895806193351746,1.6767302751541138,4.277892112731934,2.067596197128296,3.894653558731079,False,unlabeled attachment-3 case; no accuracy/F1 is defined +附件3_25,2,positive,1.0527230501174927,0.1503162831068039,0.28753793239593506,0.5621457695960999,-1.013203501701355,1.9055728912353516,0.7159426808357239,0.713359534740448,0.0025831377133727074,0.4927283525466919,0.7510258555412292,1.5411937236785889,4.41342830657959,2.1070470809936523,3.8552029132843018,False,unlabeled attachment-3 case; no accuracy/F1 is defined +附件3_26,2,positive,0.8238189220428467,0.0968468189239502,0.2526003122329712,0.6505528688430786,-0.42688244581222534,1.7250646352767944,0.4398258328437805,0.4388541281223297,0.0009717019274830818,0.528623640537262,0.46607935428619385,1.06248140335083,4.892140865325928,1.7573333978652954,4.204916477203369,False,unlabeled attachment-3 case; no accuracy/F1 is defined +附件3_27,2,positive,0.8879316449165344,0.10810206085443497,0.2769993543624878,0.6148985028266907,-0.5788680911064148,1.7725975513458252,0.5006299018859863,0.4993685483932495,0.0012613764265552163,0.5172909498214722,0.529201865196228,1.2487430572509766,4.705879211425781,1.9278333187103271,4.034416198730469,False,unlabeled attachment-3 case; no accuracy/F1 is defined +附件3_28,2,positive,0.6834221482276917,0.07506436109542847,0.30108094215393066,0.6238546967506409,-0.2326158583164215,1.5581943988800049,0.34371161460876465,0.3436410129070282,7.062139047775418e-05,0.44199296832084656,0.35912466049194336,0.9794354438781738,4.975186824798584,1.5243475437164307,4.437902450561523,False,unlabeled attachment-3 case; no accuracy/F1 is defined +附件3_29,2,positive,0.7432227730751038,0.09519395977258682,0.2877791225910187,0.6170269250869751,-0.4160189926624298,1.6209927797317505,0.3967360258102417,0.396288126707077,0.0004479244234971702,0.45498380064964294,0.4166872203350067,1.0894852876663208,4.865137100219727,1.6475201845169067,4.314729690551758,False,unlabeled attachment-3 case; no accuracy/F1 is defined +附件3_30,2,positive,0.7568522691726685,0.10250545293092728,0.31905150413513184,0.5784430503845215,-0.5056151747703552,1.6129341125488281,0.41301825642585754,0.41286802291870117,0.00015023084415588528,0.4218529462814331,0.4326811134815216,1.165923833847046,4.788698196411133,1.6343237161636353,4.327926158905029,False,unlabeled attachment-3 case; no accuracy/F1 is defined diff --git a/math/Q2/results/controlled_group_bootstrap.csv b/math/Q2/results/controlled_group_bootstrap.csv new file mode 100644 index 0000000..bfc27bc --- /dev/null +++ b/math/Q2/results/controlled_group_bootstrap.csv @@ -0,0 +1,2569 @@ +model,scenario,metric,estimate,bootstrap_median,ci_2_5,ci_97_5,replicates,unit,delta_to_natural_mae,delta_to_natural_bootstrap_median,delta_to_natural_ci_2_5,delta_to_natural_ci_97_5,baseline,delta_estimate,delta_bootstrap_median,delta_ci_2_5,delta_ci_97_5,curve_additional_rates_realized +C0,0.0/none,accuracy,0.592032967032967,0.5929823697429331,0.5497822406088535,0.6298356566397652,1000,paired source-video group resample,,,,,,,,,, +C0,0.0/none,macro_f1,0.5559346126510305,0.5558367057869622,0.5141894142546704,0.5918337468912219,1000,paired source-video group resample,,,,,,,,,, +C0,0.0/none,mae,0.7334139347076416,0.7329291105270386,0.6834514245390892,0.7862065181136131,1000,paired source-video group resample,,,,,,,,,, +C0,0.0/none,rmse,0.9371736594281902,0.9356625192775279,0.8747686466727267,1.003268697388219,1000,paired source-video group resample,,,,,,,,,, +C0,0.0/none,pearson,0.5192425847053528,0.5182984471321106,0.4543555065989494,0.5769079387187958,1000,paired source-video group resample,,,,,,,,,, +C0,0.1/single,accuracy,0.5879120879120879,0.5874285500803228,0.5447648594193608,0.6263590689202102,1000,paired source-video group resample,,,,,,,,,, +C0,0.1/single,macro_f1,0.5498847974369063,0.5488777907074065,0.5099957610630138,0.585634025659303,1000,paired source-video group resample,,,,,,,,,, +C0,0.1/single,mae,0.7357591986656189,0.7356792986392975,0.6860240221023559,0.7892804458737374,1000,paired source-video group resample,0.002345263957977295,0.002310335636138916,-0.003186596930027008,0.007446514070034027,,,,,, +C0,0.1/single,rmse,0.9393225755612472,0.937973790771371,0.8752479958152041,1.0055719374140082,1000,paired source-video group resample,,,,,,,,,, +C0,0.1/single,pearson,0.5165755152702332,0.5152187347412109,0.45164660885930064,0.5742003113031388,1000,paired source-video group resample,,,,,,,,,, +C0,0.1/sync,accuracy,0.5865384615384616,0.586576317383404,0.5443133183553385,0.6269584139264991,1000,paired source-video group resample,,,,,,,,,, +C0,0.1/sync,macro_f1,0.5503280630947532,0.5494824393124147,0.508639743209895,0.5906766400172654,1000,paired source-video group resample,,,,,,,,,, +C0,0.1/sync,mae,0.7350428700447083,0.7352079749107361,0.6864669665694236,0.788788628578186,1000,paired source-video group resample,0.0016289353370666504,0.0016409456729888916,-0.005315054953098297,0.009473209083080292,,,,,, +C0,0.1/sync,rmse,0.9451832643552867,0.9444521622404719,0.8796514333606797,1.010672032146911,1000,paired source-video group resample,,,,,,,,,, +C0,0.1/sync,pearson,0.5133998394012451,0.5125228464603424,0.45012450143694877,0.5694661796092987,1000,paired source-video group resample,,,,,,,,,, +C0,0.1/partial,accuracy,0.5934065934065934,0.5938149698440922,0.5494058423382925,0.634120187543447,1000,paired source-video group resample,,,,,,,,,, +C0,0.1/partial,macro_f1,0.5576329380033053,0.5569358951145289,0.5136735898127724,0.5969362949022702,1000,paired source-video group resample,,,,,,,,,, +C0,0.1/partial,mae,0.7352173924446106,0.7341216802597046,0.6841594845056533,0.7863971263170242,1000,paired source-video group resample,0.0018034577369689941,0.0018716752529144287,-0.006088666617870331,0.009477871656417846,,,,,, +C0,0.1/partial,rmse,0.937443445407212,0.9364795690246577,0.8756361118304781,1.0031908059696912,1000,paired source-video group resample,,,,,,,,,, +C0,0.1/partial,pearson,0.5205735564231873,0.5200516879558563,0.4558235466480255,0.5807098135352134,1000,paired source-video group resample,,,,,,,,,, +C0,0.1/async,accuracy,0.592032967032967,0.5916229194917719,0.5477374226624452,0.6321523600047557,1000,paired source-video group resample,,,,,,,,,, +C0,0.1/async,macro_f1,0.5588070218794071,0.5581100021501743,0.5163971860895342,0.5959651874477971,1000,paired source-video group resample,,,,,,,,,, +C0,0.1/async,mae,0.7388936281204224,0.7384577691555023,0.6899581402540207,0.7915590897202491,1000,paired source-video group resample,0.005479693412780762,0.005306035280227661,-0.002763606607913971,0.014477260410785675,,,,,, +C0,0.1/async,rmse,0.9437346412975244,0.9430952133442707,0.8830321697032809,1.0081500255670626,1000,paired source-video group resample,,,,,,,,,, +C0,0.1/async,pearson,0.5140159726142883,0.513122946023941,0.44995776042342184,0.5687912911176681,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/single,accuracy,0.6057692307692307,0.6066854515974276,0.562235685585133,0.6440967837736762,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/single,macro_f1,0.5692992494084482,0.5686499355616363,0.5271598785226631,0.6069995063238338,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/single,mae,0.7311311364173889,0.7307063341140747,0.6835894018411637,0.7829183146357537,1000,paired source-video group resample,-0.0022827982902526855,-0.002622753381729126,-0.013038329780101776,0.009208072721958156,,,,,, +C0,0.3/single,rmse,0.9397675747335449,0.9382487803485595,0.8778499427948991,1.0037030892695933,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/single,pearson,0.5214155912399292,0.5211992561817169,0.45798412412405015,0.5795521318912507,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/sync,accuracy,0.5796703296703297,0.5806453740342943,0.540764608413885,0.6173158888662702,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/sync,macro_f1,0.5401009894394878,0.539921855987814,0.5022398062919277,0.5765564116655415,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/sync,mae,0.7529036998748779,0.754024863243103,0.7068626776337623,0.8047507032752037,1000,paired source-video group resample,0.019489765167236328,0.0199735164642334,0.003776802122592926,0.036457897722721094,,,,,, +C0,0.3/sync,rmse,0.9622927157642773,0.9620028688161524,0.9004384818231981,1.027607915809802,1000,paired source-video group resample,,,,,,,,,, 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+C0,0.5/sync,mae,0.7872942686080933,0.7879667282104492,0.7290615335106849,0.8417998239398002,1000,paired source-video group resample,0.05388033390045166,0.0537683367729187,0.03128764927387238,0.0756556123495102,,,,,, +C0,0.5/sync,rmse,1.0023715389261885,1.001544129310977,0.932625647165041,1.070238686881361,1000,paired source-video group resample,,,,,,,,,, +C0,0.5/sync,pearson,0.4796582758426666,0.47919368743896484,0.4133769772946835,0.5425243675708771,1000,paired source-video group resample,,,,,,,,,, +C0,0.5/partial,accuracy,0.5851648351648352,0.585278307022319,0.5465874711440575,0.6209588155207625,1000,paired source-video group resample,,,,,,,,,, +C0,0.5/partial,macro_f1,0.5515962307394311,0.5505789759599358,0.5108209497372241,0.5886072439423857,1000,paired source-video group resample,,,,,,,,,, +C0,0.5/partial,mae,0.7854591012001038,0.785031259059906,0.7337380349636078,0.8392841771245003,1000,paired source-video group resample,0.05204516649246216,0.052543312311172485,0.03242650479078293,0.07344547510147094,,,,,, +C0,0.5/partial,rmse,0.9996107953364488,0.9986603523511963,0.9333316577041335,1.0686721957429668,1000,paired source-video group resample,,,,,,,,,, +C0,0.5/partial,pearson,0.4814056158065796,0.47973431646823883,0.409085301309824,0.5458405420184135,1000,paired source-video group resample,,,,,,,,,, +C0,0.5/async,accuracy,0.5728021978021978,0.572864647980833,0.5331086842210011,0.6110562459822217,1000,paired source-video group resample,,,,,,,,,, +C0,0.5/async,macro_f1,0.5406479964345268,0.5401584152675544,0.5011365166623174,0.5778814079473956,1000,paired source-video group resample,,,,,,,,,, +C0,0.5/async,mae,0.7932646870613098,0.7936233878135681,0.7412847965955734,0.845701678097248,1000,paired source-video group resample,0.05985075235366821,0.05992969870567322,0.032877863943576814,0.08415799587965012,,,,,, +C0,0.5/async,rmse,1.0033277336441708,1.0029888168037173,0.9343747105362151,1.0713249030776377,1000,paired source-video group resample,,,,,,,,,, +C0,0.5/async,pearson,0.47449469566345215,0.47415441274642944,0.4123947128653526,0.5335459366440772,1000,paired source-video group resample,,,,,,,,,, +C0,0.7/single,accuracy,0.5851648351648352,0.5846548519764316,0.5458183081186745,0.6234838173018754,1000,paired source-video group resample,,,,,,,,,, +C0,0.7/single,macro_f1,0.551310972502497,0.5500546218183084,0.5114092821483914,0.588444767065762,1000,paired source-video group resample,,,,,,,,,, +C0,0.7/single,mae,0.7879486083984375,0.7871574461460114,0.7349628403782844,0.8415876895189285,1000,paired source-video group resample,0.0545346736907959,0.05517569184303284,0.0343117892742157,0.07424644529819488,,,,,, +C0,0.7/single,rmse,1.0103239954239285,1.009774148313566,0.9436571941012704,1.0805781947785238,1000,paired source-video group resample,,,,,,,,,, +C0,0.7/single,pearson,0.4726402163505554,0.47196105122566223,0.40959134250879287,0.5330896362662315,1000,paired source-video group resample,,,,,,,,,, +C0,0.7/sync,accuracy,0.5824175824175825,0.5815040247151522,0.5400754951256683,0.6230885092324592,1000,paired source-video group resample,,,,,,,,,, +C0,0.7/sync,macro_f1,0.5489395001003641,0.5484809350831173,0.5071365841014068,0.588687591393492,1000,paired source-video group resample,,,,,,,,,, +C0,0.7/sync,mae,0.78337162733078,0.7824246883392334,0.7319780841469765,0.8363745912909508,1000,paired source-video group resample,0.04995769262313843,0.05014631152153015,0.017902542650699616,0.08152804970741272,,,,,, +C0,0.7/sync,rmse,1.0201554415572975,1.0181015861246334,0.9563419989753845,1.0832343142084777,1000,paired source-video group resample,,,,,,,,,, +C0,0.7/sync,pearson,0.47844505310058594,0.4773623049259186,0.41427435725927353,0.5355092942714691,1000,paired source-video group resample,,,,,,,,,, +C0,0.7/partial,accuracy,0.5934065934065934,0.5934611825275911,0.5513379565261624,0.6335674931129477,1000,paired source-video group resample,,,,,,,,,, +C0,0.7/partial,macro_f1,0.5640134372166105,0.5631730030761501,0.5234491524495954,0.603494732761735,1000,paired source-video group resample,,,,,,,,,, +C0,0.7/partial,mae,0.7975913286209106,0.7980578243732452,0.7509397983551025,0.8481855243444443,1000,paired source-video group resample,0.06417739391326904,0.06474125385284424,0.032609406113624576,0.09440396428108215,,,,,, +C0,0.7/partial,rmse,1.0174566917669159,1.0174025887353588,0.9612098945585245,1.079298111426934,1000,paired source-video group resample,,,,,,,,,, +C0,0.7/partial,pearson,0.49247682094573975,0.49154461920261383,0.4322598338127136,0.5482916757464409,1000,paired source-video group resample,,,,,,,,,, +C0,0.7/async,accuracy,0.5782967032967034,0.5783731579542457,0.540939763001975,0.614189956725568,1000,paired source-video group resample,,,,,,,,,, +C0,0.7/async,macro_f1,0.5537980630079038,0.5524206913819412,0.5172529591063677,0.5879905798342243,1000,paired source-video group resample,,,,,,,,,, +C0,0.7/async,mae,0.816459596157074,0.815394252538681,0.7677657306194305,0.8668210163712502,1000,paired source-video group resample,0.08304566144943237,0.08312463760375977,0.050506260991096494,0.11657980978488922,,,,,, +C0,0.7/async,rmse,1.0407948787743542,1.0398551951253658,0.9761384000841079,1.1073867799902082,1000,paired source-video group resample,,,,,,,,,, +C0,0.7/async,pearson,0.479196161031723,0.4796295464038849,0.4122688204050064,0.5425969138741493,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/modality_T,accuracy,0.5865384615384616,0.5868977048183615,0.5440477013480816,0.6256964926721083,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/modality_T,macro_f1,0.5467633134437068,0.5469508250577642,0.504340943447624,0.5833537690089519,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/modality_T,mae,0.7501237392425537,0.7492293417453766,0.6983880028128624,0.8041570410132408,1000,paired source-video group resample,0.01670980453491211,0.01683381199836731,-0.0007769048213958733,0.03351822495460509,,,,,, +C0,0.3/modality_T,rmse,0.9626693316541206,0.9613745705579496,0.8931720109235198,1.0325612258862797,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/modality_T,pearson,0.5017623901367188,0.5024878978729248,0.43672759756445884,0.5639036118984222,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/modality_A,accuracy,0.5865384615384616,0.5869883231106352,0.5445373527745174,0.6255320675234287,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/modality_A,macro_f1,0.5514817686598973,0.551358299046127,0.5112791627545656,0.5896500819010899,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/modality_A,mae,0.730167031288147,0.7294757068157196,0.6796775966882705,0.7815555021166801,1000,paired source-video group resample,-0.003246903419494629,-0.0032376646995544434,-0.006811410188674927,0.000559212267398834,,,,,, +C0,0.3/modality_A,rmse,0.9343123603160799,0.9334206999169543,0.8718232926789852,1.0015177710966405,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/modality_A,pearson,0.5227370262145996,0.5221547782421112,0.4581941328942776,0.5798648074269295,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/modality_V,accuracy,0.5879120879120879,0.5882352941176471,0.5452133635657964,0.6257601287982993,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/modality_V,macro_f1,0.5510933459828488,0.5505514731237747,0.5100285283106513,0.5863376551588455,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/modality_V,mae,0.7333331108093262,0.7327874600887299,0.6832521721720696,0.7861124500632286,1000,paired source-video group resample,-8.082389831542969e-05,-3.49581241607666e-05,-0.00333121120929718,0.00303499698638916,,,,,, +C0,0.3/modality_V,rmse,0.9377927323126264,0.936391316926479,0.8756882203456343,1.0025616214871589,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/modality_V,pearson,0.5194458365440369,0.5187852680683136,0.4549674570560455,0.5766783311963082,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/modality_TA,accuracy,0.5865384615384616,0.5858187571416015,0.5479942260768729,0.6239593828404354,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/modality_TA,macro_f1,0.5541982871602928,0.5528531171393636,0.514519755849559,0.5897836102840824,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/modality_TA,mae,0.7755855321884155,0.7754268646240234,0.7263371974229813,0.8280537679791451,1000,paired source-video group resample,0.042171597480773926,0.04231175780296326,0.025320489704608918,0.059436270594596864,,,,,, +C0,0.3/modality_TA,rmse,0.9706210863534368,0.9704207307333601,0.9082927117320581,1.0356065381388861,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/modality_TA,pearson,0.4984399676322937,0.496877059340477,0.43771328404545784,0.557022488117218,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/modality_TV,accuracy,0.5824175824175825,0.5824175824175825,0.5406466647508891,0.6232893028155141,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/modality_TV,macro_f1,0.5448445879888583,0.5437979886962516,0.50428724304325,0.5839755688868408,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/modality_TV,mae,0.7606737613677979,0.7605727016925812,0.7116958424448967,0.8141574680805206,1000,paired source-video group resample,0.02725982666015625,0.027388781309127808,0.011734052002429963,0.04389871209859847,,,,,, +C0,0.3/modality_TV,rmse,0.9675670908058889,0.966504152828732,0.9065352599302711,1.0356791957154403,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/modality_TV,pearson,0.4989868104457855,0.4982392340898514,0.4351269952952862,0.5587685331702232,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/modality_AV,accuracy,0.5947802197802198,0.5952722372078404,0.5512028706861108,0.6341844801416646,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/modality_AV,macro_f1,0.5596982062391122,0.5590233313747638,0.5165259107071636,0.5974962456738454,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/modality_AV,mae,0.737980842590332,0.7371677756309509,0.6884355857968331,0.7903782784938812,1000,paired source-video group resample,0.00456690788269043,0.004486411809921265,-0.000851413607597351,0.009459361433982847,,,,,, +C0,0.3/modality_AV,rmse,0.9420352275015905,0.9403404121662338,0.8772089804307608,1.007942770777815,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/modality_AV,pearson,0.5155339241027832,0.5148613154888153,0.4498023234307766,0.5737634435296058,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/modality_TAV,accuracy,0.5810439560439561,0.5812458219012349,0.5382375920518205,0.6224332733898065,1000,paired source-video group resample,,,,,,,,,, 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resample,,,,,,,,,, +C0,0.3/location_start_T,mae,0.7692611813545227,0.7692047655582428,0.7216728016734123,0.8238860502839088,1000,paired source-video group resample,0.035847246646881104,0.03549319505691528,0.014010483026504516,0.05833979398012161,,,,,, +C0,0.3/location_start_T,rmse,0.9753139296120601,0.9733350598780712,0.9119715355687452,1.0456409618511735,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/location_start_T,pearson,0.4825494587421417,0.48262427747249603,0.4188865438103676,0.5431592732667923,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/location_middle_T,accuracy,0.5892857142857143,0.5897794354503043,0.5480512046702617,0.6296864337347943,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/location_middle_T,macro_f1,0.5508015036863169,0.5505142685647595,0.5082449155977485,0.5884580767511477,1000,paired source-video group resample,,,,,,,,,, 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resample,0.03573894500732422,0.03601694107055664,0.020976094901561736,0.04921115189790726,,,,,, +C0,0.3/location_end_T,rmse,0.9775325687280407,0.9772966744844532,0.9152103259727273,1.0438003135508174,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/location_end_T,pearson,0.5066846013069153,0.5066242814064026,0.43873843997716905,0.5647416234016418,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/span_long_T,accuracy,0.5782967032967034,0.5788415592438159,0.5370577822733594,0.619323720227515,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/span_long_T,macro_f1,0.5401044750700011,0.539431139471737,0.4997053299775685,0.5766794790270765,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/span_long_T,mae,0.7491215467453003,0.7480838000774384,0.7003185048699379,0.8056073412299156,1000,paired source-video group resample,0.01570761203765869,0.01627400517463684,-0.0005773216485977172,0.032228642702102656,,,,,, +C0,0.3/span_long_T,rmse,0.9638979210248702,0.9615168178970414,0.8985743563953495,1.035487493803704,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/span_long_T,pearson,0.4999791085720062,0.5002008378505707,0.432734590023756,0.5576226696372032,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/span_multi_short_T,accuracy,0.5879120879120879,0.5878715185935824,0.544703678773157,0.6288220861657589,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/span_multi_short_T,macro_f1,0.5515444552866183,0.550478381803812,0.5075975240879186,0.5906755160712447,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/span_multi_short_T,mae,0.751455545425415,0.7511257231235504,0.7019509479403496,0.8058795526623725,1000,paired source-video group resample,0.018041610717773438,0.01796582341194153,0.004412245750427246,0.032249616086482996,,,,,, +C0,0.3/span_multi_short_T,rmse,0.9606981056803815,0.9597029468437807,0.8991442258979647,1.0249805829373453,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/span_multi_short_T,pearson,0.5016085505485535,0.5012595951557159,0.43685516268014907,0.5619709879159928,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/location_start_A,accuracy,0.5837912087912088,0.5844780997380875,0.5438017840870942,0.6180296527506829,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/location_start_A,macro_f1,0.5567801603972272,0.5558237972490165,0.5174591916955337,0.5901795504627572,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/location_start_A,mae,0.734998345375061,0.7347342669963837,0.6843274548649788,0.7872175872325897,1000,paired source-video group resample,0.0015844106674194336,0.0019435882568359375,-0.009833616018295287,0.013556665182113646,,,,,, +C0,0.3/location_start_A,rmse,0.9407973476946676,0.939182297968018,0.8773718996820868,1.0078729812772407,1000,paired source-video group resample,,,,,,,,,, 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source-video group resample,,,,,,,,,, +C0,0.3/location_end_A,accuracy,0.5892857142857143,0.5897794354503043,0.5469834273120188,0.6271915363381859,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/location_end_A,macro_f1,0.5533991612650587,0.5532115195376897,0.5120324673827898,0.5894904317105034,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/location_end_A,mae,0.7347469329833984,0.7342273592948914,0.6847380340099335,0.7877286106348038,1000,paired source-video group resample,0.001332998275756836,0.0012920200824737549,-0.0004923716187477112,0.003071559965610504,,,,,, +C0,0.3/location_end_A,rmse,0.9376694208283924,0.936253879803539,0.8751408189179217,1.0029901596006174,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/location_end_A,pearson,0.5189513564109802,0.5180747509002686,0.45363258570432663,0.5763091802597046,1000,paired source-video group resample,,,,,,,,,, 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resample,,,,,,,,,, +C0,0.3/span_multi_short_A,macro_f1,0.5602778355840083,0.5593483050126009,0.5186010293338358,0.5975928379157248,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/span_multi_short_A,mae,0.7361240386962891,0.7356792092323303,0.6860612720251084,0.7874566465616226,1000,paired source-video group resample,0.002710103988647461,0.002726912498474121,-0.00021516680717468257,0.005898411571979521,,,,,, +C0,0.3/span_multi_short_A,rmse,0.9416461496452981,0.9403572956730086,0.8784404452739102,1.007914005585068,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/span_multi_short_A,pearson,0.51630038022995,0.5157170295715332,0.45008379518985747,0.5742584750056267,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/location_start_V,accuracy,0.5961538461538461,0.5966142771016015,0.5525981834107122,0.6349465471100681,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/location_start_V,macro_f1,0.5638106737699603,0.563349847682696,0.5194449118031244,0.6004159203697161,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/location_start_V,mae,0.7334464192390442,0.732193261384964,0.684023642539978,0.7862200424075126,1000,paired source-video group resample,3.248453140258789e-05,1.2367963790893555e-05,-0.0063155293464660645,0.0060240700840949995,,,,,, +C0,0.3/location_start_V,rmse,0.93684132007121,0.9363950884686267,0.8716905703123498,1.0020920371280724,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/location_start_V,pearson,0.5210404396057129,0.5201423168182373,0.45783004984259607,0.5790509834885597,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/location_middle_V,accuracy,0.592032967032967,0.5933006077606358,0.5502467890978842,0.6313437455090435,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/location_middle_V,macro_f1,0.5557089790364161,0.555495711783167,0.5156059997233736,0.592820329656755,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/location_middle_V,mae,0.7338100671768188,0.7335964441299438,0.6831013143062592,0.7863773599267005,1000,paired source-video group resample,0.0003961324691772461,0.0004449784755706787,-0.004254423081874847,0.004909633100032806,,,,,, +C0,0.3/location_middle_V,rmse,0.938881206308593,0.9377410419168435,0.8764280962158272,1.0023883088430898,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/location_middle_V,pearson,0.5190234780311584,0.5185801386833191,0.4547866776585579,0.5766222849488258,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/location_end_V,accuracy,0.5892857142857143,0.5899027159193355,0.5468964368964369,0.627431161929423,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/location_end_V,macro_f1,0.5532763948706718,0.5526087244163961,0.5116344103303895,0.5893993057904876,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/location_end_V,mae,0.7332183718681335,0.7325971126556396,0.682795412838459,0.7863547876477242,1000,paired source-video group resample,-0.00019556283950805664,-0.00013950467109680176,-0.0027480289340019227,0.0022503063082695007,,,,,, +C0,0.3/location_end_V,rmse,0.9374444945116602,0.9356091820495958,0.8749493032750345,1.0024175522794607,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/location_end_V,pearson,0.5191484093666077,0.5186847746372223,0.45382630079984665,0.5765411570668221,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/span_long_V,accuracy,0.5851648351648352,0.585499316005472,0.5436926956371364,0.6231616920972556,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/span_long_V,macro_f1,0.5486135167681166,0.5483085016892868,0.5086236903195144,0.5848575446662412,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/span_long_V,mae,0.7343583106994629,0.73396897315979,0.684272187948227,0.78722335845232,1000,paired source-video group resample,0.0009443759918212891,0.000996232032775879,-0.002809832990169525,0.004614251852035523,,,,,, +C0,0.3/span_long_V,rmse,0.9378321377186339,0.9367673468566919,0.8752057408070469,1.0028643609635708,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/span_long_V,pearson,0.5198805928230286,0.519171416759491,0.45469643399119375,0.5767942205071449,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/span_multi_short_V,accuracy,0.5879120879120879,0.5884460002007428,0.5451963059233226,0.6263713700519143,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/span_multi_short_V,macro_f1,0.5514593178309082,0.5512597468470319,0.5115271125417841,0.5877679335270468,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/span_multi_short_V,mae,0.7336029410362244,0.7329019904136658,0.6839076906442643,0.7864472061395645,1000,paired source-video group resample,0.00018900632858276367,0.0002028048038482666,-0.002440623939037323,0.00268939733505249,,,,,, +C0,0.3/span_multi_short_V,rmse,0.9379328364319036,0.9364543152595417,0.8755152433669064,1.0040118536109057,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/span_multi_short_V,pearson,0.5195159912109375,0.5187688767910004,0.45459923669695856,0.57720016092062,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/synchrony_sync,accuracy,0.5879120879120879,0.5878081579657359,0.5444808474169901,0.6277229350832881,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/synchrony_sync,macro_f1,0.5489522310137621,0.5484116762996994,0.5050479763671211,0.5903541134395667,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/synchrony_sync,mae,0.7429406046867371,0.7429458200931549,0.693758949637413,0.7941453367471695,1000,paired source-video group resample,0.009526669979095459,0.009618550539016724,-0.006899794936180114,0.028126744925975798,,,,,, +C0,0.3/synchrony_sync,rmse,0.9513932113518331,0.9515840387715486,0.8870108109713848,1.0157183805106846,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/synchrony_sync,pearson,0.5149245262145996,0.5138374269008636,0.44743722230196,0.5740262866020203,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/synchrony_partial,accuracy,0.592032967032967,0.592772671604137,0.5496131913366944,0.6318729552889858,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/synchrony_partial,macro_f1,0.5568489272763009,0.5553280383763097,0.5150569824382639,0.5967672529344766,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/synchrony_partial,mae,0.7549550533294678,0.7542287707328796,0.7041897296905517,0.8057735577225685,1000,paired source-video group resample,0.021541118621826172,0.02098509669303894,0.008437594771385193,0.03572680503129959,,,,,, +C0,0.3/synchrony_partial,rmse,0.9537479991066918,0.9527588591789573,0.8905198374994483,1.0212281846680489,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/synchrony_partial,pearson,0.5077442526817322,0.5080030858516693,0.4416636176407337,0.5686416462063789,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/synchrony_async,accuracy,0.5947802197802198,0.5954208402545198,0.5535200823734622,0.6341472556404725,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/synchrony_async,macro_f1,0.5573497451357863,0.5566971866287648,0.5178464140734533,0.5952177188293901,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/synchrony_async,mae,0.7572227716445923,0.756513237953186,0.7077751472592354,0.8130751132965088,1000,paired source-video group resample,0.023808836936950684,0.023322194814682007,0.0042680025100708015,0.04232407212257385,,,,,, +C0,0.3/synchrony_async,rmse,0.9670903848875563,0.9656717947187008,0.9039646164170754,1.0329391067568396,1000,paired source-video group resample,,,,,,,,,, +C0,0.3/synchrony_async,pearson,0.4977172315120697,0.49830037355422974,0.43059912249445914,0.5547494515776634,1000,paired source-video group resample,,,,,,,,,, +C1,0.0/none,accuracy,0.6071428571428571,0.6066806136680614,0.5718096540941958,0.6454950255171821,1000,paired source-video group resample,,,,,C0,0.015109890109890056,0.01539255152568586,-0.020128293154307857,0.04987543477796981, +C1,0.0/none,macro_f1,0.55124288334091,0.5492718103862674,0.5147095481324242,0.5902919580696836,1000,paired source-video group resample,,,,,C0,-0.004691729310120518,-0.004485551803879773,-0.04536919044472238,0.03742003330852176, +C1,0.0/none,mae,0.6779899001121521,0.6775488555431366,0.6251160457730294,0.7299595981836319,1000,paired source-video group resample,,,,,C0,-0.0554240345954895,-0.05605274438858032,-0.09268802553415298,-0.016779425740242014, +C1,0.0/none,rmse,0.9222378420815579,0.9198942726887666,0.8389632929540463,1.0016835697644408,1000,paired source-video group resample,,,,,C0,-0.014935817346632296,-0.017472698654026064,-0.071965976752543,0.04424844109596132, +C1,0.0/none,pearson,0.5779994130134583,0.5789379775524139,0.5050718456506729,0.6441612392663956,1000,paired source-video group resample,,,,,C0,0.05875682830810547,0.059891462326049805,0.005193436145782472,0.11252264082431793, +C1,0.1/single,accuracy,0.6071428571428571,0.6067867772108844,0.5723771068074017,0.6442195212147741,1000,paired source-video group resample,,,,,C0,0.019230769230769162,0.020235237515162985,-0.015110930735930792,0.05487077475677341, +C1,0.1/single,macro_f1,0.5514660777818672,0.5496136851765465,0.5147094287260956,0.5903211526645042,1000,paired source-video group resample,,,,,C0,0.001581280344960856,0.0021339411318024304,-0.03777989283229387,0.04275037256185954, +C1,0.1/single,mae,0.6766936182975769,0.6764801740646362,0.6238366395235062,0.7288129955530166,1000,paired source-video group resample,-0.0012962818145751953,-0.0013050436973571777,-0.004702091217041016,0.001740024983882904,C0,-0.05906558036804199,-0.05983257293701172,-0.09707283824682236,-0.020978647470474246, +C1,0.1/single,rmse,0.9191093663235302,0.9169664450500502,0.8361660509431462,0.9980868549802342,1000,paired source-video group resample,,,,,C0,-0.020213209237716967,-0.02220025714811913,-0.07850429223277626,0.03810965646075093, +C1,0.1/single,pearson,0.5788683891296387,0.5800404846668243,0.507444652915001,0.644332654774189,1000,paired source-video group resample,,,,,C0,0.06229287385940552,0.06349948048591614,0.008841851353645324,0.11674096807837485, +C1,0.1/sync,accuracy,0.6043956043956044,0.6041966250917095,0.5680583078743842,0.6431624844746647,1000,paired source-video group resample,,,,,C0,0.017857142857142794,0.018143833881995475,-0.020012995896032743,0.05271104830232644, +C1,0.1/sync,macro_f1,0.5450356863221074,0.5439908398730005,0.5080468129753906,0.5861390386780814,1000,paired source-video group resample,,,,,C0,-0.005292376772645824,-0.004958350775715603,-0.04841944522517047,0.04032591706748356, +C1,0.1/sync,mae,0.6741200685501099,0.6732602417469025,0.6243683293461799,0.7257550477981567,1000,paired source-video group resample,-0.0038698315620422363,-0.0039826929569244385,-0.01836119145154953,0.01070696413516998,C0,-0.06092280149459839,-0.061326026916503906,-0.09934347122907639,-0.02154844403266908, +C1,0.1/sync,rmse,0.920004320600979,0.9183960393573338,0.8352714574207845,1.0003654466516843,1000,paired source-video group resample,,,,,C0,-0.025178943754307626,-0.02730669919416573,-0.08562278114301651,0.034702123280553526, +C1,0.1/sync,pearson,0.5772114992141724,0.5776531398296356,0.5103264972567558,0.6398999884724617,1000,paired source-video group resample,,,,,C0,0.06381165981292725,0.06530867516994476,0.00770525485277176,0.12158355936408043, +C1,0.1/partial,accuracy,0.6057692307692307,0.6055563723024784,0.5708251131953428,0.6419831067769897,1000,paired source-video group resample,,,,,C0,0.012362637362637319,0.013159920259234403,-0.02401214849087812,0.046634876484316565, +C1,0.1/partial,macro_f1,0.5487496665001256,0.5477075127532796,0.514350539807512,0.5871609884557909,1000,paired source-video group resample,,,,,C0,-0.00888327150317969,-0.008328464816810821,-0.04956423408202698,0.031116947974575156, +C1,0.1/partial,mae,0.6784517168998718,0.6785793304443359,0.6272698655724526,0.7318008184432984,1000,paired source-video group resample,0.00046181678771972656,0.00020623207092285156,-0.007018882036209107,0.010675629973411559,C0,-0.05676567554473877,-0.05748751759529114,-0.09379137754440307,-0.016629552841186526, +C1,0.1/partial,rmse,0.9249676698756809,0.9229618517308691,0.8420846996933459,1.0040904012889869,1000,paired source-video group resample,,,,,C0,-0.01247577553153112,-0.014146844307858841,-0.06649764506833801,0.04780026609974715, +C1,0.1/partial,pearson,0.569713830947876,0.5706944763660431,0.4976207375526428,0.6304143592715263,1000,paired source-video group resample,,,,,C0,0.04914027452468872,0.05061647295951843,-0.011827524006366729,0.10279335156083107, +C1,0.1/async,accuracy,0.6016483516483516,0.6008290851625437,0.5651513991854071,0.6394885455666149,1000,paired source-video group resample,,,,,C0,0.009615384615384581,0.009824604947464233,-0.02652327577012199,0.04310888882477668, +C1,0.1/async,macro_f1,0.5446197183098591,0.5425035176075634,0.5078380862559527,0.5832407895833654,1000,paired source-video group resample,,,,,C0,-0.014187303569548004,-0.014425556174784138,-0.054333188530978474,0.02596920828590946, +C1,0.1/async,mae,0.6867530941963196,0.6860127449035645,0.6337538197636604,0.7413154512643814,1000,paired source-video group resample,0.00876319408416748,0.008654981851577759,-0.006453171372413635,0.02698029726743698,C0,-0.05214053392410278,-0.052502959966659546,-0.09017047733068466,-0.014427591860294357, +C1,0.1/async,rmse,0.9348675963548172,0.9320346865050797,0.8523887038363116,1.0176110814407962,1000,paired source-video group resample,,,,,C0,-0.00886704494270718,-0.00948979839532349,-0.06262354123482154,0.047683168947792384, +C1,0.1/async,pearson,0.5607475638389587,0.5613925457000732,0.49125813618302344,0.6243762597441673,1000,paired source-video group resample,,,,,C0,0.04673159122467041,0.04728540778160095,-0.00846850872039795,0.09999658465385436, +C1,0.3/single,accuracy,0.6016483516483516,0.6013254333991661,0.566852009652634,0.6392086272204807,1000,paired source-video group resample,,,,,C0,-0.004120879120879106,-0.004222380697688266,-0.039837908303817365,0.029093695623075858, +C1,0.3/single,macro_f1,0.543169806046322,0.5415415701005017,0.5059419380334599,0.5841510673801928,1000,paired source-video group resample,,,,,C0,-0.026129443362126192,-0.02705421510638789,-0.06954917621369501,0.014957987503633837, +C1,0.3/single,mae,0.6973317265510559,0.6967107951641083,0.6478265538811684,0.7506953343749047,1000,paired source-video group resample,0.01934182643890381,0.018960624933242798,0.005614547431468964,0.036523875594139096,C0,-0.03379940986633301,-0.03410622477531433,-0.07367071509361267,0.007001043856143943, +C1,0.3/single,rmse,0.9538067427588233,0.9527756236348233,0.8675340169718566,1.0360484056824777,1000,paired source-video group resample,,,,,C0,0.014039168025278381,0.01272090560331035,-0.04848636402780246,0.08026610974576427, +C1,0.3/single,pearson,0.546376645565033,0.5460211932659149,0.469785400480032,0.6129250571131706,1000,paired source-video group resample,,,,,C0,0.02496105432510376,0.02632082998752594,-0.03902935534715653,0.08453152179718014, +C1,0.3/sync,accuracy,0.5892857142857143,0.5886581403701425,0.5525504291080259,0.6290574947283413,1000,paired source-video group resample,,,,,C0,0.009615384615384581,0.01025645979854184,-0.024390243902439046,0.04122445601276007, +C1,0.3/sync,macro_f1,0.5233475950298133,0.5225536987837501,0.48759942541594664,0.5608070722403254,1000,paired source-video group resample,,,,,C0,-0.016753394409674494,-0.016845170077260108,-0.054651137585459884,0.019584278182182537, +C1,0.3/sync,mae,0.7077845335006714,0.7082108557224274,0.6537623509764672,0.759605522453785,1000,paired source-video group resample,0.029794633388519287,0.029975444078445435,0.005181710422039032,0.053340493142604826,C0,-0.04511916637420654,-0.04633885622024536,-0.08659364879131318,-0.006069664657115955, +C1,0.3/sync,rmse,0.9621357154105765,0.9608984682642637,0.8814876438881731,1.043704706907709,1000,paired source-video group resample,,,,,C0,-0.00015700035370080911,-0.0018373578314723193,-0.058101943885406064,0.05861273139633754, +C1,0.3/sync,pearson,0.5361393094062805,0.536507785320282,0.46591409146785734,0.5979599550366401,1000,paired source-video group resample,,,,,C0,0.03790438175201416,0.03949663043022156,-0.02019546926021576,0.09589390233159063, +C1,0.3/partial,accuracy,0.6016483516483516,0.6009515327558677,0.5646055840227189,0.6412127239694274,1000,paired source-video group resample,,,,,C0,0.006868131868131844,0.007007711920672899,-0.03011767613398732,0.04155568444996722, +C1,0.3/partial,macro_f1,0.5393356408120263,0.5368123507608161,0.5030856960853145,0.5782583669371769,1000,paired source-video group resample,,,,,C0,-0.023900006831443,-0.02454852683064479,-0.06669790562071481,0.017474386415154787, +C1,0.3/partial,mae,0.7009829878807068,0.7014274895191193,0.6489140078425407,0.7532161325216293,1000,paired source-video group resample,0.022993087768554688,0.022717326879501343,0.006419435143470764,0.04191082417964935,C0,-0.04556870460510254,-0.04551059007644653,-0.086253422498703,-0.00460282862186432, +C1,0.3/partial,rmse,0.9508501640677943,0.9504740221791048,0.8655704626959346,1.0295148167778647,1000,paired source-video group resample,,,,,C0,-0.0019480291961817553,-0.002023820175832358,-0.06294833387496443,0.056567995419390164, +C1,0.3/partial,pearson,0.5471457839012146,0.5489107072353363,0.4792665742337704,0.609665684401989,1000,paired source-video group resample,,,,,C0,0.03843200206756592,0.03816613554954529,-0.018733289837837216,0.09645923450589179, +C1,0.3/async,accuracy,0.6085164835164835,0.6074899579851332,0.5719749033079812,0.6483117433414044,1000,paired source-video group resample,,,,,C0,0.028846153846153744,0.02924659869216223,-0.00657588163457693,0.06503286018936458, +C1,0.3/async,macro_f1,0.5466891151849613,0.545075648385647,0.5112569823094474,0.5829929348307772,1000,paired source-video group resample,,,,,C0,0.0005386446362863895,0.0007796920821138698,-0.03752496924561828,0.040744770933257526, +C1,0.3/async,mae,0.6993565559387207,0.698672354221344,0.6383380442857742,0.7587631210684777,1000,paired source-video group resample,0.021366655826568604,0.020924001932144165,-0.001980505883693695,0.04715982973575592,C0,-0.06922686100006104,-0.07070297002792358,-0.11386552006006241,-0.02328669875860216, +C1,0.3/async,rmse,0.9681702386421676,0.9674776550934897,0.8780172551929161,1.0583929531961598,1000,paired source-video group resample,,,,,C0,-0.01493455591376247,-0.01616956581009682,-0.07972962986505983,0.05432392850024326, +C1,0.3/async,pearson,0.5308828353881836,0.5305867493152618,0.45628157183527945,0.5985768586397171,1000,paired source-video group resample,,,,,C0,0.04403689503669739,0.0442117303609848,-0.020181912183761593,0.10924321115016937, +C1,0.5/single,accuracy,0.6057692307692307,0.60546875,0.5669354275335321,0.6452602216219534,1000,paired source-video group resample,,,,,C0,0.019230769230769162,0.019097890214184954,-0.015198689973226848,0.05595645309827663, +C1,0.5/single,macro_f1,0.5486895170750463,0.5469898390122179,0.5089927416206346,0.5878636741772768,1000,paired source-video group resample,,,,,C0,-0.006327765086836634,-0.006634949160084724,-0.04622984732989407,0.034543838222778525, +C1,0.5/single,mae,0.6980464458465576,0.6976488828659058,0.6435167640447617,0.7539358258247375,1000,paired source-video group resample,0.020056545734405518,0.019747227430343628,0.005394330620765686,0.03831115365028381,C0,-0.050981879234313965,-0.05116182565689087,-0.09102016538381577,-0.010063467919826515, +C1,0.5/single,rmse,0.9519456226803039,0.9499712636429658,0.8619044806307802,1.0367956439124755,1000,paired source-video group resample,,,,,C0,-0.007705214832229634,-0.00862339597231404,-0.06698041099941164,0.05551685180053956, +C1,0.5/single,pearson,0.5495686531066895,0.550152987241745,0.472167382389307,0.6147719502449036,1000,paired source-video group resample,,,,,C0,0.04133540391921997,0.04335464537143707,-0.017485783249139786,0.09641409292817114, +C1,0.5/sync,accuracy,0.6016483516483516,0.6014965834818775,0.5637295424680445,0.6405627705627706,1000,paired source-video group resample,,,,,C0,0.008241758241758212,0.008168856397176627,-0.030088121233079676,0.04447519016003803, +C1,0.5/sync,macro_f1,0.5314802437041053,0.5300292613256742,0.4932187352236502,0.568863930742357,1000,paired source-video group resample,,,,,C0,-0.03202329569207818,-0.032482617352206866,-0.07758516166218986,0.013175022944384529, +C1,0.5/sync,mae,0.7333694100379944,0.7332854270935059,0.6778887689113617,0.7900589734315872,1000,paired source-video group resample,0.055379509925842285,0.055039405822753906,0.028917156159877777,0.0816002756357193,C0,-0.05392485857009888,-0.0545019805431366,-0.09663055837154388,-0.007822680473327653, +C1,0.5/sync,rmse,1.0041580774934478,1.0026831676778643,0.9144537076492512,1.094796479152357,1000,paired source-video group resample,,,,,C0,0.0017865385672592993,-3.964926424249171e-05,-0.05891165417371423,0.0643712635984005, +C1,0.5/sync,pearson,0.5051144957542419,0.5063183903694153,0.43003127723932266,0.5753084182739258,1000,paired source-video group resample,,,,,C0,0.025456219911575317,0.02866177260875702,-0.03430902138352394,0.08456432148814201, +C1,0.5/partial,accuracy,0.5906593406593407,0.5912982413287738,0.5497145079622758,0.6306115220431294,1000,paired source-video group resample,,,,,C0,0.005494505494505475,0.0069305694305694665,-0.03296643333782047,0.0436188293622486, +C1,0.5/partial,macro_f1,0.510259818240831,0.5095118480053682,0.4723362976641021,0.5500372418849496,1000,paired source-video group resample,,,,,C0,-0.041336412498600095,-0.03985919742340838,-0.08517101092665905,0.004791575599781348, +C1,0.5/partial,mae,0.7344207763671875,0.7345760464668274,0.6816359326243401,0.7856301411986351,1000,paired source-video group resample,0.0564308762550354,0.0565924346446991,0.027215096354484557,0.08533611297607421,C0,-0.05103832483291626,-0.052739858627319336,-0.09836586564779282,-0.008098280429840088, +C1,0.5/partial,rmse,0.995874059049196,0.9954038964213221,0.9141754634591089,1.073726780999644,1000,paired source-video group resample,,,,,C0,-0.0037367362872527954,-0.0052422594345256646,-0.06573164999734811,0.055205445527657125, +C1,0.5/partial,pearson,0.5078985691070557,0.5082907378673553,0.4393769852817059,0.576042702794075,1000,paired source-video group resample,,,,,C0,0.026492953300476074,0.028565004467964172,-0.03365049213171005,0.08695457428693767, +C1,0.5/async,accuracy,0.6057692307692307,0.6053001182732112,0.569945291921151,0.6451205877415951,1000,paired source-video group resample,,,,,C0,0.03296703296703296,0.0337154570024481,-0.0012972940272163113,0.06611570247933884, +C1,0.5/async,macro_f1,0.5387719862880588,0.5376336298196753,0.5049018665580851,0.5740657960687836,1000,paired source-video group resample,,,,,C0,-0.001876010146467988,-0.0018241987811111193,-0.03997625237375214,0.03615325532865518, +C1,0.5/async,mae,0.7096429467201233,0.7086494266986847,0.655916778743267,0.7634943470358848,1000,paired source-video group resample,0.03165304660797119,0.03186807036399841,0.0020366996526718145,0.06208253949880599,C0,-0.08362174034118652,-0.08341920375823975,-0.13287434428930284,-0.0339966893196106, +C1,0.5/async,rmse,0.9768790685626316,0.9736137272848604,0.8899028309659779,1.0709217834105786,1000,paired source-video group resample,,,,,C0,-0.026448665081539202,-0.028090690448912548,-0.09633564796405557,0.043971415756412134, +C1,0.5/async,pearson,0.5283164978027344,0.5298514366149902,0.4451109007000923,0.604284231364727,1000,paired source-video group resample,,,,,C0,0.05382180213928223,0.05439405143260956,-0.015390947461128235,0.11783630773425101, +C1,0.7/single,accuracy,0.603021978021978,0.6034086708559963,0.5677524104460738,0.6397752161383286,1000,paired source-video group resample,,,,,C0,0.017857142857142794,0.018915631037855096,-0.018578840970350403,0.05418920520358273, +C1,0.7/single,macro_f1,0.5411976345204939,0.5400492909069294,0.503067467312594,0.5791741602603545,1000,paired source-video group resample,,,,,C0,-0.010113337982003201,-0.009745032591913949,-0.052198193350723704,0.03521425271978881, +C1,0.7/single,mae,0.7227900624275208,0.7225958108901978,0.6687874227762223,0.7752164795994758,1000,paired source-video group resample,0.04480016231536865,0.04459461569786072,0.024817973375320435,0.06496283411979675,C0,-0.06515854597091675,-0.0651639997959137,-0.10628124475479125,-0.023576281964778904, +C1,0.7/single,rmse,0.9774238449929349,0.9761276178053234,0.8987868292599296,1.0520768530259477,1000,paired source-video group resample,,,,,C0,-0.03290015043099359,-0.03390238762087816,-0.08979739570415429,0.023125302635563224, +C1,0.7/single,pearson,0.5305479764938354,0.531703382730484,0.46358142867684365,0.5914499685168266,1000,paired source-video group resample,,,,,C0,0.05790776014328003,0.0593605637550354,0.000256083905696869,0.1166818507015705, +C1,0.7/sync,accuracy,0.5851648351648352,0.5853341761483355,0.5455407038848598,0.6275598208515832,1000,paired source-video group resample,,,,,C0,0.0027472527472527375,0.003952630921134848,-0.03498926447801466,0.04115267325758697, +C1,0.7/sync,macro_f1,0.4920533688262833,0.4903981641853802,0.45769597196755263,0.5287460213067727,1000,paired source-video group resample,,,,,C0,-0.056886131274080765,-0.05683859850763745,-0.10001753697976946,-0.012821961606945681, +C1,0.7/sync,mae,0.7864948511123657,0.7866085171699524,0.7249597996473313,0.843836760520935,1000,paired source-video group resample,0.10850495100021362,0.10888418555259705,0.07452981173992157,0.14327656626701352,C0,0.0031232237815856934,0.0032483041286468506,-0.04517508447170258,0.05055140852928161, +C1,0.7/sync,rmse,1.045739996241891,1.044423206213002,0.9539206681882761,1.135293255630049,1000,paired source-video group resample,,,,,C0,0.02558455468459342,0.024334756577041428,-0.04298706888514142,0.086121865448942, +C1,0.7/sync,pearson,0.4775053858757019,0.4778573662042618,0.39639869779348375,0.551393224298954,1000,paired source-video group resample,,,,,C0,-0.0009396672248840332,0.0003573000431060791,-0.05907152593135834,0.06150080040097235, +C1,0.7/partial,accuracy,0.5906593406593407,0.5909392732101896,0.5520892711632555,0.6299465492411654,1000,paired source-video group resample,,,,,C0,-0.0027472527472527375,-0.0024435024032002373,-0.04221687603900674,0.03243462975170292, +C1,0.7/partial,macro_f1,0.5030872922067267,0.502055982684805,0.46679136256532355,0.5405314238922172,1000,paired source-video group resample,,,,,C0,-0.0609261450098838,-0.06023391228441999,-0.10373300086946215,-0.019778022321488696, +C1,0.7/partial,mae,0.7729265093803406,0.7729158997535706,0.7229848667979241,0.8291360452771187,1000,paired source-video group resample,0.09493660926818848,0.0946824848651886,0.060219526290893555,0.13103365451097487,C0,-0.02466481924057007,-0.02608439326286316,-0.07044650614261627,0.021696184575557692, +C1,0.7/partial,rmse,1.0172805790424229,1.0151626111157057,0.9351956173754961,1.0981398414264958,1000,paired source-video group resample,,,,,C0,-0.00017611272449302717,-0.0021486332650946793,-0.06258234466204741,0.0632347929075265, +C1,0.7/partial,pearson,0.49939295649528503,0.49969498813152313,0.4230660326778889,0.566290844976902,1000,paired source-video group resample,,,,,C0,0.006916135549545288,0.00858326256275177,-0.05913596674799919,0.06903589740395545, +C1,0.7/async,accuracy,0.5865384615384616,0.5869718959473587,0.5449877471239778,0.6288695207366019,1000,paired source-video group resample,,,,,C0,0.008241758241758212,0.009776707949134544,-0.031252128746594006,0.04591767231652463, +C1,0.7/async,macro_f1,0.49543556924259397,0.4950379277970478,0.45876140964332235,0.5317435506855182,1000,paired source-video group resample,,,,,C0,-0.05836249376530983,-0.05793954701125678,-0.10022096052531075,-0.015547663389072139, +C1,0.7/async,mae,0.7762354612350464,0.7760098576545715,0.723600159585476,0.8263284847140312,1000,paired source-video group resample,0.09824556112289429,0.09909674525260925,0.059605872631073,0.13815641850233076,C0,-0.04022413492202759,-0.04059329628944397,-0.09259072840213775,0.011846363544464089, +C1,0.7/async,rmse,1.0292775914161083,1.027557402723689,0.946861445005223,1.1122491075765568,1000,paired source-video group resample,,,,,C0,-0.011517287358245865,-0.013052582552277148,-0.08106914794490544,0.056542385983435764, +C1,0.7/async,pearson,0.4933066666126251,0.49363698065280914,0.4185964331030846,0.5627867132425308,1000,paired source-video group resample,,,,,C0,0.0141105055809021,0.015991732478141785,-0.04944557026028633,0.08012460917234421, +C1,0.3/modality_T,accuracy,0.6085164835164835,0.6078442158534573,0.573470904907836,0.6463132430989418,1000,paired source-video group resample,,,,,C0,0.0219780219780219,0.022292817774894114,-0.010107552205997754,0.056655719902712724, +C1,0.3/modality_T,macro_f1,0.5510444415789368,0.549496993494234,0.5146462026098295,0.589523820250185,1000,paired source-video group resample,,,,,C0,0.004281128135230072,0.0038725574986018807,-0.03726695632952744,0.04532582879192779, +C1,0.3/modality_T,mae,0.7043370604515076,0.7026811242103577,0.647849953174591,0.7617898017168044,1000,paired source-video group resample,0.02634716033935547,0.025432556867599487,0.003187602758407593,0.05170156359672545,C0,-0.04578667879104614,-0.04563266038894653,-0.08899187743663788,-0.003042903542518616, +C1,0.3/modality_T,rmse,0.9833056075557052,0.9808284180105982,0.8847864700117511,1.077959891187403,1000,paired source-video group resample,,,,,C0,0.020636275901584566,0.01881982389952258,-0.04326357088063996,0.07926242880004365, +C1,0.3/modality_T,pearson,0.5090063214302063,0.5100324153900146,0.4301640711724758,0.5812959969043732,1000,paired source-video group resample,,,,,C0,0.007243931293487549,0.008732706308364868,-0.055060626566410066,0.06734095588326448, +C1,0.3/modality_A,accuracy,0.6071428571428571,0.6068496364062866,0.5716185928668875,0.6447378240377062,1000,paired source-video group resample,,,,,C0,0.02060439560439553,0.021382210066538787,-0.01580861193133474,0.05555748725081133, +C1,0.3/modality_A,macro_f1,0.551308204918976,0.5492046365379133,0.5142504040310538,0.5908332315346835,1000,paired source-video group resample,,,,,C0,-0.00017356374092125648,0.000631841982431991,-0.04189737466444206,0.04081279952806213, +C1,0.3/modality_A,mae,0.6800481081008911,0.6796923279762268,0.6271305814385414,0.7331921130418777,1000,paired source-video group resample,0.0020582079887390137,0.0020438730716705322,-0.0010609552264213562,0.005739812552928924,C0,-0.05011892318725586,-0.05099409818649292,-0.0879015564918518,-0.01045995950698853, +C1,0.3/modality_A,rmse,0.9250886475124307,0.9228147145280858,0.8426764066994801,1.0055684497866024,1000,paired source-video group resample,,,,,C0,-0.009223712803649198,-0.011817972842162683,-0.06679174801720546,0.05012155354104824, +C1,0.3/modality_A,pearson,0.5769843459129333,0.5778438448905945,0.5051151841878891,0.6413686096668243,1000,paired source-video group resample,,,,,C0,0.05424731969833374,0.05572305619716644,0.0003105148673057559,0.10795796364545822, +C1,0.3/modality_V,accuracy,0.6071428571428571,0.6066806136680614,0.5718096540941958,0.6454950255171821,1000,paired source-video group resample,,,,,C0,0.019230769230769162,0.019828164643224122,-0.01608264856496363,0.05347141826393937, +C1,0.3/modality_V,macro_f1,0.55124288334091,0.5492718103862674,0.5147095481324242,0.5902919580696836,1000,paired source-video group resample,,,,,C0,0.0001495373580612247,0.000530154023979823,-0.03965206106983507,0.0422723936538458, +C1,0.3/modality_V,mae,0.6780127882957458,0.6776794195175171,0.6251323968172073,0.7301622509956359,1000,paired source-video group resample,2.288818359375e-05,3.5762786865234375e-05,-0.0005571469664573669,0.0006399571895599365,C0,-0.05532032251358032,-0.0560263991355896,-0.09379162639379501,-0.016520893573761002, +C1,0.3/modality_V,rmse,0.9225640065904674,0.9200883853492947,0.8389822123681173,1.0027608616026475,1000,paired source-video group resample,,,,,C0,-0.015228725722158942,-0.017252527428885278,-0.07252917679965426,0.04592800096941518, +C1,0.3/modality_V,pearson,0.5777980089187622,0.5788368880748749,0.5052438050508499,0.6437976241111756,1000,paired source-video group resample,,,,,C0,0.05835217237472534,0.05890652537345886,0.004417772591114045,0.11265389397740362, +C1,0.3/modality_TA,accuracy,0.5934065934065934,0.5930229074807388,0.5575651174668028,0.6320582343188726,1000,paired source-video group resample,,,,,C0,0.006868131868131844,0.007920823138214406,-0.030455163043478197,0.0425897796878088, +C1,0.3/modality_TA,macro_f1,0.5286367566179747,0.5268683229867488,0.4941670321901661,0.5659993304369391,1000,paired source-video group resample,,,,,C0,-0.025561530542318134,-0.024878962678882344,-0.06933524311952584,0.018079221922994677, +C1,0.3/modality_TA,mae,0.70912104845047,0.7090321779251099,0.6550784647464752,0.7627518907189369,1000,paired source-video group resample,0.03113114833831787,0.03066718578338623,0.012050467729568482,0.0556527629494667,C0,-0.06646448373794556,-0.06716477870941162,-0.10751845091581344,-0.026002991199493432, +C1,0.3/modality_TA,rmse,0.9645973848564896,0.9637810093488977,0.878298972288391,1.046319455269168,1000,paired source-video group resample,,,,,C0,-0.006023701496947198,-0.0061790200500964065,-0.06682769623259793,0.05414923757514415, +C1,0.3/modality_TA,pearson,0.530229926109314,0.5315019488334656,0.46217843517661095,0.5943346172571182,1000,paired source-video group resample,,,,,C0,0.031789958477020264,0.03249494731426239,-0.02928766459226608,0.09270521849393844, +C1,0.3/modality_TV,accuracy,0.5947802197802198,0.5942028985507246,0.5564834781675786,0.633756497725796,1000,paired source-video group resample,,,,,C0,0.012362637362637319,0.012256364463323788,-0.025788890578944505,0.04958677685950408, +C1,0.3/modality_TV,macro_f1,0.5349199927403334,0.5335319209424367,0.4970044192211024,0.5767311905648038,1000,paired source-video group resample,,,,,C0,-0.009924595248524848,-0.010233627327322359,-0.05196541144026389,0.03388658080022443, +C1,0.3/modality_TV,mae,0.7021923065185547,0.7021098136901855,0.6479898393154144,0.7562441974878311,1000,paired source-video group resample,0.024202406406402588,0.02364128828048706,0.0015605196356773378,0.051623301208019244,C0,-0.058481454849243164,-0.05959516763687134,-0.10163970440626144,-0.015507726371288328, +C1,0.3/modality_TV,rmse,0.9605139442436464,0.9592487875061737,0.8767466277220706,1.0422585073871373,1000,paired source-video group resample,,,,,C0,-0.007053146562242429,-0.007624345021979062,-0.07336608198548494,0.060111658442334716, +C1,0.3/modality_TV,pearson,0.5306498408317566,0.5321135222911835,0.4531451515853405,0.5964479953050613,1000,paired source-video group resample,,,,,C0,0.03166303038597107,0.03145502507686615,-0.031099822372198105,0.09567964673042295, +C1,0.3/modality_AV,accuracy,0.6153846153846154,0.6151663818236655,0.5816309548574995,0.6534375518586126,1000,paired source-video group resample,,,,,C0,0.020604395604395642,0.021131411985785276,-0.01382353046556458,0.056708896147847236, +C1,0.3/modality_AV,macro_f1,0.5587574855241352,0.5569682897487175,0.5230398359383739,0.5999942258980404,1000,paired source-video group resample,,,,,C0,-0.0009407207149769725,-0.0002813704153279972,-0.04169434020232956,0.043165201509601195, +C1,0.3/modality_AV,mae,0.6755012273788452,0.6740831136703491,0.6238791152834893,0.7291191503405571,1000,paired source-video group resample,-0.0024886727333068848,-0.0026699304580688477,-0.017233985662460326,0.011097009479999538,C0,-0.062479615211486816,-0.06293946504592896,-0.10390295982360839,-0.01881548017263415, +C1,0.3/modality_AV,rmse,0.9220603174703362,0.9200394670669079,0.8378663868989897,1.005820479105509,1000,paired source-video group resample,,,,,C0,-0.01997491003125429,-0.02212709640850108,-0.08291885174289373,0.043577125002633346, +C1,0.3/modality_AV,pearson,0.59040766954422,0.5914927423000336,0.5248964339494705,0.6514851778745652,1000,paired source-video group resample,,,,,C0,0.07487374544143677,0.07662887871265411,0.019854505360126496,0.13078480884432792, +C1,0.3/modality_TAV,accuracy,0.592032967032967,0.5917397285399854,0.5555555555555556,0.6304991883116883,1000,paired source-video group resample,,,,,C0,0.01098901098901095,0.011494252873563204,-0.02553930734639561,0.0485240944053646, +C1,0.3/modality_TAV,macro_f1,0.5306531646273801,0.5292121414394187,0.4939008118594588,0.5706529117886671,1000,paired source-video group resample,,,,,C0,-0.013824733976902093,-0.013824312322497978,-0.05601991809559213,0.03017901796135391, +C1,0.3/modality_TAV,mae,0.7066769599914551,0.706088125705719,0.6522608920931816,0.7595319256186485,1000,paired source-video group resample,0.02868705987930298,0.028076469898223877,0.009229062497615815,0.04935911297798157,C0,-0.0642547607421875,-0.06394344568252563,-0.10813345909118652,-0.02043528854846955, +C1,0.3/modality_TAV,rmse,0.9643625766154194,0.9631947463584765,0.8777748575189547,1.0443057753743201,1000,paired source-video group resample,,,,,C0,-0.01567518504594978,-0.01642008554590535,-0.0744434158563163,0.04196876148547818, +C1,0.3/modality_TAV,pearson,0.5329471230506897,0.5338970124721527,0.46844750046730044,0.5970169022679329,1000,paired source-video group resample,,,,,C0,0.04263761639595032,0.04318346083164215,-0.017829978466033937,0.10258292183279985, +C1,0.3/location_start_T,accuracy,0.6016483516483516,0.6014608457808642,0.5669671479438261,0.6386492133726647,1000,paired source-video group resample,,,,,C0,0.009615384615384581,0.00985222162793925,-0.02632223040117785,0.04394805909194238, +C1,0.3/location_start_T,macro_f1,0.5437921945102241,0.5424030009721812,0.5080806258370753,0.5830568877045641,1000,paired source-video group resample,,,,,C0,-0.01739897905809873,-0.016541621061421374,-0.05800975360014215,0.02155938725134242, +C1,0.3/location_start_T,mae,0.6949772834777832,0.6947953402996063,0.6393064528703689,0.747713926434517,1000,paired source-video group resample,0.016987383365631104,0.016228824853897095,-0.0012806236743927,0.037040983140468574,C0,-0.0742838978767395,-0.0740261971950531,-0.11522655040025712,-0.029132179915905013, +C1,0.3/location_start_T,rmse,0.9618797954516626,0.9602229311684626,0.8715600998503494,1.0416166031734424,1000,paired source-video group resample,,,,,C0,-0.013434134160397515,-0.01329873675752724,-0.07694335207130902,0.052326291470216314, +C1,0.3/location_start_T,pearson,0.532954216003418,0.533711314201355,0.4588514633476734,0.5972253069281578,1000,paired source-video group resample,,,,,C0,0.050404757261276245,0.049521178007125854,-0.014529494196176527,0.11024212315678596, +C1,0.3/location_middle_T,accuracy,0.5975274725274725,0.5972413793103448,0.5608638779986472,0.6376251001980384,1000,paired source-video group resample,,,,,C0,0.008241758241758212,0.00805991801148992,-0.02727338035527697,0.04337176234504374, +C1,0.3/location_middle_T,macro_f1,0.5306187842629876,0.5289832018002172,0.4945790232734105,0.569433031871124,1000,paired source-video group resample,,,,,C0,-0.020182719423329276,-0.02057005830093661,-0.05995935107733365,0.022646313815174072, +C1,0.3/location_middle_T,mae,0.705767810344696,0.7052761912345886,0.6511140152812004,0.7618570864200592,1000,paired source-video group resample,0.027777910232543945,0.02750420570373535,0.006807929277420044,0.04871420860290526,C0,-0.04299956560134888,-0.04301440715789795,-0.08523849099874496,-0.0022512689232826316, +C1,0.3/location_middle_T,rmse,0.9765841062062964,0.9750891990575792,0.8834029144373824,1.0685747509234282,1000,paired source-video group resample,,,,,C0,0.015126831455481216,0.014374119711033861,-0.04898978062223281,0.08078549943185262, +C1,0.3/location_middle_T,pearson,0.5209637880325317,0.5221226811408997,0.44065634682774546,0.5921292021870613,1000,paired source-video group resample,,,,,C0,0.014009475708007812,0.01533500850200653,-0.04813420474529266,0.07668219953775406, +C1,0.3/location_end_T,accuracy,0.6043956043956044,0.6041398886032562,0.565515800595524,0.6448164475612781,1000,paired source-video group resample,,,,,C0,0.030219780219780223,0.02981029810298108,-0.00426227940218808,0.06416161603942114, +C1,0.3/location_end_T,macro_f1,0.5391958036849257,0.5384257412040072,0.5004931603322708,0.5796083275747231,1000,paired source-video group resample,,,,,C0,0.0012276297550326554,0.0007364535076042622,-0.03718865568737375,0.04054905562325762, +C1,0.3/location_end_T,mae,0.713127076625824,0.7118663787841797,0.6580579370260239,0.7717627912759781,1000,paired source-video group resample,0.035137176513671875,0.03474634885787964,0.009870293736457826,0.06127412915229797,C0,-0.056025803089141846,-0.05577078461647034,-0.09927222281694412,-0.013927131891250616, +C1,0.3/location_end_T,rmse,0.9618990049781178,0.9602577190376865,0.8738901845361875,1.0458442755336472,1000,paired source-video group resample,,,,,C0,-0.015633563749922974,-0.017042836024082297,-0.07795992747767812,0.04659653340806797, +C1,0.3/location_end_T,pearson,0.5409887433052063,0.5401956140995026,0.4697173312306404,0.6097186088562012,1000,paired source-video group resample,,,,,C0,0.034304141998291016,0.03619542717933655,-0.030554254353046418,0.09503289908170699, +C1,0.3/span_long_T,accuracy,0.592032967032967,0.5909090909090909,0.5510190026423792,0.6336506336318942,1000,paired source-video group resample,,,,,C0,0.013736263736263687,0.013642590193713666,-0.022828032292578574,0.0468776216442953, +C1,0.3/span_long_T,macro_f1,0.5243559513864773,0.5225104257742073,0.48693140960774833,0.5629063731662385,1000,paired source-video group resample,,,,,C0,-0.015748523683523863,-0.016405945762968555,-0.058983884169548355,0.02420269730184655, +C1,0.3/span_long_T,mae,0.712438702583313,0.7117692828178406,0.6567808821797371,0.7678902104496955,1000,paired source-video group resample,0.03444880247116089,0.03431779146194458,0.009433393180370332,0.062406016886234275,C0,-0.036682844161987305,-0.03754425048828125,-0.08052448183298111,0.006804874539375294, +C1,0.3/span_long_T,rmse,0.970613225999349,0.9688817886420129,0.8804026205971283,1.0604626706210953,1000,paired source-video group resample,,,,,C0,0.0067153049744788085,0.004968971579744019,-0.0549136187410675,0.06868528540717854, +C1,0.3/span_long_T,pearson,0.5223181247711182,0.5239216387271881,0.4431985251605511,0.5947199195623397,1000,paired source-video group resample,,,,,C0,0.02233901619911194,0.02358199656009674,-0.04020816683769226,0.08191184103488922, +C1,0.3/span_multi_short_T,accuracy,0.6057692307692307,0.6050994339242469,0.5685327830064673,0.6426726705998604,1000,paired source-video group resample,,,,,C0,0.017857142857142794,0.01778385772913821,-0.018729569346261507,0.051794837939309106, +C1,0.3/span_multi_short_T,macro_f1,0.5426433761301394,0.5419206440505232,0.5079016901872131,0.5790511818551293,1000,paired source-video group resample,,,,,C0,-0.008901079156478975,-0.00933165981916323,-0.05062329296232728,0.031616800669025384, +C1,0.3/span_multi_short_T,mae,0.6816168427467346,0.6815358996391296,0.6291917786002159,0.7308105066418648,1000,paired source-video group resample,0.0036269426345825195,0.0038554370403289795,-0.017796476185321805,0.025313696265220634,C0,-0.06983870267868042,-0.06931149959564209,-0.10961888134479522,-0.03081425577402116, +C1,0.3/span_multi_short_T,rmse,0.9309714931339934,0.9303052590869612,0.8485999785508321,1.0077560172048394,1000,paired source-video group resample,,,,,C0,-0.029726612546388087,-0.02994074541227215,-0.08763041534055041,0.026750483838235316, +C1,0.3/span_multi_short_T,pearson,0.5452395081520081,0.5450739562511444,0.47100988775491714,0.6138804465532303,1000,paired source-video group resample,,,,,C0,0.04363095760345459,0.04324039816856384,-0.014663927257061003,0.0991303838789463, +C1,0.3/location_start_A,accuracy,0.6085164835164835,0.6079319719589418,0.5731345334678238,0.6458630555258411,1000,paired source-video group resample,,,,,C0,0.024725274725274637,0.025245441795231416,-0.010102476140211944,0.05891585986851799, +C1,0.3/location_start_A,macro_f1,0.5521389406885803,0.5502746738298386,0.5150370380763469,0.5921315175178025,1000,paired source-video group resample,,,,,C0,-0.004641219708646949,-0.004348973100676168,-0.0426967785691351,0.03235108448294833, +C1,0.3/location_start_A,mae,0.6774742603302002,0.6764070391654968,0.6252222031354904,0.7311903670430183,1000,paired source-video group resample,-0.0005156397819519043,-0.0004462003707885742,-0.006768412888050079,0.004334579408168792,C0,-0.05752408504486084,-0.05876809358596802,-0.09389935582876205,-0.019730702042579665, +C1,0.3/location_start_A,rmse,0.9220502654459637,0.919350886007989,0.8378663917742322,1.003145777525252,1000,paired source-video group resample,,,,,C0,-0.018747082248703917,-0.020820586595696244,-0.07312700167984204,0.039161838334632666, +C1,0.3/location_start_A,pearson,0.5802279114723206,0.5819732844829559,0.5077383995056153,0.6449896037578583,1000,paired source-video group resample,,,,,C0,0.0624842643737793,0.0639801025390625,0.01097300797700882,0.1152569532394409, +C1,0.3/location_middle_A,accuracy,0.6071428571428571,0.6068496364062866,0.5716185928668875,0.6447378240377062,1000,paired source-video group resample,,,,,C0,0.02060439560439553,0.021103564734918034,-0.017004041093941148,0.05579027964622026, +C1,0.3/location_middle_A,macro_f1,0.5510069929588249,0.5489421995982258,0.5142321265978776,0.5907369252653685,1000,paired source-video group resample,,,,,C0,-0.0027558303692157837,-0.0026423008121027047,-0.0457746841130733,0.04040185084868887, +C1,0.3/location_middle_A,mae,0.6807275414466858,0.6801330745220184,0.627207201719284,0.7339015632867812,1000,paired source-video group resample,0.0027376413345336914,0.002635359764099121,-0.0012629151344299317,0.007214409112930298,C0,-0.05329573154449463,-0.05407729744911194,-0.09287615865468979,-0.01380727142095568, +C1,0.3/location_middle_A,rmse,0.9258493647888447,0.9235128090836854,0.8438329022260214,1.0046397784169623,1000,paired source-video group resample,,,,,C0,-0.010929570864793292,-0.012971305591179982,-0.0685179061401914,0.047929144488409736, +C1,0.3/location_middle_A,pearson,0.5758045315742493,0.5763830244541168,0.5045776933431625,0.6401286765933036,1000,paired source-video group resample,,,,,C0,0.05544328689575195,0.057109177112579346,0.00044689476490020793,0.1090954840183258, +C1,0.3/location_end_A,accuracy,0.6071428571428571,0.6067797389225961,0.5724329478274156,0.6443614478169483,1000,paired source-video group resample,,,,,C0,0.017857142857142794,0.018360717521039516,-0.01766358957779952,0.051735688925635896, +C1,0.3/location_end_A,macro_f1,0.551044537966384,0.5486165522371447,0.5143970274203693,0.5899703859123,1000,paired source-video group resample,,,,,C0,-0.0023546232986747517,-0.002199377264880953,-0.042919095248300725,0.03923242555506438, +C1,0.3/location_end_A,mae,0.6779829859733582,0.6775741279125214,0.6263678640127182,0.7294549658894539,1000,paired source-video group resample,-6.9141387939453125e-06,0.00025007128715515137,-0.004259394109249115,0.0039290070533752434,C0,-0.05676394701004028,-0.05718269944190979,-0.09441758841276168,-0.018846032023429875, +C1,0.3/location_end_A,rmse,0.9219442115277172,0.9195508753206353,0.839965725515187,1.0029048822058948,1000,paired source-video group resample,,,,,C0,-0.015725209300675225,-0.018029475789805016,-0.07205517511499847,0.04301123699585812, +C1,0.3/location_end_A,pearson,0.5784357190132141,0.5790013372898102,0.5053057938814163,0.6438124105334282,1000,paired source-video group resample,,,,,C0,0.05948436260223389,0.06106078624725342,0.006115937232971192,0.11156836673617362, +C1,0.3/span_long_A,accuracy,0.6071428571428571,0.6068496364062866,0.5716185928668875,0.6447378240377062,1000,paired source-video group resample,,,,,C0,0.019230769230769162,0.02036833443965036,-0.01716146869370472,0.05428026393660322, +C1,0.3/span_long_A,macro_f1,0.5512701838283234,0.5491888509323002,0.5144932507330459,0.5907838039523532,1000,paired source-video group resample,,,,,C0,-0.0030670968247467068,-0.0026239807120718717,-0.04426134728611575,0.03758656429073177, +C1,0.3/span_long_A,mae,0.6796889305114746,0.6787563264369965,0.6264952376484871,0.7330356642603874,1000,paired source-video group resample,0.0016990303993225098,0.0017427504062652588,-0.001661089062690735,0.0050702795386314385,C0,-0.05696994066238403,-0.05733299255371094,-0.09572377651929856,-0.01885879933834076, +C1,0.3/span_long_A,rmse,0.9247741049651427,0.9223375937650041,0.8418759354312333,1.0058769456592147,1000,paired source-video group resample,,,,,C0,-0.013178971588219901,-0.015714979663699224,-0.07124586761121475,0.0446591719669447, +C1,0.3/span_long_A,pearson,0.5778243541717529,0.5790630578994751,0.5057659193873405,0.6416900604963302,1000,paired source-video group resample,,,,,C0,0.06029444932937622,0.061848148703575134,0.006885185837745667,0.11315126419067381, +C1,0.3/span_multi_short_A,accuracy,0.6043956043956044,0.6044527334188133,0.5694939271255062,0.641218475062135,1000,paired source-video group resample,,,,,C0,0.009615384615384581,0.010401211671612287,-0.027211128004210307,0.045198287566241765, +C1,0.3/span_multi_short_A,macro_f1,0.5491371043941137,0.5471036557855472,0.5115345463272643,0.5883913284339098,1000,paired source-video group resample,,,,,C0,-0.01114073118989467,-0.010878284952455963,-0.051659897249538456,0.03049319238989169, +C1,0.3/span_multi_short_A,mae,0.6805933117866516,0.6802165508270264,0.6271517664194107,0.7333800688385963,1000,paired source-video group resample,0.0026034116744995117,0.002593487501144409,-3.4683942794799797e-05,0.005193577706813812,C0,-0.05553072690963745,-0.0562572181224823,-0.09439068138599396,-0.014840981364250185, +C1,0.3/span_multi_short_A,rmse,0.925229032617497,0.9229077185673309,0.8409846054744893,1.004381599079662,1000,paired source-video group resample,,,,,C0,-0.01641711702780113,-0.018479879764878304,-0.07345341238428517,0.04366404520569964, +C1,0.3/span_multi_short_A,pearson,0.5771003365516663,0.5786854326725006,0.5047264724969864,0.6418843552470207,1000,paired source-video group resample,,,,,C0,0.06079995632171631,0.06231045722961426,0.006599666178226471,0.11514384075999258, +C1,0.3/location_start_V,accuracy,0.6057692307692307,0.6054845891258102,0.5704645339095562,0.6431586048805966,1000,paired source-video group resample,,,,,C0,0.009615384615384581,0.010378063523464098,-0.028766005575434957,0.04462065170528031, +C1,0.3/location_start_V,macro_f1,0.5486700331658957,0.5468142317061278,0.5132896339377986,0.5868372975075458,1000,paired source-video group resample,,,,,C0,-0.015140640604064615,-0.014720462196152806,-0.057137795350853914,0.02639834018708446, +C1,0.3/location_start_V,mae,0.6787739992141724,0.678495317697525,0.6273285299539566,0.7320346117019654,1000,paired source-video group resample,0.0007840991020202637,0.00031644105911254883,-0.0061718463897705075,0.010927782952785488,C0,-0.054672420024871826,-0.05499547719955444,-0.09326556622982025,-0.014725509285926839, +C1,0.3/location_start_V,rmse,0.9284146354682064,0.9270618098029915,0.8428373777838969,1.0119752728040976,1000,paired source-video group resample,,,,,C0,-0.008426684603003665,-0.010594450839266911,-0.06592861807899493,0.05292051331682923, +C1,0.3/location_start_V,pearson,0.5704621076583862,0.5709090232849121,0.4979195162653923,0.6341603934764861,1000,paired source-video group resample,,,,,C0,0.04942166805267334,0.05031299591064453,-0.008430735766887664,0.10275057926774024, +C1,0.3/location_middle_V,accuracy,0.6057692307692307,0.6054881492256354,0.569167580917457,0.6443494690334083,1000,paired source-video group resample,,,,,C0,0.013736263736263687,0.014765127273775547,-0.02131106047895063,0.04690305610024385, +C1,0.3/location_middle_V,macro_f1,0.5485065840539395,0.5468681892771639,0.5129090186035896,0.5867270554477702,1000,paired source-video group resample,,,,,C0,-0.0072023949824766564,-0.006663412012916203,-0.045963599685675934,0.03394960907069911, +C1,0.3/location_middle_V,mae,0.6798243522644043,0.6795104742050171,0.6276743337512016,0.7325242280960083,1000,paired source-video group resample,0.0018344521522521973,0.0014293789863586426,-0.002576503157615662,0.00856124460697174,C0,-0.05398571491241455,-0.05529096722602844,-0.09236418902873993,-0.015513123571872713, +C1,0.3/location_middle_V,rmse,0.9264565753055125,0.923643218693402,0.8423534738635465,1.0064989585862296,1000,paired source-video group resample,,,,,C0,-0.012424631003080444,-0.013657003887834196,-0.07170991774185718,0.047342087977745244, +C1,0.3/location_middle_V,pearson,0.572812020778656,0.5738295614719391,0.49964226558804514,0.6375514239072799,1000,paired source-video group resample,,,,,C0,0.05378854274749756,0.0546594113111496,-5.7786703109741204e-05,0.10735661610960959, +C1,0.3/location_end_V,accuracy,0.6057692307692307,0.6051892883576636,0.5697046857030913,0.6430473421112818,1000,paired source-video group resample,,,,,C0,0.016483516483516425,0.016495227154204817,-0.01880362913248819,0.051251883001552694, +C1,0.3/location_end_V,macro_f1,0.5498795196707147,0.5476465944284324,0.5126002730798069,0.5899582173199637,1000,paired source-video group resample,,,,,C0,-0.003396875199957128,-0.003214350646552233,-0.04281399342955595,0.038700584828763686, +C1,0.3/location_end_V,mae,0.6815360188484192,0.6806736290454865,0.6297370195388794,0.7353459060192108,1000,paired source-video group resample,0.00354611873626709,0.0034646689891815186,-0.000831073522567749,0.012633003294467924,C0,-0.051682353019714355,-0.05254840850830078,-0.08993908762931824,-0.010984450578689579, +C1,0.3/location_end_V,rmse,0.9316922859247591,0.9298932940105213,0.8464815200313367,1.0154193725019556,1000,paired source-video group resample,,,,,C0,-0.005752208586901175,-0.007356339843917925,-0.06252798370237807,0.05587579882258935, +C1,0.3/location_end_V,pearson,0.5684643983840942,0.5688571333885193,0.49550134912133215,0.6308408185839652,1000,paired source-video group resample,,,,,C0,0.04931598901748657,0.05047792196273804,-0.009574902057647704,0.10316566750407216, +C1,0.3/span_long_V,accuracy,0.6057692307692307,0.6053926351028216,0.5699734476050267,0.6445055465786871,1000,paired source-video group resample,,,,,C0,0.02060439560439553,0.02190780921907809,-0.015700446675511435,0.05287130220185249, +C1,0.3/span_long_V,macro_f1,0.5489381220760584,0.5473061690832144,0.5125976964986354,0.5875943683946058,1000,paired source-video group resample,,,,,C0,0.000324605307941761,0.0009853970109014454,-0.0395337251128501,0.04089794000797479, +C1,0.3/span_long_V,mae,0.6787789463996887,0.6784611344337463,0.6256921663880348,0.7314085364341736,1000,paired source-video group resample,0.0007890462875366211,0.0006538033485412598,-0.00033666342496871946,0.0023972600698471047,C0,-0.05557936429977417,-0.05628111958503723,-0.09273783564567566,-0.015539938211441045, +C1,0.3/span_long_V,rmse,0.9228613474493654,0.9203965561918768,0.8395651421542345,1.0023556170718824,1000,paired source-video group resample,,,,,C0,-0.014970790269268508,-0.01719790869027693,-0.07234489664045736,0.045259383277408326, +C1,0.3/span_long_V,pearson,0.5778414011001587,0.5786983370780945,0.5049772426486016,0.6439581692218781,1000,paired source-video group resample,,,,,C0,0.05796080827713013,0.0590042918920517,0.004624380171298981,0.11073285415768623, +C1,0.3/span_multi_short_V,accuracy,0.6057692307692307,0.6056427312524874,0.5708602224547106,0.6431480376315329,1000,paired source-video group resample,,,,,C0,0.017857142857142794,0.018309859154929553,-0.01704911760875232,0.052301530368244774, +C1,0.3/span_multi_short_V,macro_f1,0.550306278678187,0.5483336086571288,0.5131001229902281,0.5896190583309108,1000,paired source-video group resample,,,,,C0,-0.0011530391527211359,-0.0009942446937001859,-0.0406947716006249,0.04018137498253997, +C1,0.3/span_multi_short_V,mae,0.6800132393836975,0.6796658039093018,0.6266229182481766,0.7329073339700698,1000,paired source-video group resample,0.00202333927154541,0.0019463896751403809,0.000752517580986023,0.0039609655737876896,C0,-0.053589701652526855,-0.05433019995689392,-0.09200229346752167,-0.014550343155860901, +C1,0.3/span_multi_short_V,rmse,0.9244358894355263,0.9219636289526114,0.8407140374468121,1.00437642209508,1000,paired source-video group resample,,,,,C0,-0.013496946996377268,-0.015654060437056583,-0.07108914675076426,0.04784645838671681, +C1,0.3/span_multi_short_V,pearson,0.5773175358772278,0.5783975124359131,0.5041449412703514,0.6432931542396545,1000,paired source-video group resample,,,,,C0,0.05780154466629028,0.05867791175842285,0.003866279125213623,0.11166852265596389, +C1,0.3/synchrony_sync,accuracy,0.5961538461538461,0.595551983679273,0.5586537763912065,0.6357564689449859,1000,paired source-video group resample,,,,,C0,0.008241758241758212,0.009240960327916825,-0.025580760521475312,0.043725355955236675, +C1,0.3/synchrony_sync,macro_f1,0.5294661765561623,0.5281798253551154,0.4964721128060308,0.5632564031615921,1000,paired source-video group resample,,,,,C0,-0.019486054457599766,-0.019519827498748754,-0.058848688548447936,0.020475305475118697, +C1,0.3/synchrony_sync,mae,0.7051149010658264,0.704308956861496,0.6511041685938835,0.7611942023038865,1000,paired source-video group resample,0.027125000953674316,0.027049332857131958,0.010971249639987945,0.04413359910249709,C0,-0.037825703620910645,-0.03964009881019592,-0.08087144941091537,0.0030102074146270592, +C1,0.3/synchrony_sync,rmse,0.9601119612434329,0.9581606836654801,0.8764886056923257,1.0442714684793672,1000,paired source-video group resample,,,,,C0,0.00871874989159982,0.006346390203711139,-0.05416787950246588,0.07263544982055262, +C1,0.3/synchrony_sync,pearson,0.5407872200012207,0.5420737564563751,0.4738288290798664,0.6026979610323906,1000,paired source-video group resample,,,,,C0,0.025862693786621094,0.027707606554031372,-0.03801286220550537,0.08746829628944396, +C1,0.3/synchrony_partial,accuracy,0.5989010989010989,0.5977728958166242,0.5629883610860118,0.6370174339074045,1000,paired source-video group resample,,,,,C0,0.006868131868131844,0.007614323560437064,-0.029933673469387745,0.04533118034447827, +C1,0.3/synchrony_partial,macro_f1,0.5364431258782183,0.5351691264935516,0.5012126212692006,0.5752512491826867,1000,paired source-video group resample,,,,,C0,-0.020405801398082568,-0.019833388948294506,-0.06276597446600735,0.02528573386725433, +C1,0.3/synchrony_partial,mae,0.6977444887161255,0.6978516280651093,0.6464352011680603,0.7484437718987464,1000,paired source-video group resample,0.01975458860397339,0.01964026689529419,7.55056738853455e-05,0.040301555395126344,C0,-0.057210564613342285,-0.05718985199928284,-0.09762559682130814,-0.016315583884716038, +C1,0.3/synchrony_partial,rmse,0.9517401343100599,0.9505733352498538,0.8688224822285724,1.0273629721016655,1000,paired source-video group resample,,,,,C0,-0.002007864796631953,-0.0012469408657134196,-0.06264203320962598,0.05748741216199069, +C1,0.3/synchrony_partial,pearson,0.5430726408958435,0.5433811247348785,0.47375634908676145,0.6066196128726006,1000,paired source-video group resample,,,,,C0,0.03532838821411133,0.03498603403568268,-0.023196275532245635,0.09179198220372199, +C1,0.3/synchrony_async,accuracy,0.6016483516483516,0.601518406233693,0.5640210027100271,0.6423868442781794,1000,paired source-video group resample,,,,,C0,0.006868131868131844,0.007047219849420916,-0.02727145547976515,0.03811175052609788, +C1,0.3/synchrony_async,macro_f1,0.535100442278996,0.5344065201553084,0.5004018797664644,0.5726791027510284,1000,paired source-video group resample,,,,,C0,-0.022249302856790276,-0.021261565303646535,-0.060398932505203215,0.017676910501312527, +C1,0.3/synchrony_async,mae,0.7007834315299988,0.6996950209140778,0.6453914299607277,0.7548393562436103,1000,paired source-video group resample,0.02279353141784668,0.022615045309066772,0.0011191412806510932,0.04303499162197113,C0,-0.056439340114593506,-0.056175172328948975,-0.09865313321352005,-0.016507281363010416, +C1,0.3/synchrony_async,rmse,0.9509916350180309,0.9484426677214971,0.8622225197429566,1.0427745909680828,1000,paired source-video group resample,,,,,C0,-0.01609874986952542,-0.01766493803869784,-0.07332949643719323,0.04052751889550574, +C1,0.3/synchrony_async,pearson,0.5492207407951355,0.5509367883205414,0.4685228794813156,0.6220448717474938,1000,paired source-video group resample,,,,,C0,0.051503509283065796,0.05199389159679413,-0.0008632116019725791,0.10276819914579391, +C2,0.0/none,accuracy,0.5975274725274725,0.5971033260868812,0.5578137212331741,0.6384660766961652,1000,paired source-video group resample,,,,,C0,0.005494505494505475,0.006106870229007577,-0.03125,0.04057285180572855, +C2,0.0/none,macro_f1,0.47637082507472805,0.4756609213487376,0.4456518795125286,0.5081403109138748,1000,paired source-video group resample,,,,,C0,-0.07956378757630245,-0.07871313240506361,-0.11689642440190383,-0.04103536506889931, +C2,0.0/none,mae,0.7159271240234375,0.7163882255554199,0.6636484235525131,0.7665003627538681,1000,paired source-video group resample,,,,,C0,-0.0174868106842041,-0.017604410648345947,-0.05566457509994507,0.018328091502189628, +C2,0.0/none,rmse,0.9473113058814692,0.9459271961635211,0.8679711830227337,1.0198328263893106,1000,paired source-video group resample,,,,,C0,0.01013764645327897,0.008432707720641641,-0.04090670465801699,0.05885041877504671, +C2,0.0/none,pearson,0.579660177230835,0.5812240839004517,0.5154384732246399,0.6404302716255188,1000,paired source-video group resample,,,,,C0,0.06041759252548218,0.06228184700012207,0.015440493822097778,0.11006865948438643, +C2,0.1/single,accuracy,0.6016483516483516,0.6009768320784783,0.562105594623248,0.6421413982624437,1000,paired source-video group resample,,,,,C0,0.013736263736263687,0.014641288433382083,-0.020754901160893208,0.04944205026964562, +C2,0.1/single,macro_f1,0.48694048900464676,0.48584081418600467,0.4548305940187138,0.5194169281588271,1000,paired source-video group resample,,,,,C0,-0.06294430843225957,-0.0626310374365118,-0.09984320204780872,-0.023541317242999023, +C2,0.1/single,mae,0.7133060693740845,0.7131710946559906,0.6610704034566879,0.7648322626948356,1000,paired source-video group resample,-0.0026210546493530273,-0.002561628818511963,-0.006693494319915771,0.0012196972966194148,C0,-0.022453129291534424,-0.022572576999664307,-0.05937451273202896,0.013716207444667816, +C2,0.1/single,rmse,0.9451983043958943,0.9435913874666163,0.8661708523676109,1.0181478101833763,1000,paired source-video group resample,,,,,C0,0.005875728834647043,0.004968378054832301,-0.04309614461599197,0.05477575253061832, +C2,0.1/single,pearson,0.5814213752746582,0.5830335021018982,0.5178892180323601,0.641932313144207,1000,paired source-video group resample,,,,,C0,0.06484586000442505,0.06590870022773743,0.020325832068920135,0.11447026059031486, +C2,0.1/sync,accuracy,0.5961538461538461,0.5960893549620405,0.5549300979654499,0.6371733871465423,1000,paired source-video group resample,,,,,C0,0.009615384615384581,0.010512483574244391,-0.027839392195418214,0.04565665044325415, +C2,0.1/sync,macro_f1,0.4772337887846125,0.47641281198502683,0.4453678098671757,0.5106104116391126,1000,paired source-video group resample,,,,,C0,-0.07309427431014076,-0.07240162869066538,-0.1093524381639473,-0.036746915922306896, +C2,0.1/sync,mae,0.7168080806732178,0.7171643376350403,0.6638445407152176,0.7670024141669274,1000,paired source-video group resample,0.0008809566497802734,0.001315385103225708,-0.012289871275424958,0.011588402092456814,C0,-0.01823478937149048,-0.019444972276687622,-0.055413125455379485,0.016611063480377195, +C2,0.1/sync,rmse,0.9445578029487764,0.9429397752361705,0.8657762603688023,1.0183374944129173,1000,paired source-video group resample,,,,,C0,-0.0006254614065102082,-0.0030922110124138036,-0.04913478528234149,0.04778127497100552, +C2,0.1/sync,pearson,0.582561194896698,0.5828393697738647,0.5177481889724731,0.643026427924633,1000,paired source-video group resample,,,,,C0,0.06916135549545288,0.07010707259178162,0.024747152626514436,0.11307058110833168, +C2,0.1/partial,accuracy,0.5975274725274725,0.597118794326241,0.5565327100002997,0.6393568243200805,1000,paired source-video group resample,,,,,C0,0.004120879120879106,0.005351364508461964,-0.03147579140522534,0.037776398388456776, +C2,0.1/partial,macro_f1,0.47813406927937097,0.4771330756591816,0.44604921918297535,0.5109912277982304,1000,paired source-video group resample,,,,,C0,-0.0794988687239343,-0.07913308452691181,-0.11607727264856826,-0.04154973933135409, +C2,0.1/partial,mae,0.7148827314376831,0.7150123119354248,0.6627959758043289,0.7668295115232467,1000,paired source-video group resample,-0.0010443925857543945,-0.0009566843509674072,-0.012103898823261261,0.008674341440200805,C0,-0.02033466100692749,-0.020620375871658325,-0.05753915756940842,0.014974519610404968, +C2,0.1/partial,rmse,0.9410463967048543,0.939975964519514,0.8602830430659992,1.017004234072866,1000,paired source-video group resample,,,,,C0,0.0036029512976423206,0.002281731944834775,-0.046883728498318525,0.055016146319294315, +C2,0.1/partial,pearson,0.586395800113678,0.5875959098339081,0.5241892158985137,0.6467775478959084,1000,paired source-video group resample,,,,,C0,0.06582224369049072,0.06683027744293213,0.02119344621896744,0.114761633425951, +C2,0.1/async,accuracy,0.592032967032967,0.5921431618828323,0.5527455962059621,0.634947464868147,1000,paired source-video group resample,,,,,C0,0.0,0.0013333428148822324,-0.0373027259684362,0.03667671506855655, +C2,0.1/async,macro_f1,0.47023202278964216,0.46917615985719496,0.4397066346764128,0.5023141298269639,1000,paired source-video group resample,,,,,C0,-0.08857499908976496,-0.08823721078450802,-0.12612737630709916,-0.0480314164942442, +C2,0.1/async,mae,0.7224758863449097,0.7218783795833588,0.6707540646195411,0.7746649116277694,1000,paired source-video group resample,0.006548762321472168,0.006327450275421143,-0.002523288130760193,0.01635310798883438,C0,-0.016417741775512695,-0.016968995332717896,-0.05285276174545288,0.020050561428070067, +C2,0.1/async,rmse,0.9567308538338793,0.955833004995029,0.876607954680595,1.0316069609633751,1000,paired source-video group resample,,,,,C0,0.012996212536354967,0.011756012136363625,-0.03940176369409833,0.06115712611243609, +C2,0.1/async,pearson,0.5709324479103088,0.5714669823646545,0.5064621418714523,0.6348869204521179,1000,paired source-video group resample,,,,,C0,0.05691647529602051,0.05763465166091919,0.010335034132003785,0.10656432956457138, +C2,0.3/single,accuracy,0.6002747252747253,0.6,0.5571999855539046,0.6438426672038678,1000,paired source-video group resample,,,,,C0,-0.005494505494505475,-0.005215159319037543,-0.04132952465472292,0.029096980795329946, +C2,0.3/single,macro_f1,0.4794881025439928,0.47864735090000676,0.44661306566174486,0.5122096806867075,1000,paired source-video group resample,,,,,C0,-0.0898111468644554,-0.08940378732140383,-0.12664667166644972,-0.052392902882648085, +C2,0.3/single,mae,0.729577898979187,0.7291747629642487,0.6762829199433327,0.7831955030560493,1000,paired source-video group resample,0.013650774955749512,0.01264914870262146,0.0016282618045806885,0.0293344184756279,C0,-0.0015532374382019043,-0.0009183287620544434,-0.044194063544273375,0.03767065554857253, +C2,0.3/single,rmse,0.9741746930742672,0.9731400596500461,0.8851309826220225,1.0562802629001187,1000,paired source-video group resample,,,,,C0,0.0344071183407223,0.03262918822823441,-0.028399044358384008,0.09162327360598604, +C2,0.3/single,pearson,0.5554234385490417,0.5564932227134705,0.48444687500596045,0.6259075492620468,1000,paired source-video group resample,,,,,C0,0.03400784730911255,0.035414695739746094,-0.02332931011915207,0.09136832058429717, +C2,0.3/sync,accuracy,0.5906593406593407,0.5911958825310324,0.548299117566789,0.6334832468345698,1000,paired source-video group resample,,,,,C0,0.01098901098901095,0.011188833075129467,-0.023001567398119094,0.043786295495982126, +C2,0.3/sync,macro_f1,0.4695135147336947,0.4680546977876149,0.4378632215258733,0.5041909272852828,1000,paired source-video group resample,,,,,C0,-0.07058747470579313,-0.07011700144654684,-0.10546594210849694,-0.03146224697916792, +C2,0.3/sync,mae,0.7389450669288635,0.737177848815918,0.6849618673324585,0.7967924863100052,1000,paired source-video group resample,0.023017942905426025,0.022462010383605957,0.004946482181549072,0.04193758517503738,C0,-0.013958632946014404,-0.015113472938537598,-0.05829350501298904,0.02501997798681259, +C2,0.3/sync,rmse,0.979076597792268,0.9765014921160922,0.893832118341828,1.0584727840438923,1000,paired source-video group resample,,,,,C0,0.016783882027990638,0.01405573793696685,-0.04644978211629402,0.07458273532810139, +C2,0.3/sync,pearson,0.554204523563385,0.5555997490882874,0.4826143950223923,0.6256720215082168,1000,paired source-video group resample,,,,,C0,0.05596959590911865,0.05751881003379822,0.004116395115852357,0.1134153038263321, +C2,0.3/partial,accuracy,0.5906593406593407,0.591438078508209,0.551221397649969,0.6317403913463782,1000,paired source-video group resample,,,,,C0,-0.004120879120879106,-0.0030372495479871753,-0.04224596722738909,0.03392253504479577, +C2,0.3/partial,macro_f1,0.4650773524865703,0.46517467965227094,0.4361239652632605,0.498558926391851,1000,paired source-video group resample,,,,,C0,-0.09815829515689906,-0.096709934216333,-0.13695239996810288,-0.05681032675451386, +C2,0.3/partial,mae,0.7384321689605713,0.7374532520771027,0.686315368115902,0.7895942628383636,1000,paired source-video group resample,0.02250504493713379,0.0222453773021698,-0.0020221829414367675,0.04292491674423216,C0,-0.008119523525238037,-0.008771717548370361,-0.05228365212678909,0.03714630156755447, +C2,0.3/partial,rmse,0.9653649717662364,0.9650653785178123,0.8850214747867815,1.0438592035483927,1000,paired source-video group resample,,,,,C0,0.01256677850226029,0.01189499885274009,-0.04904190989627883,0.06859772756920343, +C2,0.3/partial,pearson,0.5671414732933044,0.5685268938541412,0.49739598855376244,0.6326754853129387,1000,paired source-video group resample,,,,,C0,0.05842769145965576,0.05976027250289917,0.0049757160246372235,0.11213303506374359, +C2,0.3/async,accuracy,0.592032967032967,0.591724889125016,0.55110285827038,0.6336132911671855,1000,paired source-video group resample,,,,,C0,0.012362637362637319,0.012916189353411989,-0.022901387775314867,0.051750589110752775, +C2,0.3/async,macro_f1,0.4768663588925115,0.47614907849395993,0.4425911970815972,0.5155128136486667,1000,paired source-video group resample,,,,,C0,-0.06928411165616344,-0.06870655678864959,-0.10559418139055901,-0.028835553212928296, +C2,0.3/async,mae,0.7368908524513245,0.737002044916153,0.6831097275018692,0.7896088033914566,1000,paired source-video group resample,0.020963728427886963,0.02057725191116333,0.0031266286969184875,0.03852394074201584,C0,-0.031692564487457275,-0.03248906135559082,-0.07653730362653732,0.011133903264999386, +C2,0.3/async,rmse,0.9789783046352472,0.9768870751455994,0.8956252831231146,1.0541635727488516,1000,paired source-video group resample,,,,,C0,-0.004126489920682874,-0.004644079420538849,-0.06460058583106747,0.057474123840449406, +C2,0.3/async,pearson,0.5517277717590332,0.5510472059249878,0.48884276747703553,0.6130752086639404,1000,paired source-video group resample,,,,,C0,0.064881831407547,0.06478051841259003,0.008872970938682556,0.12587928399443624, +C2,0.5/single,accuracy,0.5961538461538461,0.5968882602545968,0.5555555555555556,0.6378657652385004,1000,paired source-video group resample,,,,,C0,0.009615384615384581,0.010688047521472455,-0.029469702090268533,0.045280555327481056, +C2,0.5/single,macro_f1,0.4806131030054475,0.4802141783223808,0.45008941415702775,0.5135368749869695,1000,paired source-video group resample,,,,,C0,-0.07440417915643543,-0.07409874082290546,-0.1128765595828328,-0.034783348822924685, +C2,0.5/single,mae,0.7249506115913391,0.7245077788829803,0.6756784722208977,0.7760904967784882,1000,paired source-video group resample,0.009023487567901611,0.008717894554138184,-0.0042485535144805905,0.021860191226005552,C0,-0.02407771348953247,-0.023583650588989258,-0.06386247128248215,0.012807065248489376, +C2,0.5/single,rmse,0.9538159601843559,0.9521452600358931,0.8771992734737146,1.0276545480095665,1000,paired source-video group resample,,,,,C0,-0.005834877328177668,-0.007137825979204093,-0.05387302590976441,0.040655897429663614, +C2,0.5/single,pearson,0.5764800906181335,0.5777219831943512,0.5127686768770218,0.639168220758438,1000,paired source-video group resample,,,,,C0,0.06824684143066406,0.06940338015556335,0.02284711003303528,0.11440150141716003, +C2,0.5/sync,accuracy,0.5892857142857143,0.5901742688520533,0.5490309411139321,0.6321976093138998,1000,paired source-video group resample,,,,,C0,-0.004120879120879106,-0.004583675718074165,-0.04064511431483905,0.028281931640746466, +C2,0.5/sync,macro_f1,0.4678364432236606,0.46699584542400374,0.43594128614418093,0.502387337977945,1000,paired source-video group resample,,,,,C0,-0.09566709617252289,-0.09564073786899849,-0.13060669057836338,-0.06276675778631982, +C2,0.5/sync,mae,0.7474918365478516,0.7460308372974396,0.6913397520780563,0.8040147215127945,1000,paired source-video group resample,0.03156471252441406,0.03157532215118408,0.0009050384163856508,0.058230577409267424,C0,-0.0398024320602417,-0.04076722264289856,-0.08457479625940323,0.004140400886535636, +C2,0.5/sync,rmse,0.9751174611471469,0.9734653032350398,0.8891814234105866,1.059337489678615,1000,paired source-video group resample,,,,,C0,-0.02725407777904154,-0.028070738871567136,-0.09123079779875487,0.03290002961361603, +C2,0.5/sync,pearson,0.561271071434021,0.5612391829490662,0.48888154104352,0.6301522120833397,1000,paired source-video group resample,,,,,C0,0.08161279559135437,0.08167092502117157,0.028393713384866716,0.14074341133236884, +C2,0.5/partial,accuracy,0.5934065934065934,0.5930703309692671,0.5538362652232748,0.6343095236341133,1000,paired source-video group resample,,,,,C0,0.008241758241758212,0.008900280644577208,-0.028466419920175675,0.045086742267141065, +C2,0.5/partial,macro_f1,0.4718462721713861,0.4711053323707993,0.44310452833044606,0.503013425682628,1000,paired source-video group resample,,,,,C0,-0.07974995856804501,-0.07845402391033868,-0.11613363328531799,-0.041086704558975125, +C2,0.5/partial,mae,0.7500930428504944,0.7498655021190643,0.6972840338945389,0.80654256939888,1000,paired source-video group resample,0.034165918827056885,0.03429475426673889,0.010733039677143097,0.05686410069465637,C0,-0.035366058349609375,-0.03534650802612305,-0.08233517408370972,0.007434029877185818, +C2,0.5/partial,rmse,0.9901796284426347,0.9889231919594859,0.9092243314532803,1.0717194444187688,1000,paired source-video group resample,,,,,C0,-0.00943116689381407,-0.010990085403866423,-0.0747500796262565,0.05035465866125582, +C2,0.5/partial,pearson,0.5457637310028076,0.5464603006839752,0.4802266672253609,0.6105128049850463,1000,paired source-video group resample,,,,,C0,0.06435811519622803,0.0654793232679367,0.002241666615009308,0.12450965568423267, +C2,0.5/async,accuracy,0.5741758241758241,0.5741768405475398,0.5335097383129906,0.6159748119461975,1000,paired source-video group resample,,,,,C0,0.0013736263736263687,0.0,-0.037615639163412644,0.04324911868390129, +C2,0.5/async,macro_f1,0.4537896600400204,0.45278494792454843,0.42243505414916155,0.4875443942260303,1000,paired source-video group resample,,,,,C0,-0.08685833639450635,-0.08679212527300562,-0.1257750188161217,-0.04191967875667009, +C2,0.5/async,mae,0.7844226360321045,0.7829013466835022,0.725303003191948,0.8461902007460593,1000,paired source-video group resample,0.06849551200866699,0.06791180372238159,0.04252657741308212,0.09495582580566404,C0,-0.008842051029205322,-0.008114874362945557,-0.05640320777893066,0.035935579240322105, +C2,0.5/async,rmse,1.0425033959898307,1.0400608400358036,0.948281029691952,1.1295303718216718,1000,paired source-video group resample,,,,,C0,0.039175662345659834,0.03883772318567902,-0.029205092432403705,0.1044024822770915, +C2,0.5/async,pearson,0.5009015202522278,0.501881867647171,0.4291691675782204,0.5717062965035439,1000,paired source-video group resample,,,,,C0,0.026406824588775635,0.027382314205169678,-0.03931054025888443,0.09262779876589775, +C2,0.7/single,accuracy,0.6016483516483516,0.6015831134564644,0.5631822098812715,0.6410758886608222,1000,paired source-video group resample,,,,,C0,0.016483516483516425,0.01709964012595594,-0.01943375834946008,0.05483575248281137, +C2,0.7/single,macro_f1,0.4841166665779777,0.4827481795406925,0.4518723308163845,0.5189794274213998,1000,paired source-video group resample,,,,,C0,-0.06719430592451936,-0.06683831969396845,-0.10772774165262967,-0.027064115238981577, +C2,0.7/single,mae,0.7301042079925537,0.7295994460582733,0.6707099840044976,0.7869590163230896,1000,paired source-video group resample,0.014177083969116211,0.013670235872268677,-0.006183163821697235,0.0373913362622261,C0,-0.05784440040588379,-0.05732846260070801,-0.10526490211486816,-0.015068149566650394, +C2,0.7/single,rmse,0.9596087254919016,0.958368547802696,0.8700477497575837,1.0406915269337962,1000,paired source-video group resample,,,,,C0,-0.05071526993202691,-0.05092645863510903,-0.11520893861965852,0.009888837743844435, +C2,0.7/single,pearson,0.5720389485359192,0.5725791454315186,0.5061067923903465,0.6358118489384651,1000,paired source-video group resample,,,,,C0,0.09939873218536377,0.10069642961025238,0.04403953030705452,0.15812403708696365, +C2,0.7/sync,accuracy,0.5879120879120879,0.5884437351335156,0.548222580134129,0.6273804311506953,1000,paired source-video group resample,,,,,C0,0.005494505494505475,0.005586592178770888,-0.03139248761269588,0.043662290005090726, +C2,0.7/sync,macro_f1,0.46791204467622977,0.4673779252997583,0.4355487432629034,0.4997776213687719,1000,paired source-video group resample,,,,,C0,-0.08102745542413431,-0.0814623049781002,-0.11935155011582255,-0.03984726034330748, +C2,0.7/sync,mae,0.7789478302001953,0.7778678238391876,0.719620580971241,0.8421317249536514,1000,paired source-video group resample,0.06302070617675781,0.06259986758232117,0.03284166604280472,0.09311676919460296,C0,-0.004423797130584717,-0.006281644105911255,-0.058759891986846925,0.047180210053920736, +C2,0.7/sync,rmse,1.0257644988970767,1.0239416669083192,0.9327971138606588,1.1158003950835325,1000,paired source-video group resample,,,,,C0,0.005609057339779122,0.00514472665804977,-0.06301773854890017,0.06731717286084199, +C2,0.7/sync,pearson,0.5225853323936462,0.5241603553295135,0.4458654664456844,0.5925592318177223,1000,paired source-video group resample,,,,,C0,0.0441402792930603,0.045630499720573425,-0.00868387296795845,0.10082674026489256, +C2,0.7/partial,accuracy,0.5879120879120879,0.5883981492103552,0.5465920608912683,0.6292562503419225,1000,paired source-video group resample,,,,,C0,-0.005494505494505475,-0.0053483678718965755,-0.04348420052268945,0.032013200047308246, +C2,0.7/partial,macro_f1,0.46643760102647097,0.4655089600459967,0.4316710765320061,0.5000714783730954,1000,paired source-video group resample,,,,,C0,-0.09757583619013949,-0.09721112002186078,-0.13574027056218066,-0.05865867129477976, +C2,0.7/partial,mae,0.7756062746047974,0.7742500007152557,0.7162664383649826,0.8387660458683968,1000,paired source-video group resample,0.05967915058135986,0.05962464213371277,0.026219241321086884,0.09047405123710632,C0,-0.02198505401611328,-0.023150265216827393,-0.0719743475317955,0.02802268564701079, +C2,0.7/partial,rmse,1.0155973577405673,1.013960720634929,0.9233356771756633,1.1020811642710195,1000,paired source-video group resample,,,,,C0,-0.0018593340263486358,-0.002352805859753948,-0.07013985223840331,0.062409373445748914, +C2,0.7/partial,pearson,0.5279400944709778,0.528290867805481,0.4512966491281986,0.6020694762468338,1000,paired source-video group resample,,,,,C0,0.03546327352523804,0.03579056262969971,-0.02508794069290161,0.09706217795610425, +C2,0.7/async,accuracy,0.5769230769230769,0.5782792665726375,0.5364393280353617,0.6193878136634556,1000,paired source-video group resample,,,,,C0,-0.0013736263736264798,-0.0013605442176870541,-0.03951298779243537,0.03501456787094399, +C2,0.7/async,macro_f1,0.44909323144936053,0.448466857896512,0.4172525648942995,0.4784281318430167,1000,paired source-video group resample,,,,,C0,-0.10470483155854327,-0.10459395037027783,-0.14174867208057415,-0.0668555451641738, +C2,0.7/async,mae,0.8141093254089355,0.8126004040241241,0.7543921619653702,0.8770935148000717,1000,paired source-video group resample,0.09818220138549805,0.0977618396282196,0.06453149169683456,0.13322279453277588,C0,-0.0023502707481384277,-0.004083484411239624,-0.050744096934795375,0.050268760323524446, +C2,0.7/async,rmse,1.0689737342305434,1.0674052047721994,0.9807663755378683,1.14753833959475,1000,paired source-video group resample,,,,,C0,0.028178855456189256,0.02554964079931432,-0.042995442389506935,0.09948807109725592, +C2,0.7/async,pearson,0.4801608622074127,0.4790869802236557,0.4172774448990822,0.5478059098124504,1000,paired source-video group resample,,,,,C0,0.0009647011756896973,0.003095492720603943,-0.06595882251858712,0.06408879235386848, +C2,0.3/modality_T,accuracy,0.5989010989010989,0.5989268826336358,0.5594713656387665,0.6403702023257377,1000,paired source-video group resample,,,,,C0,0.012362637362637319,0.012456753370650941,-0.02263977629290023,0.04735224828433884, +C2,0.3/modality_T,macro_f1,0.47391541094523165,0.4725548483995182,0.4430563660922434,0.5091245337386633,1000,paired source-video group resample,,,,,C0,-0.07284790249847511,-0.07280955811128537,-0.10719304548347676,-0.03541716497797837, +C2,0.3/modality_T,mae,0.7320624589920044,0.7308375239372253,0.6815523102879524,0.7821850210428238,1000,paired source-video group resample,0.016135334968566895,0.015696793794631958,-0.005763269960880279,0.03927515298128127,C0,-0.018061280250549316,-0.019196301698684692,-0.06447737962007523,0.02617547363042831, +C2,0.3/modality_T,rmse,0.9627499738805664,0.9618530254061302,0.8824762011175102,1.0393969058046189,1000,paired source-video group resample,,,,,C0,8.064222644577068e-05,0.00012673262605278346,-0.06572781665957333,0.06470202293402247, +C2,0.3/modality_T,pearson,0.5720019936561584,0.5730553269386292,0.5073372319340705,0.6336762860417365,1000,paired source-video group resample,,,,,C0,0.0702396035194397,0.07045714557170868,0.0108451247215271,0.1339294701814651, +C2,0.3/modality_A,accuracy,0.5961538461538461,0.5957866561263725,0.5556975389544198,0.6367962397520328,1000,paired source-video group resample,,,,,C0,0.009615384615384581,0.009964458241473184,-0.02735171918222683,0.04744219653179196, +C2,0.3/modality_A,macro_f1,0.47559200887535114,0.47496118905996276,0.4448170929181552,0.5074197278572294,1000,paired source-video group resample,,,,,C0,-0.07588975978454615,-0.07540083542581974,-0.11157429080623664,-0.03615335054986128, +C2,0.3/modality_A,mae,0.716270387172699,0.7162911295890808,0.6651685938239098,0.7670623108744621,1000,paired source-video group resample,0.0003432631492614746,0.00014099478721618652,-0.0035251468420028687,0.004651361703872676,C0,-0.013896644115447998,-0.014388829469680786,-0.051237693428993224,0.02230078727006912, 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+C2,0.3/modality_V,mae,0.7123501300811768,0.7124723494052887,0.6606866583228111,0.7633361160755158,1000,paired source-video group resample,-0.003576993942260742,-0.0036101341247558594,-0.007713557779788971,0.0003763154149055481,C0,-0.020982980728149414,-0.021428674459457397,-0.059379379451274875,0.01455927044153213, +C2,0.3/modality_V,rmse,0.9449209553090004,0.9433584057218214,0.8644344995841631,1.0197230014487497,1000,paired source-video group resample,,,,,C0,0.007128222996374056,0.005520639327417531,-0.04279907228148682,0.05680086203348926, +C2,0.3/modality_V,pearson,0.5786991119384766,0.5804318487644196,0.5127751946449279,0.638190820813179,1000,paired source-video group resample,,,,,C0,0.0592532753944397,0.06056520342826843,0.014406566321849824,0.10830139145255085, +C2,0.3/modality_TA,accuracy,0.5989010989010989,0.5984601556635455,0.5582399775721896,0.6411300136838799,1000,paired source-video group resample,,,,,C0,0.012362637362637319,0.012965896228000984,-0.02456596992589177,0.04638527451602668, +C2,0.3/modality_TA,macro_f1,0.47701983551040156,0.4758569662854124,0.4443444868461902,0.5108543930957452,1000,paired source-video group resample,,,,,C0,-0.07717845164989129,-0.07615593313896865,-0.11376257415006202,-0.04185989062830642, +C2,0.3/modality_TA,mae,0.7315338253974915,0.7310943305492401,0.6778645381331444,0.7843464195728301,1000,paired source-video group resample,0.015606701374053955,0.015748590230941772,-0.00022870451211929314,0.0308080956339836,C0,-0.04405170679092407,-0.04391670227050781,-0.08374668955802918,-0.005507990717887884, +C2,0.3/modality_TA,rmse,0.9591971353673434,0.9576022087599152,0.8812641896785921,1.0321656471505014,1000,paired source-video group resample,,,,,C0,-0.01142395098609339,-0.0127252558183088,-0.06261480348385925,0.040643839760111766, +C2,0.3/modality_TA,pearson,0.5751843452453613,0.5760262608528137,0.5138284772634506,0.6333268001675605,1000,paired source-video group resample,,,,,C0,0.07674437761306763,0.07763566076755524,0.025541122257709502,0.1267526976764202, +C2,0.3/modality_TV,accuracy,0.6002747252747253,0.6008316108161273,0.5599930555555556,0.6423993818644208,1000,paired source-video group resample,,,,,C0,0.017857142857142794,0.01914318122327896,-0.020413423101199157,0.05769300144300146, +C2,0.3/modality_TV,macro_f1,0.4818382043262426,0.4814564170295228,0.4500263391731132,0.5174999804463118,1000,paired source-video group resample,,,,,C0,-0.06300638366261568,-0.0625239949153906,-0.10282557563158702,-0.020549314367626307, +C2,0.3/modality_TV,mae,0.7279267907142639,0.7269971370697021,0.673421174287796,0.7794497221708298,1000,paired source-video group resample,0.011999666690826416,0.011058449745178223,-0.007797181606292724,0.030236852169036862,C0,-0.032746970653533936,-0.03376948833465576,-0.07455133646726608,0.006936557590961442, +C2,0.3/modality_TV,rmse,0.9690962757078789,0.9658939036461245,0.8885271262656781,1.0448927217450363,1000,paired source-video group resample,,,,,C0,0.001529184901990055,-0.0004703921234154862,-0.05912508862983734,0.05811492116348641, +C2,0.3/modality_TV,pearson,0.5645437836647034,0.5669387578964233,0.49404276385903356,0.6316510364413261,1000,paired source-video group resample,,,,,C0,0.06555697321891785,0.06808897852897644,0.014927051961421967,0.1192801333963871, +C2,0.3/modality_AV,accuracy,0.5975274725274725,0.5973577807297373,0.5565327100002997,0.6383953206432373,1000,paired source-video group resample,,,,,C0,0.0027472527472527375,0.0028429296521401137,-0.03157020346941442,0.03768252666119767, +C2,0.3/modality_AV,macro_f1,0.48386425400942173,0.4835952740662477,0.45093541204708787,0.5170330946361811,1000,paired source-video group resample,,,,,C0,-0.07583395222969042,-0.07516243437051467,-0.11133014685989075,-0.035949798844225105, +C2,0.3/modality_AV,mae,0.7123004198074341,0.7115959525108337,0.6607982829213143,0.764741663634777,1000,paired source-video group resample,-0.003626704216003418,-0.004183590412139893,-0.010674892365932465,0.004420357942581174,C0,-0.02568042278289795,-0.02599063515663147,-0.06502998471260071,0.010060831904411309, +C2,0.3/modality_AV,rmse,0.9454391331621051,0.9431595038959882,0.8663434457149799,1.0189019098565846,1000,paired source-video group resample,,,,,C0,0.003403905660514628,0.0013167767058931967,-0.047026987109602236,0.053251118299873, +C2,0.3/modality_AV,pearson,0.5768678188323975,0.5777308940887451,0.51363146007061,0.6375651404261589,1000,paired source-video group resample,,,,,C0,0.06133389472961426,0.06279546022415161,0.01592768132686615,0.1109973825514316, +C2,0.3/modality_TAV,accuracy,0.5975274725274725,0.5978251836201753,0.5592321847904624,0.6371958275069689,1000,paired source-video group resample,,,,,C0,0.016483516483516425,0.017127829468129463,-0.016579801414055517,0.05220320197044338, +C2,0.3/modality_TAV,macro_f1,0.47735479559765004,0.47635874514307697,0.44891226945560014,0.5090924548428694,1000,paired source-video group resample,,,,,C0,-0.06712310300663216,-0.06669611079102888,-0.10376935225551817,-0.028256387839227362, +C2,0.3/modality_TAV,mae,0.7234240770339966,0.7227151393890381,0.6722834005951881,0.7767813220620156,1000,paired source-video group resample,0.007496953010559082,0.00752606987953186,-0.01370966136455536,0.02797999978065489,C0,-0.047507643699645996,-0.047049880027770996,-0.08901602327823639,-0.011364999413490296, +C2,0.3/modality_TAV,rmse,0.9489927297500593,0.9468320815477143,0.8651778623558927,1.026393251952246,1000,paired source-video group resample,,,,,C0,-0.031045031911309806,-0.03273221075288696,-0.08631457277754773,0.0187405847192053, +C2,0.3/modality_TAV,pearson,0.5824760794639587,0.5834887325763702,0.5122652858495712,0.6499619886279105,1000,paired source-video group resample,,,,,C0,0.09216657280921936,0.09377419948577881,0.044780859351158143,0.14355748817324637, +C2,0.3/location_start_T,accuracy,0.5892857142857143,0.5896926735160841,0.5479629726821844,0.6306881784260516,1000,paired source-video group resample,,,,,C0,-0.0027472527472527375,-0.002751036841945942,-0.039063026448787064,0.03459734537610224, +C2,0.3/location_start_T,macro_f1,0.46337007300426,0.46238616366021623,0.4317363599260529,0.4950373505405614,1000,paired source-video group resample,,,,,C0,-0.09782110056406285,-0.09729681745878377,-0.13346132874343267,-0.05918352405922313, +C2,0.3/location_start_T,mae,0.7456059455871582,0.7459498047828674,0.6925614178180695,0.7983681261539459,1000,paired source-video group resample,0.029678821563720703,0.029647409915924072,0.016374641656875612,0.0441580131649971,C0,-0.023655235767364502,-0.02347925305366516,-0.06870201975107193,0.018643088638782477, +C2,0.3/location_start_T,rmse,0.9858544146900221,0.9859344105055928,0.9034649954546937,1.0594993609638013,1000,paired source-video group resample,,,,,C0,0.010540485077962014,0.011598630985847125,-0.04954087903826603,0.06936667616293754, +C2,0.3/location_start_T,pearson,0.5562344789505005,0.5569377243518829,0.4931278482079506,0.6178226038813591,1000,paired source-video group resample,,,,,C0,0.07368502020835876,0.07297399640083313,0.018758854269981386,0.13009975478053093, +C2,0.3/location_middle_T,accuracy,0.5975274725274725,0.5974103251759972,0.555861793837124,0.6395568490598794,1000,paired source-video group resample,,,,,C0,0.008241758241758212,0.008492607284529385,-0.02759433962264152,0.04272228366713954, +C2,0.3/location_middle_T,macro_f1,0.4655368421463156,0.46518399445969616,0.4356843534866461,0.49689067052458996,1000,paired source-video group resample,,,,,C0,-0.08526466154000129,-0.08495731770249237,-0.11996044059834296,-0.04587688574181439, +C2,0.3/location_middle_T,mae,0.7309456467628479,0.7310732305049896,0.6771000519394874,0.7836949959397316,1000,paired source-video group resample,0.0150185227394104,0.014638274908065796,0.003589276969432831,0.027169194817543027,C0,-0.01782172918319702,-0.01855340600013733,-0.05593040585517883,0.019792012870311734, +C2,0.3/location_middle_T,rmse,0.9648965056664569,0.9640838317736533,0.881254471094909,1.0455126336961353,1000,paired source-video group resample,,,,,C0,0.003439230915641689,0.0024906511255801678,-0.0528558877314661,0.06009795815967442, +C2,0.3/location_middle_T,pearson,0.5694351196289062,0.569843590259552,0.5015490487217903,0.6377282187342643,1000,paired source-video group resample,,,,,C0,0.062480807304382324,0.06401567161083221,0.012535480409860612,0.11550071910023688, +C2,0.3/location_end_T,accuracy,0.592032967032967,0.5913313711911358,0.5527415313527058,0.6320757979070435,1000,paired source-video group resample,,,,,C0,0.017857142857142905,0.018258462983017865,-0.019600451601768622,0.05510022373407607, +C2,0.3/location_end_T,macro_f1,0.47134329106322204,0.4706206638706132,0.44042240785846176,0.5050207011355257,1000,paired source-video group resample,,,,,C0,-0.06662488286667101,-0.06656411396621614,-0.10636457236115902,-0.028588205335235654, +C2,0.3/location_end_T,mae,0.7427834868431091,0.742005318403244,0.6878668770194054,0.7991739064455032,1000,paired source-video group resample,0.02685636281967163,0.026891976594924927,-0.008174113929271698,0.05858485847711563,C0,-0.02636939287185669,-0.02705252170562744,-0.07129400074481965,0.019008512794971462, +C2,0.3/location_end_T,rmse,0.9839318807000826,0.9831107058549292,0.8972112239435497,1.0626014433281525,1000,paired source-video group resample,,,,,C0,0.00639931197204191,0.007539502035974477,-0.06470815809828402,0.07139467745040957, +C2,0.3/location_end_T,pearson,0.544383704662323,0.5430675446987152,0.4799082286655903,0.6099565416574478,1000,paired source-video group resample,,,,,C0,0.037699103355407715,0.037661030888557434,-0.024018083512783048,0.10676333233714098, +C2,0.3/span_long_T,accuracy,0.5947802197802198,0.5956678135752268,0.5563146385076359,0.6345574199782871,1000,paired source-video group resample,,,,,C0,0.016483516483516425,0.01651755772050878,-0.020610119047618978,0.04964589910967178, +C2,0.3/span_long_T,macro_f1,0.47208307612039374,0.47098425554258594,0.44158313558578427,0.503754504168362,1000,paired source-video group resample,,,,,C0,-0.0680213989496074,-0.0677406269966036,-0.10630447669278066,-0.02923349193011829, +C2,0.3/span_long_T,mae,0.7405283451080322,0.7394252419471741,0.6868452563881874,0.7923743218183517,1000,paired source-video group resample,0.024601221084594727,0.024040639400482178,0.007662224769592285,0.041699880361557,C0,-0.008593201637268066,-0.008484750986099243,-0.051018379628658295,0.0315895602107048, +C2,0.3/span_long_T,rmse,0.9760344641768165,0.9748805552583105,0.8941139254723033,1.0529488353152872,1000,paired source-video group resample,,,,,C0,0.012136543151946344,0.011463828142171617,-0.041198769601647305,0.062128732581587874, +C2,0.3/span_long_T,pearson,0.561130702495575,0.5617328882217407,0.4973676405847073,0.6261218816041946,1000,paired source-video group resample,,,,,C0,0.061151593923568726,0.061032429337501526,0.014578384160995484,0.11403545290231704, +C2,0.3/span_multi_short_T,accuracy,0.5906593406593407,0.5908138855926617,0.5499947405329594,0.6340061350604593,1000,paired source-video group resample,,,,,C0,0.0027472527472527375,0.0029390931785396868,-0.02877041345786226,0.03417464613730802, +C2,0.3/span_multi_short_T,macro_f1,0.4822995628152073,0.48141226629905076,0.444615477809426,0.519019682999007,1000,paired source-video group resample,,,,,C0,-0.06924489247141102,-0.06888637758947086,-0.10452587223425532,-0.033656791636180614, +C2,0.3/span_multi_short_T,mae,0.7434698343276978,0.7427114844322205,0.6891790300607681,0.7992532253265381,1000,paired source-video group resample,0.027542710304260254,0.027559369802474976,0.006068171560764312,0.04747052490711212,C0,-0.007985711097717285,-0.008503943681716919,-0.04821856170892715,0.03204598426818847, +C2,0.3/span_multi_short_T,rmse,0.9820389048567071,0.9811022258446972,0.9019802862010045,1.0591781419625454,1000,paired source-video group resample,,,,,C0,0.021340799176325587,0.019564235617424652,-0.035707175676665634,0.07565876109290118, +C2,0.3/span_multi_short_T,pearson,0.551609992980957,0.5520462691783905,0.4841053865849972,0.6176887601613998,1000,paired source-video group resample,,,,,C0,0.050001442432403564,0.05041554570198059,0.00011520981788635254,0.10324369668960572, +C2,0.3/location_start_A,accuracy,0.5947802197802198,0.5939473579421017,0.5538642556470101,0.6349542176573426,1000,paired source-video group resample,,,,,C0,0.01098901098901095,0.011275551759073466,-0.02747511922040225,0.04787949792055932, +C2,0.3/location_start_A,macro_f1,0.47841809306200295,0.4778189709244737,0.44559311252119654,0.5113498254501788,1000,paired source-video group resample,,,,,C0,-0.07836206733522427,-0.07800102169653442,-0.11770273926336991,-0.039576588791047196, +C2,0.3/location_start_A,mae,0.7160713076591492,0.7163065671920776,0.663323099911213,0.7669787779450417,1000,paired source-video group resample,0.00014418363571166992,3.6150217056274414e-05,-0.00500619113445282,0.006364613771438598,C0,-0.018927037715911865,-0.019434630870819092,-0.058666400611400604,0.017376585304737086, +C2,0.3/location_start_A,rmse,0.9488575251968607,0.9475669676357426,0.8700613868410982,1.0248394735598525,1000,paired source-video group resample,,,,,C0,0.008060177502193122,0.006671591691955525,-0.04255634531223254,0.056751424417298246, +C2,0.3/location_start_A,pearson,0.5788134932518005,0.5806077420711517,0.5152563244104386,0.6411619439721108,1000,paired source-video group resample,,,,,C0,0.06106984615325928,0.06237834692001343,0.01702329218387604,0.11052736043930053, +C2,0.3/location_middle_A,accuracy,0.5961538461538461,0.5954756651662871,0.5567984364925854,0.6360380814662782,1000,paired source-video group resample,,,,,C0,0.009615384615384581,0.009615457187063692,-0.02614104215604561,0.04548853292351335, +C2,0.3/location_middle_A,macro_f1,0.4753471123037087,0.4748809466873448,0.44573546607877046,0.5067895302495274,1000,paired source-video group resample,,,,,C0,-0.07841571102433204,-0.07805049070356859,-0.11408731242612155,-0.042795510782365334, +C2,0.3/location_middle_A,mae,0.7171043753623962,0.7162021398544312,0.6652256086468696,0.7689183995127677,1000,paired source-video group resample,0.0011772513389587402,0.000638127326965332,-0.005509348213672638,0.009427718818187714,C0,-0.01691889762878418,-0.016692399978637695,-0.05528852194547653,0.017360919713973993, +C2,0.3/location_middle_A,rmse,0.9502102418453959,0.9483952344130101,0.872566249608971,1.0232927569441217,1000,paired source-video group resample,,,,,C0,0.013431306191757919,0.011321229579729086,-0.03932315224348517,0.0626558718680388, +C2,0.3/location_middle_A,pearson,0.574103593826294,0.5762537121772766,0.5116801261901855,0.6363154649734497,1000,paired source-video group resample,,,,,C0,0.05374234914779663,0.05495309829711914,0.00753692090511322,0.1027492508292198, +C2,0.3/location_end_A,accuracy,0.5961538461538461,0.5952054524385915,0.5560241173401357,0.6382415209009721,1000,paired source-video group resample,,,,,C0,0.006868131868131844,0.007220220370509345,-0.031499290461721,0.04329170829170827, +C2,0.3/location_end_A,macro_f1,0.47494276996476636,0.47452944179762224,0.4442365567494339,0.5071167159363424,1000,paired source-video group resample,,,,,C0,-0.07845639130029236,-0.07749591903506176,-0.11635577801524002,-0.03951860442157871, +C2,0.3/location_end_A,mae,0.7157881259918213,0.7161504030227661,0.6627780929207802,0.7662473514676094,1000,paired source-video group resample,-0.00013899803161621094,-0.0002563595771789551,-0.0020588144659996034,0.0025055959820747373,C0,-0.01895880699157715,-0.01899254322052002,-0.05674133747816086,0.017060185968875884, +C2,0.3/location_end_A,rmse,0.9475169684065801,0.9460253746513823,0.8676625748044431,1.0189720363659514,1000,paired source-video group resample,,,,,C0,0.009847547578187621,0.008228362965711722,-0.04194458520671204,0.058531212642809395, +C2,0.3/location_end_A,pearson,0.5792104601860046,0.5806664824485779,0.5149622827768325,0.6405511364340782,1000,paired source-video group resample,,,,,C0,0.060259103775024414,0.06170934438705444,0.01536225974559784,0.11064665019512175, +C2,0.3/span_long_A,accuracy,0.5989010989010989,0.5986392038879889,0.559632164193708,0.6399373205496308,1000,paired source-video group resample,,,,,C0,0.01098901098901095,0.01118881118881121,-0.02657622574055166,0.0479352222365647, +C2,0.3/span_long_A,macro_f1,0.48010176957545375,0.4786503022103693,0.4497085187580653,0.5107100090408145,1000,paired source-video group resample,,,,,C0,-0.07423551107761633,-0.07408612240597678,-0.11212794507968621,-0.035265531620671205, +C2,0.3/span_long_A,mae,0.7114369869232178,0.7118459045886993,0.6595722541213036,0.7631115138530731,1000,paired source-video group resample,-0.0044901371002197266,-0.004373878240585327,-0.008175840973854065,-0.0013466224074363718,C0,-0.02522188425064087,-0.025503337383270264,-0.06238603442907333,0.011031796038150786, +C2,0.3/span_long_A,rmse,0.9440503166799064,0.9424953053725365,0.8647766160342982,1.0181154629708988,1000,paired source-video group resample,,,,,C0,0.006097240126543779,0.0046456829822801304,-0.04334423556993183,0.054493626859312694, +C2,0.3/span_long_A,pearson,0.5808009505271912,0.582606852054596,0.5159701779484749,0.6419116973876953,1000,paired source-video group resample,,,,,C0,0.06327104568481445,0.06492871046066284,0.01900885105133057,0.11197692081332206, +C2,0.3/span_multi_short_A,accuracy,0.6016483516483516,0.6008403773459063,0.561668056623596,0.6426655677824387,1000,paired source-video group resample,,,,,C0,0.006868131868131844,0.0076046116009683695,-0.030734936716851357,0.042296975060773206, +C2,0.3/span_multi_short_A,macro_f1,0.4865729898516784,0.48551164027146454,0.4558704065650155,0.5200520155421656,1000,paired source-video group resample,,,,,C0,-0.07370484573232994,-0.07350935081927612,-0.1113267529597932,-0.03268989413136887, +C2,0.3/span_multi_short_A,mae,0.7110940217971802,0.7111473381519318,0.6594640403985977,0.7634679362177849,1000,paired source-video group resample,-0.004833102226257324,-0.0046912431716918945,-0.008103466033935547,-0.0024337559938430787,C0,-0.025030016899108887,-0.024602681398391724,-0.06374092400074005,0.011096638441085811, +C2,0.3/span_multi_short_A,rmse,0.9443235031618997,0.9429380710213162,0.8645180790099443,1.0178710285637766,1000,paired source-video group resample,,,,,C0,0.0026773535166015883,0.0010916148576180507,-0.04832992656728821,0.05202519566089859, +C2,0.3/span_multi_short_A,pearson,0.5806780457496643,0.5824363529682159,0.5159598290920258,0.641915911436081,1000,paired source-video group resample,,,,,C0,0.06437766551971436,0.06561702489852905,0.019642791152000426,0.11467449888586997, +C2,0.3/location_start_V,accuracy,0.5989010989010989,0.5982386225134255,0.5578662544341534,0.6412238382599362,1000,paired source-video group resample,,,,,C0,0.0027472527472527375,0.003344453880432252,-0.03344072353233386,0.03883490816056105, +C2,0.3/location_start_V,macro_f1,0.49127389556226014,0.4891955886183198,0.4570629588483295,0.5268618505254263,1000,paired source-video group resample,,,,,C0,-0.07253677820770016,-0.07254994765499581,-0.1099857743576148,-0.030924414640084198, +C2,0.3/location_start_V,mae,0.7038062810897827,0.7046139240264893,0.6514796540141106,0.7561280936002731,1000,paired source-video group resample,-0.012120842933654785,-0.011955887079238892,-0.01832551509141922,-0.006232813000679016,C0,-0.029640138149261475,-0.029468655586242676,-0.0673322319984436,0.007145613431930534, +C2,0.3/location_start_V,rmse,0.9373748695789557,0.9364712593376538,0.8570092772769551,1.0117159327086553,1000,paired source-video group resample,,,,,C0,0.0005335495077456454,-0.001132943375846629,-0.04995971665260217,0.04988459467021455, +C2,0.3/location_start_V,pearson,0.5804867148399353,0.5819790661334991,0.5157798871397972,0.6418437004089356,1000,paired source-video group resample,,,,,C0,0.05944627523422241,0.06039893627166748,0.014002475142478944,0.10702668875455856, +C2,0.3/location_middle_V,accuracy,0.6071428571428571,0.6064690026954178,0.5673461420484649,0.6475945295180517,1000,paired source-video group resample,,,,,C0,0.015109890109890056,0.015471197974363027,-0.019810013682571598,0.0491242842853948, +C2,0.3/location_middle_V,macro_f1,0.49345733231256966,0.49323745401144664,0.4619456689779209,0.5253668451090483,1000,paired source-video group resample,,,,,C0,-0.06225164672384648,-0.06171135725027596,-0.09672936263082983,-0.026765741900994733, +C2,0.3/location_middle_V,mae,0.7044275403022766,0.7045295238494873,0.652340005338192,0.7552003964781762,1000,paired source-video group resample,-0.011499583721160889,-0.011294543743133545,-0.01890375167131424,-0.0054980009794235235,C0,-0.029382526874542236,-0.03004947304725647,-0.06396536082029343,0.005218809843063352, +C2,0.3/location_middle_V,rmse,0.9378301039317501,0.9361971066743722,0.8588743188957817,1.0119031037739463,1000,paired source-video group resample,,,,,C0,-0.0010511023768428052,-0.002746004511753053,-0.05128548934642598,0.04909763498620642, +C2,0.3/location_middle_V,pearson,0.5825801491737366,0.5843299627304077,0.5192502394318581,0.641457188129425,1000,paired source-video group resample,,,,,C0,0.06355667114257812,0.06486669182777405,0.01719103306531906,0.11426352635025977, +C2,0.3/location_end_V,accuracy,0.5975274725274725,0.5971033260868812,0.5578137212331741,0.6384660766961652,1000,paired source-video group resample,,,,,C0,0.008241758241758212,0.008626998598345315,-0.028486928410794518,0.04347983845522809, +C2,0.3/location_end_V,macro_f1,0.47637082507472805,0.4756609213487376,0.4456518795125286,0.5081403109138748,1000,paired source-video group resample,,,,,C0,-0.07690556979594376,-0.07589069091262421,-0.11529513368928902,-0.03761286491036308, +C2,0.3/location_end_V,mae,0.7148162722587585,0.7153553664684296,0.6619596436619759,0.7655935361981392,1000,paired source-video group resample,-0.001110851764678955,-0.001061171293258667,-0.0025326400995254517,0.00015425980091094972,C0,-0.018402099609375,-0.018701910972595215,-0.056289784610271454,0.017546930909156794, +C2,0.3/location_end_V,rmse,0.9451361247319756,0.9437858004322437,0.8668543136293582,1.0182658810478509,1000,paired source-video group resample,,,,,C0,0.007691630220315382,0.0064584406208813006,-0.04350812729556921,0.05592197330160429, +C2,0.3/location_end_V,pearson,0.5800597667694092,0.5816244184970856,0.5154706940054894,0.640439935028553,1000,paired source-video group resample,,,,,C0,0.060911357402801514,0.06233862042427063,0.01646047681570053,0.10995246991515159, +C2,0.3/span_long_V,accuracy,0.6016483516483516,0.6011602763123576,0.561894576012223,0.6423661192447843,1000,paired source-video group resample,,,,,C0,0.016483516483516425,0.016416889560405934,-0.020837237631184443,0.051089638054385, +C2,0.3/span_long_V,macro_f1,0.4919942901233187,0.49089259248647377,0.45972277980663395,0.5248650721280452,1000,paired source-video group resample,,,,,C0,-0.05661922664479796,-0.056508529584712586,-0.09378179294927323,-0.01792957830779163, +C2,0.3/span_long_V,mae,0.7091807126998901,0.7095381021499634,0.6588842362165451,0.7605405196547508,1000,paired source-video group resample,-0.006746411323547363,-0.006640523672103882,-0.012982425093650819,-0.0009022876620292683,C0,-0.025177597999572754,-0.025572091341018677,-0.06248779594898224,0.00970180183649063, +C2,0.3/span_long_V,rmse,0.9426353946239638,0.9414192926899563,0.8640082093152242,1.0166750172168233,1000,paired source-video group resample,,,,,C0,0.0048032569053299,0.0030949288221184257,-0.046623278816668945,0.05371737924410122, +C2,0.3/span_long_V,pearson,0.5798429846763611,0.5817065834999084,0.5170114427804947,0.6404590323567391,1000,paired source-video group resample,,,,,C0,0.05996239185333252,0.06156596541404724,0.015349229425191879,0.10733991265296933, +C2,0.3/span_multi_short_V,accuracy,0.6002747252747253,0.6001355013550136,0.559658439324437,0.6414241346125806,1000,paired source-video group resample,,,,,C0,0.012362637362637319,0.01256283389755608,-0.023988005997001464,0.045937310720775275, +C2,0.3/span_multi_short_V,macro_f1,0.48350086071605053,0.4827221558503766,0.4517033368321794,0.5156253066222701,1000,paired source-video group resample,,,,,C0,-0.06795845711485765,-0.06747119192123893,-0.10402352688210208,-0.030657554166195936, +C2,0.3/span_multi_short_V,mae,0.7115349173545837,0.7116321325302124,0.6594920367002487,0.7631366774439812,1000,paired source-video group resample,-0.00439220666885376,-0.004321455955505371,-0.007839095592498778,-0.001103827357292179,C0,-0.022068023681640625,-0.02204078435897827,-0.05831386297941208,0.012407457828521713, +C2,0.3/span_multi_short_V,rmse,0.9438452249447313,0.9428635071691974,0.864112615191235,1.0179670702066193,1000,paired source-video group resample,,,,,C0,0.005912388512827715,0.004560884399750387,-0.04464790244628346,0.05467890689479401, +C2,0.3/span_multi_short_V,pearson,0.5805149078369141,0.5826558768749237,0.5166253760457039,0.6401758477091789,1000,paired source-video group resample,,,,,C0,0.06099891662597656,0.06243099272251129,0.016749420762062074,0.10853291600942609, +C2,0.3/synchrony_sync,accuracy,0.5989010989010989,0.5987727765929585,0.5594253282708432,0.6409571819652488,1000,paired source-video group resample,,,,,C0,0.01098901098901095,0.010457677165354284,-0.020492987015719995,0.04656593298188015, +C2,0.3/synchrony_sync,macro_f1,0.47962028817918206,0.47835429991254874,0.4492359770704302,0.5125191728005944,1000,paired source-video group resample,,,,,C0,-0.06933194283458005,-0.07009481204112017,-0.10383894254599621,-0.03195702229934431, +C2,0.3/synchrony_sync,mae,0.7325150966644287,0.732930064201355,0.6749753251671791,0.7863179951906204,1000,paired source-video group resample,0.01658797264099121,0.01698523759841919,-0.008242711424827576,0.03726052641868591,C0,-0.01042550802230835,-0.011241406202316284,-0.05405507832765579,0.02935555428266525, +C2,0.3/synchrony_sync,rmse,0.9660958262591977,0.9651757694959956,0.8761031970360261,1.0442190620279452,1000,paired source-video group resample,,,,,C0,0.014702614907364575,0.013180132930910027,-0.05176507576137241,0.0744717914243368, +C2,0.3/synchrony_sync,pearson,0.5664559006690979,0.5664995312690735,0.49589718207716943,0.6351595431566238,1000,paired source-video group resample,,,,,C0,0.05153137445449829,0.05397772789001465,-0.001724804937839508,0.11395980119705199, +C2,0.3/synchrony_partial,accuracy,0.5879120879120879,0.5874121220661688,0.5467398351489523,0.6300423154890143,1000,paired source-video group resample,,,,,C0,-0.004120879120879106,-0.0034182686291308606,-0.037486965316224606,0.028868455145827348, 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resample,,,,,C0,0.04187542200088501,0.042714059352874756,-0.011600853502750396,0.09448107033967969, +C2,0.3/synchrony_async,accuracy,0.5906593406593407,0.5906576012312368,0.5513322701750888,0.6300676158181023,1000,paired source-video group resample,,,,,C0,-0.004120879120879106,-0.004081632653061218,-0.037934853068280094,0.02946520050187108, +C2,0.3/synchrony_async,macro_f1,0.4726179792368093,0.4718873655437356,0.4408775165554015,0.5041634921053565,1000,paired source-video group resample,,,,,C0,-0.08473176589897696,-0.08467547440667336,-0.1197132089730192,-0.04858739509871009, +C2,0.3/synchrony_async,mae,0.7457230091094971,0.7451136410236359,0.6888889476656914,0.800988444685936,1000,paired source-video group resample,0.02979588508605957,0.02970561385154724,0.0010959908366203312,0.05542882978916167,C0,-0.011499762535095215,-0.011939972639083862,-0.05539375245571136,0.03301877230405805, 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+C3,0.0/none,mae,0.7170802354812622,0.7156046032905579,0.6639145448803901,0.7703304812312126,1000,paired source-video group resample,,,,,C0,-0.016333699226379395,-0.01734006404876709,-0.05781894475221634,0.024683099985122664, +C3,0.0/none,rmse,0.9519601802071409,0.9474941959410556,0.8683263327658715,1.0329987491635648,1000,paired source-video group resample,,,,,C0,0.014786520778950707,0.014822741783559301,-0.042867190022087935,0.0669030685238819, +C3,0.0/none,pearson,0.5966253280639648,0.5973509550094604,0.5297306656837464,0.6592308267951011,1000,paired source-video group resample,,,,,C0,0.07738274335861206,0.07747094333171844,0.033088904619216916,0.12686202973127364, +C3,0.1/single,accuracy,0.6126373626373627,0.6134755626388486,0.5714189965530447,0.65717519106408,1000,paired source-video group resample,,,,,C0,0.02472527472527475,0.02551926743584454,-0.011259612856200434,0.06024385608276725, +C3,0.1/single,macro_f1,0.5074331536879377,0.5077392051564198,0.4708051490255845,0.547071966556951,1000,paired source-video group resample,,,,,C0,-0.04245164374896859,-0.0414219217186316,-0.08273945654790366,0.000911617612540335, +C3,0.1/single,mae,0.7157126069068909,0.7141960263252258,0.6628350302577019,0.7681829914450645,1000,paired source-video group resample,-0.0013676285743713379,-0.0013465285301208496,-0.005499430000782013,0.002516254782676696,C0,-0.020046591758728027,-0.020808696746826172,-0.061213068664073944,0.020402161777019465, +C3,0.1/single,rmse,0.9521454639877448,0.9484145913205893,0.8691878408428271,1.0328148478658647,1000,paired source-video group resample,,,,,C0,0.012822888426497592,0.012508284129473801,-0.04666847122815622,0.06470910215452635, +C3,0.1/single,pearson,0.5960115790367126,0.5969662666320801,0.5294166103005409,0.6579326599836349,1000,paired source-video group resample,,,,,C0,0.07943606376647949,0.07935918867588043,0.03424882739782333,0.12871250212192537, +C3,0.1/sync,accuracy,0.6098901098901099,0.6102650490397259,0.5682794353223869,0.6545599345253085,1000,paired source-video group resample,,,,,C0,0.02335164835164838,0.02435948944586952,-0.014770785748065628,0.0579540742276592, +C3,0.1/sync,macro_f1,0.49265816381281796,0.49299408399178923,0.45859399997681644,0.529236797500513,1000,paired source-video group resample,,,,,C0,-0.05766989928193528,-0.056698352056272244,-0.09358712903871858,-0.0201869728483241, +C3,0.1/sync,mae,0.7114960551261902,0.7095820009708405,0.6598939448595047,0.7631383016705513,1000,paired source-video group resample,-0.0055841803550720215,-0.00523337721824646,-0.01608676016330719,0.0034772425889968844,C0,-0.023546814918518066,-0.024424433708190918,-0.06290726661682129,0.016369496285915375, +C3,0.1/sync,rmse,0.9394185779587847,0.9363275647416562,0.8582408923850827,1.0176773634152534,1000,paired source-video group resample,,,,,C0,-0.005764686396501961,-0.005982809741127915,-0.06314190867517729,0.04910706609931128, +C3,0.1/sync,pearson,0.607245147228241,0.6074457168579102,0.5408821344375611,0.667614097893238,1000,paired source-video group resample,,,,,C0,0.09384530782699585,0.09497380256652832,0.04798596128821373,0.13990281745791436, +C3,0.1/partial,accuracy,0.6085164835164835,0.6091206179441473,0.566594258309721,0.6555049119516594,1000,paired source-video group resample,,,,,C0,0.015109890109890056,0.015238101380942892,-0.021485619156309827,0.04926764314247667, +C3,0.1/partial,macro_f1,0.49174032060105866,0.4915691621605515,0.458134665090723,0.5300063674397696,1000,paired source-video group resample,,,,,C0,-0.06589261740224661,-0.06505956785369862,-0.10236952233178195,-0.026056059365513324, +C3,0.1/partial,mae,0.7204377055168152,0.7186769545078278,0.667500801384449,0.772548359632492,1000,paired source-video group resample,0.0033574700355529785,0.002913951873779297,-0.011961674690246582,0.020285430550575252,C0,-0.01477968692779541,-0.016247481107711792,-0.05958123356103897,0.028093931078910818, +C3,0.1/partial,rmse,0.9570879861012483,0.9550067742073584,0.871143285581238,1.0421509483245066,1000,paired source-video group resample,,,,,C0,0.019644540694036317,0.018398676297529448,-0.04098570999089089,0.07798862684790094, +C3,0.1/partial,pearson,0.5933700203895569,0.5933354794979095,0.5233057364821434,0.6574082359671592,1000,paired source-video group resample,,,,,C0,0.07279646396636963,0.07436147332191467,0.024187712371349333,0.12676831334829328, +C3,0.1/async,accuracy,0.6126373626373627,0.6128319875880017,0.572786568371842,0.6580951870018393,1000,paired source-video group resample,,,,,C0,0.020604395604395642,0.02153467140062315,-0.01586225043227975,0.05843654670022843, +C3,0.1/async,macro_f1,0.4986475827494779,0.4992102707514282,0.4663799228110079,0.5360288124762013,1000,paired source-video group resample,,,,,C0,-0.060159439129929215,-0.059060056149475904,-0.09783255923190814,-0.018552075196627393, +C3,0.1/async,mae,0.7148625254631042,0.7136245965957642,0.6616725102066994,0.7685697466135025,1000,paired source-video group resample,-0.002217710018157959,-0.002038329839706421,-0.008604709804058076,0.004315702617168424,C0,-0.024031102657318115,-0.025152355432510376,-0.06546227931976319,0.014543078839778883, +C3,0.1/async,rmse,0.9496184712283836,0.9461010215132445,0.8683552137602968,1.0303291095842395,1000,paired source-video group resample,,,,,C0,0.00588382993085923,0.005656826904299972,-0.05529195031738768,0.05702567772227253, +C3,0.1/async,pearson,0.5980018377304077,0.5986056923866272,0.5307797968387604,0.6597115784883499,1000,paired source-video group resample,,,,,C0,0.08398586511611938,0.08415021002292633,0.04075344949960709,0.13321749120950696, +C3,0.3/single,accuracy,0.6098901098901099,0.6106575889137393,0.5692510472920915,0.6558537427979192,1000,paired source-video group resample,,,,,C0,0.004120879120879217,0.005211728596262455,-0.02830572173646264,0.03682051111808588, +C3,0.3/single,macro_f1,0.49425008330224046,0.4940561394566815,0.45894687039222837,0.5323447791350288,1000,paired source-video group resample,,,,,C0,-0.07504916610620777,-0.07394011943960374,-0.11166098513893935,-0.03823138086170626, +C3,0.3/single,mae,0.7236636877059937,0.7220041453838348,0.6725677594542503,0.7774389401078224,1000,paired source-video group resample,0.006583452224731445,0.006598770618438721,-0.002804498374462128,0.015692615509033205,C0,-0.007467448711395264,-0.0075958967208862305,-0.05033087879419327,0.03182409703731536, +C3,0.3/single,rmse,0.9532929569532828,0.950092102168452,0.8696925445160493,1.0313406479219889,1000,paired source-video group resample,,,,,C0,0.01352538221973787,0.01263565281163076,-0.04768045434952651,0.06752563216426284, +C3,0.3/single,pearson,0.597331702709198,0.5981155037879944,0.5299086153507233,0.6591739490628242,1000,paired source-video group resample,,,,,C0,0.0759161114692688,0.07576936483383179,0.02977323830127716,0.12829098403453826, +C3,0.3/sync,accuracy,0.6057692307692307,0.6062284042028065,0.5650916116626916,0.6509188187610665,1000,paired source-video group resample,,,,,C0,0.026098901098901006,0.026024822634992117,-0.008709224929864142,0.05890803687813008, +C3,0.3/sync,macro_f1,0.48499351554462616,0.48476413618085346,0.4525681482813813,0.5188638934839757,1000,paired source-video group resample,,,,,C0,-0.05510747389486165,-0.05461943046597939,-0.08969829760382161,-0.01967536890575698, +C3,0.3/sync,mae,0.7285177111625671,0.7270229458808899,0.6745445698499679,0.7799342781305313,1000,paired source-video group resample,0.011437475681304932,0.011602431535720825,-0.004518055915832519,0.026486018300056455,C0,-0.02438598871231079,-0.02538120746612549,-0.06561042070388794,0.01334472447633742, +C3,0.3/sync,rmse,0.9577771763721012,0.9550639574414945,0.8723957686254342,1.036749019017595,1000,paired source-video group resample,,,,,C0,-0.004515539392176082,-0.006426632400064802,-0.06504344066060541,0.04740033247195877, +C3,0.3/sync,pearson,0.5945711731910706,0.5951205492019653,0.5296235308051109,0.6578360393643379,1000,paired source-video group resample,,,,,C0,0.0963362455368042,0.09786832332611084,0.05203472971916199,0.1461006425321102, +C3,0.3/partial,accuracy,0.6098901098901099,0.6108066982489806,0.5681122974335667,0.6543337015993266,1000,paired source-video group resample,,,,,C0,0.015109890109890167,0.01507882819399814,-0.023756532485875757,0.05382715004253416, +C3,0.3/partial,macro_f1,0.49115001695649024,0.4908980498412524,0.45799855372627596,0.5264002442441301,1000,paired source-video group resample,,,,,C0,-0.0720856306869791,-0.07192584603808241,-0.11085961629756177,-0.030951754622025464, +C3,0.3/partial,mae,0.7223724722862244,0.7214479148387909,0.6716541215777397,0.7737413346767426,1000,paired source-video group resample,0.005292236804962158,0.005181223154067993,-0.008856913447380066,0.020866310596466063,C0,-0.02417922019958496,-0.024771928787231445,-0.06888899654150009,0.01815379410982131, 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+C3,0.3/async,mae,0.7302905917167664,0.7280998528003693,0.6752513840794563,0.7888963088393212,1000,paired source-video group resample,0.01321035623550415,0.01280224323272705,-0.0043903693556785585,0.030426967144012444,C0,-0.03829282522201538,-0.03973513841629028,-0.08420137912034989,0.004261244833469385, +C3,0.3/async,rmse,0.9664461366629807,0.9629187311849706,0.874601089272133,1.0593735414927596,1000,paired source-video group resample,,,,,C0,-0.01665865789294929,-0.018050838063103147,-0.08116090879642245,0.03786983807592003, +C3,0.3/async,pearson,0.5865367650985718,0.5874101519584656,0.5054779142141342,0.6567953556776047,1000,paired source-video group resample,,,,,C0,0.09969082474708557,0.09962031245231628,0.05210872143507004,0.1577252082526684, +C3,0.5/single,accuracy,0.6085164835164835,0.6095427812559286,0.5681818181818182,0.6534819585272928,1000,paired source-video group resample,,,,,C0,0.0219780219780219,0.022861498257839674,-0.013398171768707437,0.057592403034342605, 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+C3,0.5/async,mae,0.7382102608680725,0.7367503941059113,0.6857916712760925,0.794854336977005,1000,paired source-video group resample,0.021130025386810303,0.020724445581436157,0.003183761239051819,0.03981099724769592,C0,-0.055054426193237305,-0.05501246452331543,-0.10223177820444107,-0.012254621088504794, +C3,0.5/async,rmse,0.9747093623364383,0.971045036210882,0.8871676955942862,1.0658424665177817,1000,paired source-video group resample,,,,,C0,-0.028618371307732482,-0.03041785012175746,-0.09466231697360325,0.03216236009728615, +C3,0.5/async,pearson,0.5812525749206543,0.582502007484436,0.5033072859048844,0.6483487382531166,1000,paired source-video group resample,,,,,C0,0.10675787925720215,0.10811693966388702,0.05047245398163795,0.16750340983271597, +C3,0.7/single,accuracy,0.6057692307692307,0.6058902381327866,0.5637867015796704,0.6482081134368292,1000,paired source-video group resample,,,,,C0,0.02060439560439553,0.02140469185118371,-0.014906669985067223,0.05977779494777796, 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+C3,0.7/sync,accuracy,0.5961538461538461,0.5960871149990887,0.5522767949208969,0.6420631403570122,1000,paired source-video group resample,,,,,C0,0.013736263736263687,0.014598700850365298,-0.023824041811846608,0.05144693577204617, +C3,0.7/sync,macro_f1,0.47119937694704045,0.4704808196554713,0.4367229677688112,0.5043026485849287,1000,paired source-video group resample,,,,,C0,-0.07774012315332363,-0.07746005612683113,-0.11690440380047247,-0.03644509639650302, +C3,0.7/sync,mae,0.7866805195808411,0.7866965532302856,0.7316616579890252,0.8405689507722854,1000,paired source-video group resample,0.06960028409957886,0.06977245211601257,0.043309128284454344,0.09622702747583389,C0,0.003308892250061035,0.0031119883060455322,-0.045779375731945036,0.05449162721633911, +C3,0.7/sync,rmse,1.0174537040806868,1.0164063596101993,0.9322989049087168,1.0994524462441684,1000,paired source-video group resample,,,,,C0,-0.0027017374766107327,-0.004630775717096247,-0.0669393591921754,0.05429609857716294, +C3,0.7/sync,pearson,0.5514959692955017,0.5516934096813202,0.48023470789194106,0.6214953750371932,1000,paired source-video group resample,,,,,C0,0.07305091619491577,0.0742557942867279,0.023017456382513048,0.12993075773119928, +C3,0.7/partial,accuracy,0.592032967032967,0.5923027780151454,0.5511285589410589,0.637139411596141,1000,paired source-video group resample,,,,,C0,-0.0013736263736263687,-0.001320132588366052,-0.04121162927981106,0.0399494998561765, +C3,0.7/partial,macro_f1,0.46458888132354637,0.46410192804284267,0.432439067507708,0.49969427276615963,1000,paired source-video group resample,,,,,C0,-0.09942455589306409,-0.09848135123607377,-0.14165251803768203,-0.05783973262204943, +C3,0.7/partial,mae,0.7878201603889465,0.7868720591068268,0.7295992761850357,0.8466428875923157,1000,paired source-video group resample,0.07073992490768433,0.07092732191085815,0.040813618898391725,0.10324259251356124,C0,-0.009771168231964111,-0.011064887046813965,-0.0643392637372017,0.0410576969385147, +C3,0.7/partial,rmse,1.0246115785924825,1.023254069941479,0.9345496996265037,1.1084368647833371,1000,paired source-video group resample,,,,,C0,0.007154886825566642,0.005024096552959767,-0.06242961603349552,0.06897607919617246, +C3,0.7/partial,pearson,0.5424395799636841,0.5421074032783508,0.46880946308374405,0.613610029220581,1000,paired source-video group resample,,,,,C0,0.049962759017944336,0.052091360092163086,-0.010668082535266875,0.11237225160002706, +C3,0.7/async,accuracy,0.5865384615384616,0.5866404199475066,0.5459226768003449,0.6303785715910641,1000,paired source-video group resample,,,,,C0,0.008241758241758212,0.008658170914542684,-0.03062127505869608,0.046978117300477525, +C3,0.7/async,macro_f1,0.45530019418284273,0.45432406536180964,0.42685960758342073,0.48516061053492093,1000,paired source-video group resample,,,,,C0,-0.09849786882506106,-0.0980487743379162,-0.13636699920467216,-0.059031173878404994, +C3,0.7/async,mae,0.7962862849235535,0.7959353923797607,0.735024693608284,0.8544554814696312,1000,paired source-video group resample,0.07920604944229126,0.0783383846282959,0.046334771811962126,0.11302678585052489,C0,-0.020173311233520508,-0.02096995711326599,-0.07532329112291336,0.0288434624671936, +C3,0.7/async,rmse,1.0393429141158677,1.0380072692620348,0.9522967631461038,1.123547440248211,1000,paired source-video group resample,,,,,C0,-0.0014519646584865153,-0.004226524320469105,-0.07358414175190556,0.07301486877472269, +C3,0.7/async,pearson,0.5302903652191162,0.5296413600444794,0.46095208525657655,0.6028841301798821,1000,paired source-video group resample,,,,,C0,0.05109420418739319,0.05434410274028778,-0.01696515306830406,0.1151912547647953, +C3,0.3/modality_T,accuracy,0.6112637362637363,0.6120856085067536,0.5710001079768855,0.6572287642708408,1000,paired source-video group resample,,,,,C0,0.02472527472527475,0.025376591097386436,-0.007163838388828494,0.05811665571576429, +C3,0.3/modality_T,macro_f1,0.4908838142121336,0.49104522207810175,0.4583523082773089,0.5255577304231686,1000,paired source-video group resample,,,,,C0,-0.05587949923157315,-0.055676848053545086,-0.09024202528166937,-0.021608037625528865, +C3,0.3/modality_T,mae,0.732006847858429,0.7304387390613556,0.6788239046931267,0.7885336518287659,1000,paired source-video group resample,0.014926612377166748,0.0149003267288208,-0.0038165777921676633,0.03173524290323257,C0,-0.018116891384124756,-0.01844117045402527,-0.061367250978946686,0.022969301044940917, +C3,0.3/modality_T,rmse,0.9646668059536355,0.9618462825903272,0.8765820963791144,1.0574203845973227,1000,paired source-video group resample,,,,,C0,0.001997474299514912,0.0017218628713164819,-0.06128793295066047,0.05387158221189966, +C3,0.3/modality_T,pearson,0.5902022123336792,0.5917832255363464,0.5108725965023041,0.661033283174038,1000,paired source-video group resample,,,,,C0,0.08843982219696045,0.08932013809680939,0.04323256313800812,0.14194881245493887, +C3,0.3/modality_A,accuracy,0.6098901098901099,0.61050395109587,0.5681752028695755,0.6548687938757588,1000,paired source-video group resample,,,,,C0,0.02335164835164838,0.024140228643905137,-0.013432552189550945,0.06025521002930637, +C3,0.3/modality_A,macro_f1,0.5003632614019909,0.5007790381695245,0.46393158821321206,0.5412996849505903,1000,paired source-video group resample,,,,,C0,-0.05111850725790634,-0.050150174259184166,-0.08904986830088324,-0.010858793987550313, +C3,0.3/modality_A,mae,0.7147579789161682,0.7135427296161652,0.661244586110115,0.767749710381031,1000,paired source-video group resample,-0.002322256565093994,-0.0022295117378234863,-0.004463289678096771,-0.0009482473134994507,C0,-0.01540905237197876,-0.01634228229522705,-0.058243556320667265,0.02589028626680374, +C3,0.3/modality_A,rmse,0.9499571953717086,0.9456311604983281,0.8660529179056106,1.0303789309709963,1000,paired source-video group resample,,,,,C0,0.015644835055628747,0.015642395921979357,-0.044429692755290254,0.06758763616198202, +C3,0.3/modality_A,pearson,0.5963897109031677,0.5972223281860352,0.5295476987957954,0.6591679856181145,1000,paired source-video group resample,,,,,C0,0.07365268468856812,0.0735844075679779,0.02901679202914238,0.12421217113733292, +C3,0.3/modality_V,accuracy,0.6098901098901099,0.6102891427206878,0.5685171207089097,0.65567733550171,1000,paired source-video group resample,,,,,C0,0.02197802197802201,0.022880753590625913,-0.012083401538713378,0.05660377358490565, +C3,0.3/modality_V,macro_f1,0.4989284858669034,0.4986693307104155,0.46441432724486054,0.5400167974958238,1000,paired source-video group resample,,,,,C0,-0.052164860115945344,-0.051290431773180434,-0.0882800808602862,-0.012805426977692746, +C3,0.3/modality_V,mae,0.7170413732528687,0.7157358229160309,0.6629090800881385,0.7709826454520226,1000,paired source-video group resample,-3.886222839355469e-05,3.594160079956055e-05,-0.001664324104785919,0.0010431617498397826,C0,-0.01629173755645752,-0.01741465926170349,-0.05807222872972488,0.02567499130964278, +C3,0.3/modality_V,rmse,0.9520052914732846,0.9479425982760488,0.868791605137847,1.0330452952127167,1000,paired source-video group resample,,,,,C0,0.014212559160658222,0.013966882462453922,-0.04457603659620238,0.06656764848959747, +C3,0.3/modality_V,pearson,0.5969159007072449,0.5975306332111359,0.5302077934145928,0.6594635084271431,1000,paired source-video group resample,,,,,C0,0.07747006416320801,0.07748475670814514,0.03244954422116279,0.1271711193025112, +C3,0.3/modality_TA,accuracy,0.6153846153846154,0.615896759879305,0.5749561126859036,0.6585786601565304,1000,paired source-video group resample,,,,,C0,0.028846153846153855,0.029211849865258488,-0.003931847968545288,0.06456937946663967, +C3,0.3/modality_TA,macro_f1,0.5024003704110033,0.5020351458639543,0.47008919246546194,0.5379212344379718,1000,paired source-video group resample,,,,,C0,-0.051797916749289574,-0.0502129167051697,-0.08341675376019468,-0.015620763295152083, +C3,0.3/modality_TA,mae,0.7302486896514893,0.7300140261650085,0.6792119786143302,0.7835343182086945,1000,paired source-video group resample,0.01316845417022705,0.01349678635597229,-0.0009686574339866637,0.028971211612224577,C0,-0.04533684253692627,-0.04606083035469055,-0.08698828667402267,-0.004007880389690399, +C3,0.3/modality_TA,rmse,0.9633564470305576,0.9614290979876876,0.8792391646659842,1.0445162788894928,1000,paired source-video group resample,,,,,C0,-0.0072646393228792405,-0.008312089736285277,-0.06791985323469177,0.048098647139611754, +C3,0.3/modality_TA,pearson,0.5913560390472412,0.5922068059444427,0.5240315362811089,0.652550283074379,1000,paired source-video group resample,,,,,C0,0.09291607141494751,0.09329766035079956,0.04597550928592682,0.1431595355272293, +C3,0.3/modality_TV,accuracy,0.5975274725274725,0.5972216862820761,0.5551011417782972,0.6443555062632168,1000,paired source-video group resample,,,,,C0,0.015109890109890056,0.01649491548481441,-0.021568720857245302,0.05202904052774242, +C3,0.3/modality_TV,macro_f1,0.4812298940228253,0.4809013939042478,0.4477028547534791,0.5168452132308748,1000,paired source-video group resample,,,,,C0,-0.06361469396603298,-0.062157803981565646,-0.10310034662711265,-0.022211203517871904, +C3,0.3/modality_TV,mae,0.742725670337677,0.7408063113689423,0.6859609887003899,0.80104910582304,1000,paired source-video group resample,0.025645434856414795,0.02494072914123535,0.004483704268932342,0.04614184945821762,C0,-0.01794809103012085,-0.01786428689956665,-0.06364698708057404,0.021801315248012536, +C3,0.3/modality_TV,rmse,0.9803810232362419,0.9762210246232617,0.887897298070125,1.069482796976121,1000,paired source-video group resample,,,,,C0,0.012813932430353003,0.01163949286477578,-0.05185180175015704,0.0665854709882164, +C3,0.3/modality_TV,pearson,0.5745789408683777,0.575908750295639,0.4926375709474087,0.6482042744755745,1000,paired source-video group resample,,,,,C0,0.07559213042259216,0.0763881504535675,0.027911814302206038,0.13183620646595956, +C3,0.3/modality_AV,accuracy,0.6112637362637363,0.6117093744564902,0.5701482081167142,0.6556484247147549,1000,paired source-video group resample,,,,,C0,0.016483516483516536,0.017646777005719982,-0.015791687130443495,0.053210628995076455, +C3,0.3/modality_AV,macro_f1,0.506149828610671,0.5065708094626058,0.4687534353486282,0.5473514524729204,1000,paired source-video group resample,,,,,C0,-0.05354837762844111,-0.052460830967794164,-0.08964057064024676,-0.010892020685727115, +C3,0.3/modality_AV,mae,0.7144672870635986,0.7129254043102264,0.6613860487937927,0.7677353277802468,1000,paired source-video group resample,-0.0026129484176635742,-0.0027513504028320312,-0.007101719081401825,0.00263620913028717,C0,-0.0235135555267334,-0.02405640482902527,-0.06337234079837799,0.017485903203487394, +C3,0.3/modality_AV,rmse,0.9513030852695343,0.9472210386715045,0.8686016650806823,1.0303449212214733,1000,paired source-video group resample,,,,,C0,0.00926785776794381,0.008519307013855448,-0.04806322745890111,0.06040020768404211, +C3,0.3/modality_AV,pearson,0.5951568484306335,0.5956951975822449,0.5278365477919579,0.6570694029331208,1000,paired source-video group resample,,,,,C0,0.07962292432785034,0.07960778474807739,0.03430922254920006,0.12967523187398908, +C3,0.3/modality_TAV,accuracy,0.6085164835164835,0.609406703506268,0.566752634888966,0.6527392043261393,1000,paired source-video group resample,,,,,C0,0.027472527472527375,0.028343410426620474,-0.006964518768139943,0.06456680737201151, +C3,0.3/modality_TAV,macro_f1,0.4931643958459892,0.4925250509750181,0.4571651176558851,0.5298099034878142,1000,paired source-video group resample,,,,,C0,-0.051313502758292995,-0.051253239787752675,-0.08905556834953512,-0.008596092403451765, +C3,0.3/modality_TAV,mae,0.7309597730636597,0.7300606966018677,0.6787432938814163,0.7818764820694923,1000,paired source-video group resample,0.013879537582397461,0.014343619346618652,-0.009901602566242217,0.03547090888023376,C0,-0.03997194766998291,-0.04058849811553955,-0.08439677208662033,0.001970456540584547, +C3,0.3/modality_TAV,rmse,0.956704375828628,0.9554129153110915,0.8748705779484288,1.0371515023678766,1000,paired source-video group resample,,,,,C0,-0.023333385832741138,-0.02308363484881809,-0.08034561328811664,0.03129162325488696, +C3,0.3/modality_TAV,pearson,0.5956684350967407,0.59564009308815,0.5276330292224884,0.6583825215697288,1000,paired source-video group resample,,,,,C0,0.10535892844200134,0.10765689611434937,0.05472401082515717,0.15334795340895652, +C3,0.3/location_start_T,accuracy,0.5934065934065934,0.593841642228739,0.5520970765674336,0.6398376119087119,1000,paired source-video group resample,,,,,C0,0.0013736263736263687,0.002000982541002172,-0.03406258615689238,0.03951049893009434, +C3,0.3/location_start_T,macro_f1,0.4793691067543829,0.4790445737216608,0.4449647537959383,0.5175147083207262,1000,paired source-video group resample,,,,,C0,-0.08182206681393994,-0.08080537654642639,-0.11736312005485311,-0.04412079877200977, +C3,0.3/location_start_T,mae,0.7465300559997559,0.7457560300827026,0.6922345593571663,0.7969803974032402,1000,paired source-video group resample,0.029449820518493652,0.028710007667541504,0.016699549555778504,0.04409014284610748,C0,-0.022731125354766846,-0.023456275463104248,-0.07082708030939103,0.023961347341537473, +C3,0.3/location_start_T,rmse,0.9829546960478771,0.9807857270195748,0.8972224446612206,1.061519614461787,1000,paired source-video group resample,,,,,C0,0.007640766435817015,0.00701211431840526,-0.05616148224328199,0.06074174691811803, +C3,0.3/location_start_T,pearson,0.5679339170455933,0.568588376045227,0.4989545583724976,0.6338432282209396,1000,paired source-video group resample,,,,,C0,0.08538445830345154,0.08569248020648956,0.03601503074169159,0.13869261741638184, +C3,0.3/location_middle_T,accuracy,0.6071428571428571,0.6077615057932881,0.5662959911657947,0.6526430366646955,1000,paired source-video group resample,,,,,C0,0.017857142857142794,0.01911270813375726,-0.015258883305582688,0.0530825752014888, +C3,0.3/location_middle_T,macro_f1,0.4876354238033967,0.48791338268949624,0.4543484248628986,0.5223775011982578,1000,paired source-video group resample,,,,,C0,-0.06316607988292017,-0.06237418891268387,-0.09943620395408145,-0.023198477466514985, +C3,0.3/location_middle_T,mae,0.7293169498443604,0.728069007396698,0.6763676702976227,0.7824603840708733,1000,paired source-video group resample,0.012236714363098145,0.011916190385818481,-0.004205788671970367,0.029066698253154753,C0,-0.01945042610168457,-0.019925355911254883,-0.062010949850082396,0.019215197861194595, +C3,0.3/location_middle_T,rmse,0.9628131827575185,0.9599865029855326,0.8777566036894434,1.0403167701088667,1000,paired source-video group resample,,,,,C0,0.0013559080067032658,9.933022395330893e-05,-0.05941360910776912,0.052317368074044704, +C3,0.3/location_middle_T,pearson,0.5903710722923279,0.5902280211448669,0.5228990092873573,0.6537869617342948,1000,paired source-video group resample,,,,,C0,0.08341675996780396,0.08444277942180634,0.03299007415771484,0.1381569728255272, +C3,0.3/location_end_T,accuracy,0.6071428571428571,0.6077715259136898,0.5635119891598159,0.6519932682806324,1000,paired source-video group resample,,,,,C0,0.03296703296703296,0.03358778625954195,-0.0015278193135928554,0.06666903409090907, +C3,0.3/location_end_T,macro_f1,0.4898199937576475,0.4898371373741941,0.45560513844700223,0.5253455680863359,1000,paired source-video group resample,,,,,C0,-0.048148180172245536,-0.047140456020934,-0.08400842810553377,-0.013570210309591841, +C3,0.3/location_end_T,mae,0.7465690970420837,0.745170533657074,0.6922998338937759,0.8082631036639214,1000,paired source-video group resample,0.029488861560821533,0.029040545225143433,0.005133633315563202,0.05195293128490446,C0,-0.02258378267288208,-0.024007439613342285,-0.06732613295316696,0.01811903715133667, +C3,0.3/location_end_T,rmse,0.9823456994436758,0.978792794066853,0.8942901532512098,1.0730947229515293,1000,paired source-video group resample,,,,,C0,0.00481313071563505,0.0037720906711263824,-0.06317749827323105,0.06364151960924064, +C3,0.3/location_end_T,pearson,0.5887442231178284,0.5890999734401703,0.5119454801082611,0.6596619933843613,1000,paired source-video group resample,,,,,C0,0.08205962181091309,0.08301451802253723,0.03831276595592499,0.13382561802864074, +C3,0.3/span_long_T,accuracy,0.6098901098901099,0.6106982031617302,0.569208783003551,0.6552265911555054,1000,paired source-video group resample,,,,,C0,0.03159340659340659,0.032563174365490166,-0.005571615014511977,0.06698108180869802, +C3,0.3/span_long_T,macro_f1,0.4872728855753121,0.486785405246152,0.45617596454980314,0.523317893569927,1000,paired source-video group resample,,,,,C0,-0.052831589494689024,-0.05147130151089682,-0.09011700833138665,-0.015591368850065247, +C3,0.3/span_long_T,mae,0.7339414954185486,0.732835054397583,0.6758992210030556,0.7951135829091072,1000,paired source-video group resample,0.016861259937286377,0.016526639461517334,-0.004020729660987854,0.03697161227464676,C0,-0.015180051326751709,-0.01613330841064453,-0.058676677942276004,0.024436564743518824, +C3,0.3/span_long_T,rmse,0.9738111571766707,0.969643811068467,0.8838142815920417,1.0682973798815192,1000,paired source-video group resample,,,,,C0,0.009913236151800509,0.009063391538264631,-0.05326286292573479,0.06336982739084288, +C3,0.3/span_long_T,pearson,0.5825886130332947,0.5839605629444122,0.5007984206080437,0.6547305420041084,1000,paired source-video group resample,,,,,C0,0.08260950446128845,0.08456163108348846,0.036528459191322325,0.13408099859952924, +C3,0.3/span_multi_short_T,accuracy,0.6016483516483516,0.6018296251179345,0.5604316155686019,0.6480041529940207,1000,paired source-video group resample,,,,,C0,0.013736263736263687,0.01470588235294118,-0.020193797980287233,0.04878713364790327, +C3,0.3/span_multi_short_T,macro_f1,0.47605249115746906,0.47603214455349463,0.44456045978578396,0.5113366967269759,1000,paired source-video group resample,,,,,C0,-0.07549196412914927,-0.07365469033083571,-0.11104946410073858,-0.03826418078269244, +C3,0.3/span_multi_short_T,mae,0.742709219455719,0.7417836785316467,0.68980662971735,0.7928549408912658,1000,paired source-video group resample,0.025628983974456787,0.02509474754333496,0.008002591133117676,0.04315800815820694,C0,-0.008746325969696045,-0.01004597544670105,-0.05274506062269211,0.030123779177665698, +C3,0.3/span_multi_short_T,rmse,0.9691388365034447,0.9671576548370998,0.8851915554098647,1.0422275071521219,1000,paired source-video group resample,,,,,C0,0.00844073082306318,0.0065889601923806995,-0.05077701712891374,0.058572260638574056, +C3,0.3/span_multi_short_T,pearson,0.5862954258918762,0.5884627103805542,0.5192553609609604,0.6504557996988296,1000,paired source-video group resample,,,,,C0,0.08468687534332275,0.08618441224098206,0.03867076262831688,0.13612247109413148, +C3,0.3/location_start_A,accuracy,0.614010989010989,0.6144914651493598,0.5721734148204736,0.6571588859947906,1000,paired source-video group resample,,,,,C0,0.030219780219780223,0.031029680910320656,-0.005465231489821659,0.06809306347857753, +C3,0.3/location_start_A,macro_f1,0.5130200076026159,0.5132929054905451,0.47538358596888025,0.5514301193771137,1000,paired source-video group resample,,,,,C0,-0.04376015279461132,-0.04290402730536702,-0.08206278542175971,-0.0026732823841933654, +C3,0.3/location_start_A,mae,0.7031530141830444,0.7015696465969086,0.6507922351360321,0.7560118034482002,1000,paired source-video group resample,-0.013927221298217773,-0.013569742441177368,-0.021468913555145262,-0.008168593049049377,C0,-0.0318453311920166,-0.03316333889961243,-0.07358747869729995,0.00769946873188017, +C3,0.3/location_start_A,rmse,0.9375210123886273,0.9334151750955235,0.8546883306328367,1.0168088813006604,1000,paired source-video group resample,,,,,C0,-0.0032763353060403233,-0.004422706597418946,-0.05883996960540102,0.04486268439116542, +C3,0.3/location_start_A,pearson,0.6028702855110168,0.6036265790462494,0.5364824503660202,0.6651968866586685,1000,paired source-video group resample,,,,,C0,0.08512663841247559,0.0863509327173233,0.04268138408660889,0.1332759469747543, +C3,0.3/location_middle_A,accuracy,0.6085164835164835,0.6088968788925502,0.5673051075268817,0.6530371146004392,1000,paired source-video group resample,,,,,C0,0.0219780219780219,0.022524967636272764,-0.014058675098681713,0.0582472481112213, +C3,0.3/location_middle_A,macro_f1,0.5023301428035931,0.502197808717728,0.4646558334212925,0.5432900450016318,1000,paired source-video group resample,,,,,C0,-0.051432680524447605,-0.05082806460185951,-0.08954434224653327,-0.011738724027038728, +C3,0.3/location_middle_A,mae,0.7134491801261902,0.7122405171394348,0.6604156658053398,0.7670514702796936,1000,paired source-video group resample,-0.0036310553550720215,-0.0034897923469543457,-0.006528864800930023,-0.0013189017772674565,C0,-0.020574092864990234,-0.021310269832611084,-0.06172113716602325,0.0199441984295845, +C3,0.3/location_middle_A,rmse,0.9487972186957245,0.9445097432461879,0.8651887090305711,1.0292820495620356,1000,paired source-video group resample,,,,,C0,0.01201828304208652,0.012004870106644083,-0.04791461575122855,0.06418009271991308, +C3,0.3/location_middle_A,pearson,0.5962650179862976,0.5969748497009277,0.5291495114564896,0.6585860759019851,1000,paired source-video group resample,,,,,C0,0.07590377330780029,0.0764249861240387,0.03064451664686203,0.12495877966284752, +C3,0.3/location_end_A,accuracy,0.6098901098901099,0.6101215521271621,0.5685392228739004,0.6556404385449219,1000,paired source-video group resample,,,,,C0,0.020604395604395642,0.02133739837398374,-0.015157342657342645,0.056290584415584495, +C3,0.3/location_end_A,macro_f1,0.4987683934922384,0.49852799841626527,0.46376379085575126,0.5395955315004504,1000,paired source-video group resample,,,,,C0,-0.05463076777282033,-0.0536517650751164,-0.09083396958334038,-0.013754861735482847, +C3,0.3/location_end_A,mae,0.7137581706047058,0.71207395195961,0.6615562483668327,0.7672385975718499,1000,paired source-video group resample,-0.0033220648765563965,-0.003215193748474121,-0.009216633439064027,-3.0438601970672733e-05,C0,-0.020988762378692627,-0.021825700998306274,-0.06287043243646621,0.020040066540241236, +C3,0.3/location_end_A,rmse,0.9467939638013896,0.942593992190645,0.8638686669091362,1.0286126599252001,1000,paired source-video group resample,,,,,C0,0.00912454297299714,0.008437265689047957,-0.04890032376054949,0.06105384196214534, +C3,0.3/location_end_A,pearson,0.600132167339325,0.6007272005081177,0.5339677721261978,0.6632803842425347,1000,paired source-video group resample,,,,,C0,0.08118081092834473,0.08154618740081787,0.03595581203699112,0.13116849809885026, +C3,0.3/span_long_A,accuracy,0.614010989010989,0.6145764348785872,0.5714237711213518,0.6585737946264262,1000,paired source-video group resample,,,,,C0,0.026098901098901117,0.026729577485973877,-0.010894730773665345,0.06392244318181811, +C3,0.3/span_long_A,macro_f1,0.5086147615868403,0.5089075500378517,0.47067080191489424,0.5487889979462276,1000,paired source-video group resample,,,,,C0,-0.045722519066229816,-0.044302030158791084,-0.08429336095208426,-0.0030304530974780298, +C3,0.3/span_long_A,mae,0.7085235714912415,0.7070678770542145,0.656327611207962,0.7624730512499809,1000,paired source-video group resample,-0.008556663990020752,-0.008272379636764526,-0.015728873014450074,-0.0032207280397415178,C0,-0.028135299682617188,-0.028930217027664185,-0.06995974034070969,0.012824322283267974, +C3,0.3/span_long_A,rmse,0.942797918260677,0.9386339640010614,0.8599445187987611,1.022663492470453,1000,paired source-video group resample,,,,,C0,0.004844841707314473,0.004515770838467326,-0.05320136334321401,0.056284560784625216, +C3,0.3/span_long_A,pearson,0.6017601490020752,0.6023356020450592,0.5356867223978042,0.6638555094599724,1000,paired source-video group resample,,,,,C0,0.08423024415969849,0.08448578417301178,0.03983314633369446,0.1326729692518711, +C3,0.3/span_multi_short_A,accuracy,0.614010989010989,0.6148007195349909,0.5720171867586966,0.6586602717556223,1000,paired source-video group resample,,,,,C0,0.019230769230769273,0.020408201042530494,-0.01626106594399275,0.05473476663785653, +C3,0.3/span_multi_short_A,macro_f1,0.5083291589190543,0.5089565451730986,0.4715332234708202,0.5490965123928383,1000,paired source-video group resample,,,,,C0,-0.05194867666495406,-0.05024485157585834,-0.08740301497334943,-0.009701528473173602, +C3,0.3/span_multi_short_A,mae,0.7089516520500183,0.7074446380138397,0.6566918805241585,0.7617249578237534,1000,paired source-video group resample,-0.008128583431243896,-0.007902264595031738,-0.015179137885570525,-0.0031967923045158396,C0,-0.027172386646270752,-0.028088510036468506,-0.06959650367498398,0.01534873396158217, +C3,0.3/span_multi_short_A,rmse,0.943282888403786,0.939146772901096,0.8604646588856985,1.0229152599849196,1000,paired source-video group resample,,,,,C0,0.00163673875848791,0.0008504926776696786,-0.05870066745814604,0.05307118023947826, +C3,0.3/span_multi_short_A,pearson,0.6015817523002625,0.6023958623409271,0.535572636127472,0.6639562651515007,1000,paired source-video group resample,,,,,C0,0.0852813720703125,0.08567233383655548,0.04101904928684234,0.13478911072015762, +C3,0.3/location_start_V,accuracy,0.6153846153846154,0.6159397174432371,0.5742872538897643,0.6607748494662895,1000,paired source-video group resample,,,,,C0,0.019230769230769273,0.0198322007075033,-0.01752258964638167,0.056657223796033995, +C3,0.3/location_start_V,macro_f1,0.5138610200958919,0.5145539958213117,0.4774493736520931,0.5554462433275547,1000,paired source-video group resample,,,,,C0,-0.04994965367406845,-0.04913675412199464,-0.08835455096538788,-0.006534957510747651, +C3,0.3/location_start_V,mae,0.7119380235671997,0.7106110453605652,0.6580780625343323,0.7658981442451477,1000,paired source-video group resample,-0.0051422119140625,-0.005142569541931152,-0.009403061866760255,-0.001829187572002414,C0,-0.021508395671844482,-0.022573620080947876,-0.0620731920003891,0.01895885169506072, +C3,0.3/location_start_V,rmse,0.9485688673163747,0.9444915573139039,0.8650349534262936,1.0285192692832765,1000,paired source-video group resample,,,,,C0,0.011727547245164671,0.011937862916448772,-0.04600457063934081,0.06254884632093644, +C3,0.3/location_start_V,pearson,0.5979459285736084,0.5986596047878265,0.5308774948120117,0.6599991217255592,1000,paired source-video group resample,,,,,C0,0.07690548896789551,0.07643844187259674,0.032984796166419986,0.12687387987971302, +C3,0.3/location_middle_V,accuracy,0.6098901098901099,0.6102891427206878,0.5685171207089097,0.65567733550171,1000,paired source-video group resample,,,,,C0,0.017857142857142905,0.018654238792720768,-0.015224798033017208,0.05339298225858923, +C3,0.3/location_middle_V,macro_f1,0.4989284858669034,0.4986693307104155,0.46441432724486054,0.5400167974958238,1000,paired source-video group resample,,,,,C0,-0.056780493169512725,-0.055472941982484925,-0.09376626445732458,-0.015991978391678582, +C3,0.3/location_middle_V,mae,0.7164756655693054,0.715098649263382,0.662284454703331,0.7706324264407158,1000,paired source-video group resample,-0.0006045699119567871,-0.0005436241626739502,-0.002444234490394592,0.0007212176918983454,C0,-0.017334401607513428,-0.01792725920677185,-0.05974605530500412,0.024531026184558866, +C3,0.3/location_middle_V,rmse,0.9516112705003446,0.9476098657515453,0.8681969748007489,1.033030954824971,1000,paired source-video group resample,,,,,C0,0.0127300641917516,0.012728088123788728,-0.04648089804414978,0.0653054228785687, +C3,0.3/location_middle_V,pearson,0.5965531468391418,0.597224771976471,0.5294073164463043,0.6591616317629814,1000,paired source-video group resample,,,,,C0,0.0775296688079834,0.07767513394355774,0.032089175283908845,0.12647076547145844, +C3,0.3/location_end_V,accuracy,0.6085164835164835,0.6089076775124218,0.5675931366495505,0.653505519037579,1000,paired source-video group resample,,,,,C0,0.019230769230769162,0.01987602761630647,-0.016110302706341235,0.054256804082951485, +C3,0.3/location_end_V,macro_f1,0.49763920375337345,0.4973406855996474,0.4616859392255865,0.5389805018703048,1000,paired source-video group resample,,,,,C0,-0.05563719111729837,-0.054827745951071205,-0.09312688366752514,-0.015536837914946356, +C3,0.3/location_end_V,mae,0.7166463732719421,0.7151671350002289,0.6633379846811295,0.7696295037865638,1000,paired source-video group resample,-0.00043386220932006836,-0.00042951107025146484,-0.0010171175003051759,0.00012362748384475686,C0,-0.016571998596191406,-0.017678529024124146,-0.058272837102413176,0.024117925763130186, +C3,0.3/location_end_V,rmse,0.9509495782852943,0.9465482573788597,0.8672542677505403,1.0318942463919372,1000,paired source-video group resample,,,,,C0,0.013505083773634019,0.01367196416176919,-0.04506648502651089,0.06581392947873897, +C3,0.3/location_end_V,pearson,0.5967321395874023,0.5974868535995483,0.5297795727849006,0.6597610682249069,1000,paired source-video group resample,,,,,C0,0.07758373022079468,0.07745802402496338,0.03317624628543854,0.12714117392897606, +C3,0.3/span_long_V,accuracy,0.6098901098901099,0.6102891427206878,0.5685171207089097,0.65567733550171,1000,paired source-video group resample,,,,,C0,0.02472527472527475,0.026261242673635776,-0.009911577440929941,0.0597794472459303, +C3,0.3/span_long_V,macro_f1,0.4989284858669034,0.4986693307104155,0.46441432724486054,0.5400167974958238,1000,paired source-video group resample,,,,,C0,-0.049685030901213234,-0.04836300187253098,-0.086051106270568,-0.010407562140588461, +C3,0.3/span_long_V,mae,0.7174816131591797,0.7160951197147369,0.6637105464935302,0.7711890786886215,1000,paired source-video group resample,0.00040137767791748047,0.00045689940452575684,-0.0011609375476837158,0.0015162914991378785,C0,-0.016876697540283203,-0.017886608839035034,-0.05847949534654617,0.023840509355068207, +C3,0.3/span_long_V,rmse,0.9524375124581569,0.9480940194454628,0.8689644052118993,1.0337343939363541,1000,paired source-video group resample,,,,,C0,0.014605374739522947,0.014789519732649747,-0.04332676469286165,0.06734513807149858, +C3,0.3/span_long_V,pearson,0.5971121788024902,0.5977010428905487,0.5301537320017815,0.6596368014812469,1000,paired source-video group resample,,,,,C0,0.07723158597946167,0.07756894826889038,0.0335664376616478,0.12678624019026755, +C3,0.3/span_multi_short_V,accuracy,0.6071428571428571,0.607731743214047,0.5657898302991421,0.6519432001650945,1000,paired source-video group resample,,,,,C0,0.019230769230769162,0.020129413710410937,-0.015246727499864283,0.05397834342165381, +C3,0.3/span_multi_short_V,macro_f1,0.49417740607604194,0.4940612262275331,0.459742841714665,0.5317126815409188,1000,paired source-video group resample,,,,,C0,-0.057281911754866244,-0.05631309702603768,-0.09370066227514716,-0.01769266630689742, +C3,0.3/span_multi_short_V,mae,0.7198209762573242,0.7179659307003021,0.667256335914135,0.7731165409088134,1000,paired source-video group resample,0.0027407407760620117,0.002649933099746704,0.0014720410108566284,0.005061537027359009,C0,-0.013781964778900146,-0.014562606811523438,-0.05596472173929214,0.026794882118701933, +C3,0.3/span_multi_short_V,rmse,0.9542627266806466,0.9499560960789928,0.8702356502108037,1.035591693500361,1000,paired source-video group resample,,,,,C0,0.016329890248742984,0.016662080335761442,-0.041205098195991455,0.06821286359945623, +C3,0.3/span_multi_short_V,pearson,0.596470832824707,0.5971465706825256,0.5295115441083909,0.658729587495327,1000,paired source-video group resample,,,,,C0,0.07695484161376953,0.0770668089389801,0.033181166648864745,0.1268135704100132, +C3,0.3/synchrony_sync,accuracy,0.6057692307692307,0.6065466623807994,0.565984021515583,0.6496498341924681,1000,paired source-video group resample,,,,,C0,0.017857142857142794,0.018570521748192736,-0.014750901343821685,0.05216290010454434, +C3,0.3/synchrony_sync,macro_f1,0.4881817344938774,0.488474965659716,0.4569564266711679,0.5230376204172303,1000,paired source-video group resample,,,,,C0,-0.0607704965198847,-0.059223837325015016,-0.09512233005491529,-0.020901081481318303, +C3,0.3/synchrony_sync,mae,0.7392285466194153,0.7359806895256042,0.6838678359985352,0.7959519892930984,1000,paired source-video group resample,0.022148311138153076,0.02171224355697632,0.0008666634559631358,0.04268773049116134,C0,-0.0037120580673217773,-0.004855334758758545,-0.050108264386653896,0.03609851449728012, +C3,0.3/synchrony_sync,rmse,0.9758488908814854,0.9726018002876649,0.8817926623875576,1.0682342784064351,1000,paired source-video group resample,,,,,C0,0.02445567952965233,0.022247499621615652,-0.04369619812502412,0.07967059989418787, +C3,0.3/synchrony_sync,pearson,0.5791566371917725,0.5805416703224182,0.49919675216078757,0.6523820921778679,1000,paired source-video group resample,,,,,C0,0.06423211097717285,0.0669236034154892,0.015773366391658782,0.12159265875816345, +C3,0.3/synchrony_partial,accuracy,0.6181318681318682,0.6183577413840471,0.5780082337063946,0.66247508368291,1000,paired source-video group resample,,,,,C0,0.026098901098901117,0.02661069645641878,-0.007924860420705842,0.06000891632373108, +C3,0.3/synchrony_partial,macro_f1,0.5051258955586794,0.505110912097096,0.470463138799592,0.5420073748496115,1000,paired source-video group resample,,,,,C0,-0.05172303171762149,-0.05000486807984364,-0.08820338964901438,-0.012645674272772798, +C3,0.3/synchrony_partial,mae,0.7251508235931396,0.7242235243320465,0.6752995729446412,0.7746389850974083,1000,paired source-video group resample,0.008070588111877441,0.00807267427444458,-0.01332402378320694,0.029637324810028072,C0,-0.029804229736328125,-0.0313149094581604,-0.06774115562438965,0.0078003510832786414, +C3,0.3/synchrony_partial,rmse,0.9488413496104877,0.9455621240933318,0.8727393001515585,1.023916202981008,1000,paired source-video group resample,,,,,C0,-0.0049066494962041185,-0.006806094550442565,-0.05661564786248996,0.04625194504673874, +C3,0.3/synchrony_partial,pearson,0.6016477942466736,0.6019212305545807,0.5392459958791733,0.6628203436732292,1000,paired source-video group resample,,,,,C0,0.0939035415649414,0.09638230502605438,0.05062521994113922,0.13627572357654572, +C3,0.3/synchrony_async,accuracy,0.6043956043956044,0.6048212050128396,0.5635295722266193,0.6507518501674453,1000,paired source-video group resample,,,,,C0,0.009615384615384581,0.01032353221048632,-0.022864432703003316,0.043453538228630316, +C3,0.3/synchrony_async,macro_f1,0.491820222170069,0.49146226184075414,0.45810881389673946,0.5292785859642924,1000,paired source-video group resample,,,,,C0,-0.06552952296571729,-0.06430332725605767,-0.09979801846500026,-0.02876396661367031, +C3,0.3/synchrony_async,mae,0.7344034910202026,0.7332303524017334,0.6783451497554779,0.7865106269717216,1000,paired source-video group resample,0.01732325553894043,0.01718759536743164,-0.005046845972537994,0.03834327757358551,C0,-0.02281928062438965,-0.022821873426437378,-0.06709843426942826,0.01675909161567686, +C3,0.3/synchrony_async,rmse,0.9649652566733213,0.961945052326665,0.8793720832422971,1.0445823375364522,1000,paired source-video group resample,,,,,C0,-0.0021251282142349393,-0.0035285080243669387,-0.06101655518450179,0.04938532760384777, +C3,0.3/synchrony_async,pearson,0.5873648524284363,0.5880985856056213,0.5204508602619171,0.6524789541959762,1000,paired source-video group resample,,,,,C0,0.08964762091636658,0.09050607681274414,0.04129168093204499,0.1405468299984932, +C4,0.0/none,accuracy,0.6098901098901099,0.609280979598317,0.569748411208204,0.6484417243530706,1000,paired source-video group resample,,,,,C0,0.017857142857142905,0.01773536725182767,-0.015652299121508898,0.05428021623978708, +C4,0.0/none,macro_f1,0.5569878493378154,0.5563018650748057,0.5185708987514359,0.5952754623956661,1000,paired source-video group resample,,,,,C0,0.0010532366867849197,0.0008671411094854364,-0.036818795330055304,0.04233318093157744, +C4,0.0/none,mae,0.6913279294967651,0.6911936402320862,0.6413895487785339,0.7435645565390586,1000,paired source-video group resample,,,,,C0,-0.042086005210876465,-0.04263550043106079,-0.08203034698963166,-0.003885559737682343, +C4,0.0/none,rmse,0.9513293376826223,0.9490658044083926,0.8712569524042632,1.029922531079829,1000,paired source-video group resample,,,,,C0,0.014155678254432091,0.01274076203711011,-0.04885947774468457,0.07298812941776582, +C4,0.0/none,pearson,0.5684858560562134,0.5682405531406403,0.4988481506705284,0.6357528358697891,1000,paired source-video group resample,,,,,C0,0.049243271350860596,0.0500015914440155,-0.006941637396812438,0.10447049289941784, +C4,0.1/single,accuracy,0.6085164835164835,0.608061250903078,0.5696001838235294,0.6474734113623003,1000,paired source-video group resample,,,,,C0,0.02060439560439553,0.020917767385894348,-0.014247920168972857,0.0575668056842755, +C4,0.1/single,macro_f1,0.5553551268968435,0.5547733762855966,0.5176056682428751,0.5920734637604536,1000,paired source-video group resample,,,,,C0,0.0054703294599371954,0.0057853603194514824,-0.03435260688103446,0.046213632792851254, +C4,0.1/single,mae,0.692819356918335,0.6929545402526855,0.6445789739489556,0.7450352028012276,1000,paired source-video group resample,0.0014914274215698242,0.001508176326751709,-0.005727596580982208,0.009412699937820432,C0,-0.042939841747283936,-0.04321366548538208,-0.08336851298809052,-0.004494513571262363, +C4,0.1/single,rmse,0.9506498623718602,0.9487756058654957,0.8710333971031555,1.0292687321970138,1000,paired source-video group resample,,,,,C0,0.011327286810613013,0.01048744406553509,-0.05214655227743487,0.07097754796932373, +C4,0.1/single,pearson,0.568820595741272,0.5677261054515839,0.5012456342577934,0.6339727312326431,1000,paired source-video group resample,,,,,C0,0.05224508047103882,0.05318157374858856,-0.000760702788829803,0.10852183327078818, +C4,0.1/sync,accuracy,0.6071428571428571,0.6066713800577197,0.5690352278178915,0.6454503927265497,1000,paired source-video group resample,,,,,C0,0.02060439560439553,0.020787037037036993,-0.014813511970308765,0.057231579074092986, +C4,0.1/sync,macro_f1,0.5513144396980693,0.5503920045634241,0.5138458953397241,0.5880616322912752,1000,paired source-video group resample,,,,,C0,0.0009863766033160193,0.0007218868308094817,-0.03786001203469091,0.03917428440807385, +C4,0.1/sync,mae,0.6901516914367676,0.6902734041213989,0.6412878006696701,0.7424538195133209,1000,paired source-video group resample,-0.0011762380599975586,-0.0008752346038818359,-0.014678946137428284,0.009699831902980804,C0,-0.044891178607940674,-0.044360607862472534,-0.08199951648712159,-0.007397373020648963, +C4,0.1/sync,rmse,0.9423340779881683,0.941943842188712,0.8621660494108627,1.0201562337171128,1000,paired source-video group resample,,,,,C0,-0.002849186367118395,-0.0036340563472216925,-0.06319431835211742,0.05476836094047629, +C4,0.1/sync,pearson,0.5765157341957092,0.5760420560836792,0.5078922808170319,0.6428698152303696,1000,paired source-video group resample,,,,,C0,0.06311589479446411,0.06376083195209503,0.010083787888288499,0.11520167887210846, +C4,0.1/partial,accuracy,0.6181318681318682,0.6180146562963629,0.5805998536724643,0.6556313146696139,1000,paired source-video group resample,,,,,C0,0.02472527472527475,0.02535216296798848,-0.012864027122936189,0.05931337432059156, +C4,0.1/partial,macro_f1,0.5629823795879468,0.5623275377862742,0.5261242978696696,0.5983819535940645,1000,paired source-video group resample,,,,,C0,0.005349441584641568,0.005333306281493533,-0.035298347841388626,0.046625944114608985, +C4,0.1/partial,mae,0.6881271600723267,0.6884903013706207,0.6399402558803559,0.7399926245212555,1000,paired source-video group resample,-0.0032007694244384766,-0.0029689669609069824,-0.012865172326564788,0.005927075445652008,C0,-0.047090232372283936,-0.04728573560714722,-0.08604556322097778,-0.00665586292743683, +C4,0.1/partial,rmse,0.9477462964781758,0.9458718582879555,0.8686383092341153,1.025551810418897,1000,paired source-video group resample,,,,,C0,0.010302851070963737,0.008956023755472997,-0.05146929821512375,0.07163642390599549, +C4,0.1/partial,pearson,0.5724332332611084,0.5724915266036987,0.5033639892935753,0.6368671238422394,1000,paired source-video group resample,,,,,C0,0.05185967683792114,0.053104206919670105,-0.005541713535785675,0.10735398456454276, +C4,0.1/async,accuracy,0.6085164835164835,0.6088974261281856,0.5710378632637854,0.6494875801607274,1000,paired source-video group resample,,,,,C0,0.016483516483516425,0.016713221601489747,-0.020435967302452233,0.05402277796288618, +C4,0.1/async,macro_f1,0.5493351686926862,0.548564279548502,0.512550367229737,0.587387224232982,1000,paired source-video group resample,,,,,C0,-0.009471853186720947,-0.010087412930481321,-0.047685363915886174,0.03262150017062821, +C4,0.1/async,mae,0.6898413300514221,0.6901612281799316,0.6413616165518761,0.7408695563673973,1000,paired source-video group resample,-0.0014865994453430176,-0.0010546445846557617,-0.015491193532943726,0.00923229604959488,C0,-0.049052298069000244,-0.04909512400627136,-0.08654326796531678,-0.012810157239437106, +C4,0.1/async,rmse,0.9422415988251039,0.9417481335768823,0.8620613856571694,1.0206530400188862,1000,paired source-video group resample,,,,,C0,-0.001493042472420436,-0.0024471921752172165,-0.06139978160408527,0.05658621188493834, +C4,0.1/async,pearson,0.5761445164680481,0.5758955180644989,0.5087565407156944,0.6426015511155129,1000,paired source-video group resample,,,,,C0,0.062128543853759766,0.062623530626297,0.008377596735954285,0.11452083438634872, +C4,0.3/single,accuracy,0.6057692307692307,0.6055000227438136,0.5685098273042861,0.6438408340606383,1000,paired source-video group resample,,,,,C0,0.0,-0.0006281407035175768,-0.03667919274036123,0.03407409783601409, +C4,0.3/single,macro_f1,0.5448574982784282,0.5434063853214764,0.5072676055461015,0.5828787324528375,1000,paired source-video group resample,,,,,C0,-0.024441751130020006,-0.025349254910040753,-0.06374547001857724,0.012760477811166921, +C4,0.3/single,mae,0.7051863074302673,0.7051578760147095,0.6545857682824134,0.7599174916744232,1000,paired source-video group resample,0.013858377933502197,0.013867497444152832,0.003198225796222687,0.025151631236076347,C0,-0.025944828987121582,-0.02635970711708069,-0.06858597844839096,0.013548624515533443, +C4,0.3/single,rmse,0.9625155199954686,0.9610343030932527,0.8808095454918975,1.0414484684104082,1000,paired source-video group resample,,,,,C0,0.022747945261923697,0.021420123120671375,-0.04099919851096453,0.08543256397175622, +C4,0.3/single,pearson,0.558603048324585,0.5578450560569763,0.48742182925343513,0.6259456872940063,1000,paired source-video group resample,,,,,C0,0.03718745708465576,0.03883250057697296,-0.019943040609359742,0.09313765391707418, +C4,0.3/sync,accuracy,0.5961538461538461,0.5954641892760705,0.5579998648308235,0.6350433625233713,1000,paired source-video group resample,,,,,C0,0.016483516483516425,0.016371077762619368,-0.01783448967792412,0.050001646903820855, +C4,0.3/sync,macro_f1,0.527534842106031,0.5263896363056975,0.4920509375651904,0.5622926930032175,1000,paired source-video group resample,,,,,C0,-0.012566147333456845,-0.012654979334972338,-0.047438935921343954,0.02509261418098108, +C4,0.3/sync,mae,0.7100124955177307,0.7097547948360443,0.6567122966051102,0.765663120150566,1000,paired source-video group resample,0.018684566020965576,0.018873989582061768,0.0011272057890892033,0.03410067409276962,C0,-0.04289120435714722,-0.04299095273017883,-0.08465884625911713,-0.003834520280361183, +C4,0.3/sync,rmse,0.9593676327599577,0.9573890773230795,0.876547741082392,1.0380894705832764,1000,paired source-video group resample,,,,,C0,-0.0029250830043195952,-0.0037119622346292735,-0.0649448298141316,0.05345331264472348, +C4,0.3/sync,pearson,0.562080442905426,0.562017172574997,0.4953893795609474,0.6260113999247551,1000,paired source-video group resample,,,,,C0,0.06384551525115967,0.06492425501346588,0.011636020988225937,0.11839371770620344, +C4,0.3/partial,accuracy,0.5989010989010989,0.5985379570552694,0.5623092429694789,0.6379367059891108,1000,paired source-video group resample,,,,,C0,0.004120879120879106,0.004135081219720671,-0.030619410685622597,0.03941705149212963, +C4,0.3/partial,macro_f1,0.5334785261026341,0.5316765750050771,0.49840205847018326,0.5703266529725478,1000,paired source-video group resample,,,,,C0,-0.029757121540835207,-0.03016523924577924,-0.06810793242220849,0.006450752538816257, +C4,0.3/partial,mae,0.7163351774215698,0.7161301374435425,0.6660571873188019,0.7694678321480751,1000,paired source-video group resample,0.025007247924804688,0.025281667709350586,0.00701940655708313,0.04268206655979156,C0,-0.030216515064239502,-0.030116349458694458,-0.07353100776672364,0.014109711349010462, +C4,0.3/partial,rmse,0.9732804038460091,0.9721209109901332,0.8908419803988767,1.058651244185419,1000,paired source-video group resample,,,,,C0,0.020482210582033034,0.018969474080539173,-0.04596763985085723,0.08251591389382672, +C4,0.3/partial,pearson,0.5495026111602783,0.5497955083847046,0.4791161023080349,0.6198936849832535,1000,paired source-video group resample,,,,,C0,0.04078882932662964,0.042190179228782654,-0.019574160873889922,0.09947131872177122, +C4,0.3/async,accuracy,0.6057692307692307,0.604666283606012,0.5670151921358356,0.6465763724379442,1000,paired source-video group resample,,,,,C0,0.026098901098901006,0.025315476190476194,-0.01016607704402514,0.06299516294684764, +C4,0.3/async,macro_f1,0.5389170418111896,0.537816821533526,0.5038734934559748,0.5760468103224203,1000,paired source-video group resample,,,,,C0,-0.007233428737485337,-0.006870143115462968,-0.04438247834969657,0.03356401399055389, +C4,0.3/async,mae,0.7097203731536865,0.710175096988678,0.6591630727052689,0.7622607380151748,1000,paired source-video group resample,0.018392443656921387,0.01915884017944336,-0.0024695947766304005,0.03842334449291229,C0,-0.058863043785095215,-0.059314578771591187,-0.10123717039823532,-0.01653449833393099, +C4,0.3/async,rmse,0.9613115466570531,0.9607466528499322,0.8782183109489007,1.045427765343819,1000,paired source-video group resample,,,,,C0,-0.021793247898876933,-0.02216715043975781,-0.09010139688863436,0.04297467165574621, +C4,0.3/async,pearson,0.5613389015197754,0.560345858335495,0.49110048189759253,0.6277281507849694,1000,paired source-video group resample,,,,,C0,0.07449296116828918,0.07536101341247559,0.01701890826225281,0.13440260738134382, +C4,0.5/single,accuracy,0.5961538461538461,0.5953938473698441,0.5568343236221143,0.6379719731831164,1000,paired source-video group resample,,,,,C0,0.009615384615384581,0.010370393131178324,-0.02834372287540445,0.04661181765876344, +C4,0.5/single,macro_f1,0.5373018728963802,0.5358652024386374,0.4991409677463083,0.5766356551254881,1000,paired source-video group resample,,,,,C0,-0.017715409265502746,-0.017253966985501246,-0.059191777027791055,0.02483189747484076, +C4,0.5/single,mae,0.7077146172523499,0.7079867720603943,0.6557512357831001,0.7615304887294769,1000,paired source-video group resample,0.016386687755584717,0.016140490770339966,0.0034023359417915348,0.03149628341197967,C0,-0.04131370782852173,-0.041683465242385864,-0.07781103253364563,-0.003155384957790381, +C4,0.5/single,rmse,0.9631128576999805,0.9619511429603891,0.8778042455580641,1.0478629002970603,1000,paired source-video group resample,,,,,C0,0.0034620201874469014,0.002636609846197735,-0.06201172129406878,0.06284946657139649, +C4,0.5/single,pearson,0.5596314668655396,0.5592842996120453,0.4886684961616993,0.6297772407531739,1000,paired source-video group resample,,,,,C0,0.05139821767807007,0.05298702418804169,-0.003566540032625198,0.10844829380512237, +C4,0.5/sync,accuracy,0.6098901098901099,0.6100106996529138,0.5731948520340397,0.6504000884504677,1000,paired source-video group resample,,,,,C0,0.016483516483516536,0.016129032258064502,-0.02052194983539029,0.0539999961969088, +C4,0.5/sync,macro_f1,0.5318651950115886,0.5307710628502627,0.4975758956957047,0.565950770820909,1000,paired source-video group resample,,,,,C0,-0.031638344384594896,-0.0322700732591249,-0.07493880072112237,0.010504351181947513, +C4,0.5/sync,mae,0.7272348999977112,0.7266396284103394,0.6709515243768692,0.7829209312796592,1000,paired source-video group resample,0.035906970500946045,0.0356716513633728,0.00974622666835785,0.060729981958866114,C0,-0.06005936861038208,-0.06033432483673096,-0.10698389559984207,-0.017837345600128195, +C4,0.5/sync,rmse,0.982766093021158,0.9816731448277316,0.8961837343660085,1.068603459775728,1000,paired source-video group resample,,,,,C0,-0.01960544590503044,-0.021192708921955627,-0.08734253561924471,0.04289566683587832, +C4,0.5/sync,pearson,0.5451382994651794,0.5446782112121582,0.4740124709904194,0.6127483621239662,1000,paired source-video group resample,,,,,C0,0.06548002362251282,0.06704527139663696,0.008278129249811172,0.12654397338628767, +C4,0.5/partial,accuracy,0.592032967032967,0.5921916912660503,0.5529492145080721,0.6302946849485745,1000,paired source-video group resample,,,,,C0,0.006868131868131844,0.008026759444193898,-0.03276645351528341,0.0448855263417814, +C4,0.5/partial,macro_f1,0.5106145826134237,0.5086259570196757,0.4756069560199353,0.5468796129571197,1000,paired source-video group resample,,,,,C0,-0.04098164812600735,-0.03981759610658053,-0.08600231481989674,0.0006433186163625284, +C4,0.5/partial,mae,0.7387668490409851,0.7381762862205505,0.6834636434912682,0.798521663248539,1000,paired source-video group resample,0.04743891954421997,0.047747284173965454,0.022169357538223265,0.07796637713909149,C0,-0.04669225215911865,-0.04758632183074951,-0.0922721117734909,0.0010098904371261485, +C4,0.5/partial,rmse,0.998935042989206,0.998972721544624,0.9102056154231477,1.083495402899112,1000,paired source-video group resample,,,,,C0,-0.0006757523472428195,-0.002415612274367873,-0.06714489772524473,0.06958735814840475, +C4,0.5/partial,pearson,0.5270354747772217,0.5262722671031952,0.45179113298654555,0.5970614925026894,1000,paired source-video group resample,,,,,C0,0.04562985897064209,0.046424418687820435,-0.01884058341383934,0.10689517259597775, +C4,0.5/async,accuracy,0.5934065934065934,0.5929799552997905,0.5549338407605693,0.6346066068661402,1000,paired source-video group resample,,,,,C0,0.020604395604395642,0.020746887966805017,-0.014165835312823753,0.058057674294125575, +C4,0.5/async,macro_f1,0.5159114652231741,0.5149968893518537,0.48130148686092694,0.553329259294792,1000,paired source-video group resample,,,,,C0,-0.024736531211352664,-0.023608739299456727,-0.06469392164441584,0.01345418327466001, +C4,0.5/async,mae,0.7350773811340332,0.7348652780056,0.6805802330374717,0.7931857734918595,1000,paired source-video group resample,0.043749451637268066,0.04402998089790344,0.02400382459163666,0.06434917896986007,C0,-0.05818730592727661,-0.058444201946258545,-0.10385551899671555,-0.012578874826431278, +C4,0.5/async,rmse,0.9911767812772675,0.9905010969859602,0.9083222981647325,1.0744996650245386,1000,paired source-video group resample,,,,,C0,-0.012150952366903334,-0.013980812013497101,-0.07828323776525024,0.05207655506466993, +C4,0.5/async,pearson,0.5368825793266296,0.5359650552272797,0.4675330832600594,0.6042950376868248,1000,paired source-video group resample,,,,,C0,0.06238788366317749,0.06390899419784546,0.0023906759917736056,0.11897796615958213, +C4,0.7/single,accuracy,0.5947802197802198,0.5941928620177446,0.5578766239471112,0.6339881585164185,1000,paired source-video group resample,,,,,C0,0.009615384615384581,0.010056572169021172,-0.024596571894300385,0.04545926065635616, +C4,0.7/single,macro_f1,0.5243936478396592,0.5230813859758061,0.49017136958687174,0.5559591546611296,1000,paired source-video group resample,,,,,C0,-0.026917324662837805,-0.0265634520669058,-0.06338798897073618,0.012831834919613237, +C4,0.7/single,mae,0.7299391627311707,0.7301859855651855,0.6758868619799614,0.7888668611645698,1000,paired source-video group resample,0.03861123323440552,0.03903859853744507,0.019484812021255495,0.05948457419872283,C0,-0.058009445667266846,-0.05796882510185242,-0.1024298369884491,-0.014563710987567913, +C4,0.7/single,rmse,0.9767702415757151,0.97520919085998,0.8960494950936794,1.061525666256085,1000,paired source-video group resample,,,,,C0,-0.03355375384821335,-0.033216310300961616,-0.09949503560514714,0.033869188859658436, +C4,0.7/single,pearson,0.5543427467346191,0.5537466406822205,0.4839296333491802,0.6177191138267517,1000,paired source-video group resample,,,,,C0,0.08170253038406372,0.08194532990455627,0.022718624025583268,0.1414358288049698, +C4,0.7/sync,accuracy,0.592032967032967,0.5923549107142857,0.5510032872209286,0.6342229478056961,1000,paired source-video group resample,,,,,C0,0.009615384615384581,0.010638297872340385,-0.031776556776556775,0.047198114597142474, +C4,0.7/sync,macro_f1,0.4860369334299082,0.4853025144126424,0.4535237137846311,0.5187739455882587,1000,paired source-video group resample,,,,,C0,-0.06290256667045585,-0.06273878115684345,-0.10565904277872305,-0.02349938065464156, +C4,0.7/sync,mae,0.7700906991958618,0.7705946564674377,0.7127695575356483,0.8270917475223541,1000,paired source-video group resample,0.07876276969909668,0.07860547304153442,0.04983165115118027,0.11168132275342942,C0,-0.013280928134918213,-0.013093650341033936,-0.06614947766065597,0.036808526515960685, +C4,0.7/sync,rmse,1.0298638130633275,1.0298068033731513,0.944592187569761,1.1163449543032284,1000,paired source-video group resample,,,,,C0,0.009708371506029989,0.008667731954977442,-0.05374462433144441,0.06795904936353556, +C4,0.7/sync,pearson,0.5142890214920044,0.5120687484741211,0.44440867006778717,0.5848484769463539,1000,paired source-video group resample,,,,,C0,0.03584396839141846,0.03629693388938904,-0.01941767856478691,0.09175319969654083, +C4,0.7/partial,accuracy,0.5879120879120879,0.5882762006054161,0.5477313575175147,0.6298351368398323,1000,paired source-video group resample,,,,,C0,-0.005494505494505475,-0.005018891687657401,-0.047696990424076616,0.03411089456246337, +C4,0.7/partial,macro_f1,0.4744877046241633,0.47436419906744365,0.4390780907211148,0.5104296292465248,1000,paired source-video group resample,,,,,C0,-0.08952573259244717,-0.08864224066415585,-0.13128630107456193,-0.04648130859647228, +C4,0.7/partial,mae,0.791839599609375,0.7916676700115204,0.7306735903024674,0.8571296140551568,1000,paired source-video group resample,0.10051167011260986,0.10014930367469788,0.07153877466917039,0.1342094615101814,C0,-0.0057517290115356445,-0.005919456481933594,-0.05433725565671921,0.043228049576282485, +C4,0.7/partial,rmse,1.0548551073057653,1.0532422087774136,0.9625267629704782,1.148531924855323,1000,paired source-video group resample,,,,,C0,0.03739841553884937,0.036734520596235276,-0.03177871740902107,0.10082551069815536, +C4,0.7/partial,pearson,0.4877459406852722,0.4871433228254318,0.40698941946029665,0.5651431873440742,1000,paired source-video group resample,,,,,C0,-0.004730880260467529,-0.003615275025367737,-0.0692194513976574,0.059218199551105494, +C4,0.7/async,accuracy,0.603021978021978,0.6034611113652717,0.5626681914777988,0.6425798275217147,1000,paired source-video group resample,,,,,C0,0.024725274725274637,0.025192454604219316,-0.020278847525317327,0.06342820798219118, +C4,0.7/async,macro_f1,0.49410910064137487,0.4925216284693525,0.45878784105234727,0.5274156188228861,1000,paired source-video group resample,,,,,C0,-0.05968896236652893,-0.05985054875946552,-0.10669304467196122,-0.016806767034315048, +C4,0.7/async,mae,0.7782714366912842,0.7780938744544983,0.7224156230688095,0.840789595246315,1000,paired source-video group resample,0.08694350719451904,0.08630427718162537,0.05569553673267365,0.12255030423402787,C0,-0.038188159465789795,-0.039981722831726074,-0.08738577216863633,0.017326842248439778, +C4,0.7/async,rmse,1.040794363358736,1.0376395036174348,0.9508677316643922,1.1321083296709222,1000,paired source-video group resample,,,,,C0,-5.154156181852443e-07,-0.00214362582590355,-0.07331915494458478,0.08180584158653535, +C4,0.7/async,pearson,0.501583456993103,0.5002941489219666,0.42795726507902143,0.5741652861237526,1000,paired source-video group resample,,,,,C0,0.022387295961380005,0.024705618619918823,-0.05703204125165939,0.09296304509043693, +C4,0.3/modality_T,accuracy,0.592032967032967,0.5921678168474094,0.5538870815405604,0.6312388383797386,1000,paired source-video group resample,,,,,C0,0.005494505494505475,0.005319148936170137,-0.03109519455450574,0.042585542748803676, +C4,0.3/modality_T,macro_f1,0.522749124601129,0.5213577927657711,0.48931842013682186,0.5575393525641552,1000,paired source-video group resample,,,,,C0,-0.024014188842577777,-0.0245472296648018,-0.06448612553694094,0.01686784644361309, +C4,0.3/modality_T,mae,0.7255198955535889,0.726082444190979,0.6727274119853973,0.7782109513878822,1000,paired source-video group resample,0.03419196605682373,0.03419479727745056,0.015670499205589293,0.05357528328895569,C0,-0.024603843688964844,-0.02465108036994934,-0.0691661849617958,0.018069255352020246, +C4,0.3/modality_T,rmse,0.987385521059622,0.9870507155604932,0.9027872098290397,1.0726839302284346,1000,paired source-video group resample,,,,,C0,0.024716189405501354,0.024029147551855368,-0.040587795766226696,0.08853425359491933, +C4,0.3/modality_T,pearson,0.53729248046875,0.5381157696247101,0.4666877157986164,0.606026554107666,1000,paired source-video group resample,,,,,C0,0.03553009033203125,0.036161646246910095,-0.02682024836540222,0.09702915176749227, +C4,0.3/modality_A,accuracy,0.6085164835164835,0.607803751399776,0.570860288770034,0.6474779001542802,1000,paired source-video group resample,,,,,C0,0.0219780219780219,0.02198603869215815,-0.01491188299591637,0.05679173071935703, +C4,0.3/modality_A,macro_f1,0.5571978496539316,0.5560514700942185,0.518505774628905,0.594901529579126,1000,paired source-video group resample,,,,,C0,0.005716080994034312,0.005995805680383215,-0.03316719287351106,0.04496204494505636, +C4,0.3/modality_A,mae,0.6869610548019409,0.6870865523815155,0.6390947073698043,0.7390632286667824,1000,paired source-video group resample,-0.004366874694824219,-0.004212498664855957,-0.012212304770946503,0.0029278814792633055,C0,-0.043205976486206055,-0.04340869188308716,-0.08092417865991593,-0.00451837778091431, +C4,0.3/modality_A,rmse,0.946639178278813,0.9450702177488932,0.8669761157573114,1.026310880126881,1000,paired source-video group resample,,,,,C0,0.012326817962733161,0.010482777190523984,-0.04962326667001788,0.0712867480137003, +C4,0.3/modality_A,pearson,0.572704017162323,0.572740763425827,0.5032334282994271,0.6386909514665604,1000,paired source-video group resample,,,,,C0,0.04996699094772339,0.05104789137840271,-0.005345937609672545,0.10277550667524336, +C4,0.3/modality_V,accuracy,0.6085164835164835,0.6077904015317088,0.5695692643672406,0.6463429060944766,1000,paired source-video group resample,,,,,C0,0.02060439560439553,0.020832343088365624,-0.013798415918091294,0.055502099637335295, +C4,0.3/modality_V,macro_f1,0.5547564796327966,0.5540826767877125,0.5171856578359909,0.5920589837372116,1000,paired source-video group resample,,,,,C0,0.0036631336499478584,0.0035773155416030655,-0.032202442096656674,0.04426398331621699, +C4,0.3/modality_V,mae,0.6884675025939941,0.6886386573314667,0.6392177790403366,0.741069421172142,1000,paired source-video group resample,-0.002860426902770996,-0.0021233558654785156,-0.013918320834636688,0.0043301224708557125,C0,-0.04486560821533203,-0.04487955570220947,-0.0822703406214714,-0.009010306000709538, +C4,0.3/modality_V,rmse,0.9424747402438817,0.9420147556204062,0.8626952347111909,1.0214423381970137,1000,paired source-video group resample,,,,,C0,0.004682007931255283,0.004298437490222795,-0.05625651976819715,0.06252613855663904, +C4,0.3/modality_V,pearson,0.5753766894340515,0.5754360854625702,0.5074418827891349,0.6406727492809295,1000,paired source-video group resample,,,,,C0,0.05593085289001465,0.05658090114593506,0.0024580493569374092,0.10865152478218078, +C4,0.3/modality_TA,accuracy,0.5934065934065934,0.5925197274031564,0.5558508911301464,0.6325420986533931,1000,paired source-video group resample,,,,,C0,0.006868131868131844,0.007189076325146759,-0.02747632202052093,0.04161937928400568, +C4,0.3/modality_TA,macro_f1,0.5217732549219669,0.5200243915820306,0.48688936311216924,0.5555742069770213,1000,paired source-video group resample,,,,,C0,-0.032425032238325935,-0.03198795673915045,-0.06939332205223064,0.005463894874371835, +C4,0.3/modality_TA,mae,0.7196934223175049,0.719999760389328,0.6651951521635056,0.7708804443478584,1000,paired source-video group resample,0.028365492820739746,0.028059661388397217,0.012137508392333985,0.04642264693975448,C0,-0.055892109870910645,-0.05661958456039429,-0.09884129762649536,-0.014370337128639226, +C4,0.3/modality_TA,rmse,0.9731426325127299,0.9712354563021468,0.8893167294710458,1.0549347763216272,1000,paired source-video group resample,,,,,C0,0.00252154615929312,-0.00026523639084269357,-0.062330223662042265,0.06282653467576088, +C4,0.3/modality_TA,pearson,0.551323413848877,0.5516726970672607,0.48162355497479437,0.6165887981653213,1000,paired source-video group resample,,,,,C0,0.05288344621658325,0.05544079840183258,-0.005046266317367553,0.11075860038399696, +C4,0.3/modality_TV,accuracy,0.6043956043956044,0.6044179523141655,0.5668050215171501,0.644044908211653,1000,paired source-video group resample,,,,,C0,0.0219780219780219,0.02237302171512695,-0.01757068687085114,0.0606478781585816, +C4,0.3/modality_TV,macro_f1,0.5342713045825597,0.5334286851210699,0.4979322655376324,0.569705603809339,1000,paired source-video group resample,,,,,C0,-0.010573283406298595,-0.010949604829592174,-0.053668780077199885,0.03335617231096957, +C4,0.3/modality_TV,mae,0.7099452614784241,0.7102292776107788,0.6585451856255531,0.7577145859599114,1000,paired source-video group resample,0.018617331981658936,0.018866121768951416,-0.0015438571572303772,0.03749026358127594,C0,-0.05072849988937378,-0.050781846046447754,-0.098011913895607,-0.004950825870037081, +C4,0.3/modality_TV,rmse,0.9681623891724022,0.9660918314053938,0.8880856924845769,1.0456229117396894,1000,paired source-video group resample,,,,,C0,0.000595298366513286,-0.0003779107370773249,-0.06564600586224988,0.06768338989881269, +C4,0.3/modality_TV,pearson,0.5528072714805603,0.55255526304245,0.48411558419466016,0.6206704348325729,1000,paired source-video group resample,,,,,C0,0.05382046103477478,0.055779263377189636,-0.010581306368112562,0.11335462927818296, +C4,0.3/modality_AV,accuracy,0.6098901098901099,0.609375,0.572374732192292,0.6482218694723493,1000,paired source-video group resample,,,,,C0,0.015109890109890167,0.015427769985974726,-0.018415562200041043,0.05104512972998893, +C4,0.3/modality_AV,macro_f1,0.5558035356537437,0.5553070244802248,0.5181132716647965,0.5922710844080833,1000,paired source-video group resample,,,,,C0,-0.0038946705853684094,-0.0037488652008174084,-0.04033689042065755,0.03766532037109943, +C4,0.3/modality_AV,mae,0.684674084186554,0.6849975287914276,0.63516456335783,0.7369623571634293,1000,paired source-video group resample,-0.006653845310211182,-0.006061762571334839,-0.01951645016670227,0.002124328911304469,C0,-0.053306758403778076,-0.05282166600227356,-0.08995560705661773,-0.017665497958660126, +C4,0.3/modality_AV,rmse,0.9375569326279832,0.9371980135318196,0.8591739700041799,1.016238826016504,1000,paired source-video group resample,,,,,C0,-0.004478294873607291,-0.005064212628466014,-0.0650354568845367,0.05269023688336117, +C4,0.3/modality_AV,pearson,0.5798117518424988,0.579791933298111,0.512623405456543,0.6439945876598357,1000,paired source-video group resample,,,,,C0,0.06427782773971558,0.06484144926071167,0.010759884119033815,0.1156142547726631, +C4,0.3/modality_TAV,accuracy,0.5906593406593407,0.5904370785478954,0.5532750591861348,0.6306890129588213,1000,paired source-video group resample,,,,,C0,0.009615384615384581,0.009759499268632787,-0.02487675282832344,0.04825851013936811, +C4,0.3/modality_TAV,macro_f1,0.5200467648099073,0.5188025314037426,0.4836589631414981,0.5559277447123021,1000,paired source-video group resample,,,,,C0,-0.024431133794374893,-0.023971828903714798,-0.06512313164689822,0.020213540324671785, +C4,0.3/modality_TAV,mae,0.7165269255638123,0.7163264453411102,0.6648397490382194,0.7691221117973328,1000,paired source-video group resample,0.02519899606704712,0.02471071481704712,0.007141003012657166,0.04441724717617035,C0,-0.05440479516983032,-0.054458022117614746,-0.098731729388237,-0.01292672157287599, +C4,0.3/modality_TAV,rmse,0.9669502830170809,0.9649159635925275,0.8818194151100961,1.0504289997533065,1000,paired source-video group resample,,,,,C0,-0.013087478644288275,-0.014241191436675071,-0.07891173673730377,0.04568795321026464, +C4,0.3/modality_TAV,pearson,0.5551301836967468,0.5549207925796509,0.4855451762676239,0.6194512858986855,1000,paired source-video group resample,,,,,C0,0.06482067704200745,0.06558774411678314,0.007763060927391056,0.12302348837256431, +C4,0.3/location_start_T,accuracy,0.6071428571428571,0.6064386578572354,0.5690505753871697,0.6472337868654577,1000,paired source-video group resample,,,,,C0,0.015109890109890056,0.015406192685295084,-0.01978663186612531,0.05322626817276548, +C4,0.3/location_start_T,macro_f1,0.5432899743458909,0.5424020788361305,0.5064928179005569,0.5814472985845951,1000,paired source-video group resample,,,,,C0,-0.01790119922243194,-0.017172920119800428,-0.057643665741230074,0.02449213914083256, +C4,0.3/location_start_T,mae,0.7165481448173523,0.7161619067192078,0.666883584856987,0.7674664184451103,1000,paired source-video group resample,0.025220215320587158,0.02505439519882202,0.009901447594165802,0.04049147665500641,C0,-0.05271303653717041,-0.05308949947357178,-0.09907747954130172,-0.007425671815872195, +C4,0.3/location_start_T,rmse,0.9742067227695683,0.9730580882655884,0.8969667936746978,1.0478218422792822,1000,paired source-video group resample,,,,,C0,-0.0011072068424917703,-0.0007247650219828206,-0.06965640563246685,0.06265542316168632, +C4,0.3/location_start_T,pearson,0.5580077767372131,0.5574716329574585,0.48883336186409,0.6237359076738358,1000,paired source-video group resample,,,,,C0,0.07545831799507141,0.07648423314094543,0.014719603210687639,0.13768475428223606, +C4,0.3/location_middle_T,accuracy,0.5947802197802198,0.5947712418300654,0.5566380338821284,0.6342727639000806,1000,paired source-video group resample,,,,,C0,0.005494505494505475,0.005252973983465026,-0.029501841124759842,0.03897126495551693, +C4,0.3/location_middle_T,macro_f1,0.5246095893828269,0.5234141352221655,0.48840927931694844,0.5598494887497596,1000,paired source-video group resample,,,,,C0,-0.026191914303489994,-0.027049365457229246,-0.06140062629397615,0.013354518842775378, +C4,0.3/location_middle_T,mae,0.7175800800323486,0.7178681790828705,0.6661497488617897,0.7720985606312751,1000,paired source-video group resample,0.026252150535583496,0.025995910167694092,0.01080935150384903,0.04232200682163238,C0,-0.03118729591369629,-0.031260013580322266,-0.07295162677764892,0.01237518936395645, +C4,0.3/location_middle_T,rmse,0.9734778859683726,0.9723842654001226,0.8894363365573814,1.0532945064958004,1000,paired source-video group resample,,,,,C0,0.012020611217557375,0.011869400277362108,-0.051635185987813303,0.07473423803653091, +C4,0.3/location_middle_T,pearson,0.5450464487075806,0.5445218980312347,0.47108335644006727,0.6137464329600334,1000,paired source-video group resample,,,,,C0,0.03809213638305664,0.03908458352088928,-0.023121993243694305,0.0970884263515472, +C4,0.3/location_end_T,accuracy,0.5934065934065934,0.5933768130460227,0.555551659654044,0.6328726551226551,1000,paired source-video group resample,,,,,C0,0.019230769230769273,0.01884057971014491,-0.016676742532005632,0.056225396318757254, +C4,0.3/location_end_T,macro_f1,0.5187918657579326,0.5174943513829892,0.48254081084750783,0.556991835668364,1000,paired source-video group resample,,,,,C0,-0.019176308171960477,-0.01926655083644463,-0.060109657300782667,0.021709213687314703, +C4,0.3/location_end_T,mae,0.7217822074890137,0.7210619747638702,0.6710312590003014,0.7739161983132362,1000,paired source-video group resample,0.030454277992248535,0.030349135398864746,0.0066149175167083745,0.05506623536348343,C0,-0.04737067222595215,-0.04758530855178833,-0.09292017221450806,-0.0021630167961120637, +C4,0.3/location_end_T,rmse,0.9617513606153819,0.961583127716009,0.8824874281183072,1.0417705219349982,1000,paired source-video group resample,,,,,C0,-0.015781208112658818,-0.0184801598160233,-0.08215957510084469,0.046653905627998274, +C4,0.3/location_end_T,pearson,0.5594192743301392,0.5594765245914459,0.48919527903199195,0.6237318947911262,1000,paired source-video group resample,,,,,C0,0.05273467302322388,0.05381350219249725,-0.0037069447338581077,0.11315832585096358, +C4,0.3/span_long_T,accuracy,0.5947802197802198,0.5947445143470922,0.5566090207992521,0.6330493406644074,1000,paired source-video group resample,,,,,C0,0.016483516483516425,0.01705121514835245,-0.018234745076348723,0.05097386642841189, +C4,0.3/span_long_T,macro_f1,0.525344876852737,0.5243360503607457,0.48839241240280956,0.5608617122031512,1000,paired source-video group resample,,,,,C0,-0.014759598217264136,-0.014609317995339766,-0.055138185679417945,0.025379734897066374, +C4,0.3/span_long_T,mae,0.7229676246643066,0.721604198217392,0.673911003768444,0.7753313660621644,1000,paired source-video group resample,0.031639695167541504,0.03153446316719055,0.012681430578231812,0.0502533197402954,C0,-0.026153922080993652,-0.02736353874206543,-0.07007375359535217,0.01716881543397903, +C4,0.3/span_long_T,rmse,0.9721592931968658,0.969968674924813,0.8936842749558349,1.0520134399362258,1000,paired source-video group resample,,,,,C0,0.008261372171995629,0.005790115790221151,-0.059109886422975405,0.0721356089843293, +C4,0.3/span_long_T,pearson,0.5539432764053345,0.5547208786010742,0.48201668038964274,0.6183512017130852,1000,paired source-video group resample,,,,,C0,0.05396416783332825,0.05521586537361145,-0.004306140542030333,0.11356888860464096, +C4,0.3/span_multi_short_T,accuracy,0.6071428571428571,0.6069701536177774,0.5676739390190488,0.6470781479477468,1000,paired source-video group resample,,,,,C0,0.019230769230769162,0.019382325135923972,-0.01637304456906735,0.05646775179989001, +C4,0.3/span_multi_short_T,macro_f1,0.5386058399227313,0.5382807084776833,0.4999728426584564,0.5797477906879706,1000,paired source-video group resample,,,,,C0,-0.012938615363887074,-0.01325866155023947,-0.053035910160403744,0.031061852277299653, +C4,0.3/span_multi_short_T,mae,0.7084731459617615,0.7083915174007416,0.6569698289036751,0.759762966632843,1000,paired source-video group resample,0.017145216464996338,0.017474442720413208,-0.005486229062080383,0.03804870396852493,C0,-0.042982399463653564,-0.04332619905471802,-0.08371772468090058,-0.0002537950873374959, +C4,0.3/span_multi_short_T,rmse,0.95430129585382,0.9532213159067546,0.8725001868380402,1.0362738720620837,1000,paired source-video group resample,,,,,C0,-0.006396809826561545,-0.007732859336633369,-0.06639458115283517,0.05849115041591755, +C4,0.3/span_multi_short_T,pearson,0.5685112476348877,0.5683026611804962,0.4983051620423794,0.6364045754075051,1000,paired source-video group resample,,,,,C0,0.06690269708633423,0.06824354827404022,0.0053644277155399335,0.12049570083618164, +C4,0.3/location_start_A,accuracy,0.6057692307692307,0.6054095779797877,0.5687075331311771,0.64516364492583,1000,paired source-video group resample,,,,,C0,0.0219780219780219,0.021972119968619863,-0.012328311459963692,0.05644665892775074, +C4,0.3/location_start_A,macro_f1,0.5576709586208229,0.5564175458348725,0.5213517546092917,0.5941705832763656,1000,paired source-video group resample,,,,,C0,0.0008907982235957235,0.0009349632650935691,-0.036593713846383685,0.03807035533826343, +C4,0.3/location_start_A,mae,0.6834709644317627,0.6830746531486511,0.6344089850783348,0.7371530205011367,1000,paired source-video group resample,-0.007856965065002441,-0.00777241587638855,-0.017358110845088957,0.0013277947902679429,C0,-0.05152738094329834,-0.05219712853431702,-0.08956926316022873,-0.014786097407341013, +C4,0.3/location_start_A,rmse,0.9424449840850333,0.9413424583972383,0.8618324807119577,1.0227002833393053,1000,paired source-video group resample,,,,,C0,0.001647636390365692,0.00017232148336543407,-0.05805501108106949,0.05839062524596434, +C4,0.3/location_start_A,pearson,0.5742443799972534,0.5737507045269012,0.5039369896054268,0.6392042472958565,1000,paired source-video group resample,,,,,C0,0.05650073289871216,0.058200448751449585,0.0017028152942657473,0.11132649704813957, +C4,0.3/location_middle_A,accuracy,0.6098901098901099,0.6095561573929003,0.5725112839819456,0.6477211696466261,1000,paired source-video group resample,,,,,C0,0.02335164835164838,0.02385966087271696,-0.011532172895115246,0.06156001113436874, +C4,0.3/location_middle_A,macro_f1,0.5586004492318496,0.5573234809169143,0.5206192251640113,0.5956986318362619,1000,paired source-video group resample,,,,,C0,0.004837625903808873,0.004753342533816707,-0.03411851099419354,0.046562885400513745, +C4,0.3/location_middle_A,mae,0.6852142810821533,0.6847926676273346,0.6366436615586281,0.7370648980140686,1000,paired source-video group resample,-0.006113648414611816,-0.006130993366241455,-0.014491473138332366,0.001636385917663573,C0,-0.0488089919090271,-0.049262553453445435,-0.08745971769094467,-0.011202506721019745, +C4,0.3/location_middle_A,rmse,0.945550998835399,0.9445890695697007,0.8639899351985583,1.0250823481569307,1000,paired source-video group resample,,,,,C0,0.008772063181760936,0.006970476886680399,-0.05234024474611442,0.06925112491254126, +C4,0.3/location_middle_A,pearson,0.5735681056976318,0.5732335448265076,0.5036539509892464,0.6384761288762093,1000,paired source-video group resample,,,,,C0,0.05320686101913452,0.054539501667022705,-0.0010633349418640128,0.10735659077763557, +C4,0.3/location_end_A,accuracy,0.6057692307692307,0.6050133845811829,0.5670963301977606,0.6443396193062096,1000,paired source-video group resample,,,,,C0,0.016483516483516425,0.016678256838201178,-0.016376488095238038,0.051837364780166234, +C4,0.3/location_end_A,macro_f1,0.5519323418637248,0.5511339103504409,0.5154410712783923,0.5892140521416083,1000,paired source-video group resample,,,,,C0,-0.0014668194013339741,-0.0016191942359935485,-0.03759245339768917,0.04045235858300604, +C4,0.3/location_end_A,mae,0.692928671836853,0.6929461658000946,0.6448288202285767,0.746066990494728,1000,paired source-video group resample,0.0016007423400878906,0.0014072656631469727,-0.002674303948879242,0.006750088930130003,C0,-0.04181826114654541,-0.041914016008377075,-0.08008241802453994,-0.004151050746440903, +C4,0.3/location_end_A,rmse,0.9508383790956884,0.9489232103436889,0.8717202860709194,1.030295663023015,1000,paired source-video group resample,,,,,C0,0.013168958267295916,0.011676295332414321,-0.05108000619218579,0.0718849434366137, +C4,0.3/location_end_A,pearson,0.5685250163078308,0.5677963197231293,0.4974157400429249,0.6336277797818184,1000,paired source-video group resample,,,,,C0,0.049573659896850586,0.05081374943256378,-0.006416261196136475,0.1055570840835571, +C4,0.3/span_long_A,accuracy,0.6071428571428571,0.6069933489827856,0.5700083949813276,0.6452863984578158,1000,paired source-video group resample,,,,,C0,0.019230769230769162,0.01931955211024977,-0.017226606089590302,0.05532663925261513, +C4,0.3/span_long_A,macro_f1,0.5574475849521998,0.5558860202269575,0.5201275414313935,0.5927646394890388,1000,paired source-video group resample,,,,,C0,0.003110304299129729,0.0027465209837814197,-0.034677238835152446,0.04499648281047917, +C4,0.3/span_long_A,mae,0.6861920952796936,0.6858861744403839,0.6372141793370247,0.7398158147931099,1000,paired source-video group resample,-0.005135834217071533,-0.0050514936447143555,-0.013966019451618194,0.00337103009223938,C0,-0.05046677589416504,-0.050558000802993774,-0.08894800543785095,-0.012363007664680487, +C4,0.3/span_long_A,rmse,0.945262340129137,0.943952447786488,0.8644217151814666,1.0259563615665446,1000,paired source-video group resample,,,,,C0,0.007309263575774438,0.005621866168979084,-0.05231948771320445,0.06626111991727016, +C4,0.3/span_long_A,pearson,0.5736428499221802,0.5735782086849213,0.5045252442359924,0.6393895477056504,1000,paired source-video group resample,,,,,C0,0.05611294507980347,0.05735453963279724,0.0015592619776725772,0.11113795712590215, +C4,0.3/span_multi_short_A,accuracy,0.6071428571428571,0.6065927769875139,0.5700210701020496,0.645210800633084,1000,paired source-video group resample,,,,,C0,0.012362637362637319,0.013200642800441365,-0.021560376289957224,0.048782142502564824, +C4,0.3/span_multi_short_A,macro_f1,0.5574086862186544,0.5564094693356084,0.5201902215096919,0.5933299134237233,1000,paired source-video group resample,,,,,C0,-0.0028691493653539846,-0.003100104489147104,-0.04088367093145933,0.03704894361350652, +C4,0.3/span_multi_short_A,mae,0.6852989196777344,0.6849913895130157,0.6359555795788765,0.7376911491155624,1000,paired source-video group resample,-0.006029009819030762,-0.006120115518569946,-0.015089163184165954,0.002483946084976194,C0,-0.05082511901855469,-0.050898075103759766,-0.08830933272838593,-0.012995079159736635, +C4,0.3/span_multi_short_A,rmse,0.943850592753208,0.9419921063082346,0.864123854380919,1.0233117118408521,1000,paired source-video group resample,,,,,C0,0.0022044431079099036,0.0002840758150310929,-0.05762015702127574,0.061225619589425226, +C4,0.3/span_multi_short_A,pearson,0.5749490261077881,0.5748330950737,0.506322619318962,0.6406708016991616,1000,paired source-video group resample,,,,,C0,0.058648645877838135,0.05977684259414673,0.005279667675495149,0.11317923739552498, +C4,0.3/location_start_V,accuracy,0.6112637362637363,0.6107993893225888,0.5735140931372549,0.6506060061140082,1000,paired source-video group resample,,,,,C0,0.015109890109890167,0.015256705467290743,-0.02012019904681811,0.04913729911813427, +C4,0.3/location_start_V,macro_f1,0.5524988033176134,0.5517427565579193,0.5166335783510334,0.590461673349809,1000,paired source-video group resample,,,,,C0,-0.01131187045234694,-0.012319813471285246,-0.048657932707844055,0.027681010812694373, +C4,0.3/location_start_V,mae,0.688166081905365,0.6883297860622406,0.63823212236166,0.7410118490457535,1000,paired source-video group resample,-0.0031618475914001465,-0.002500981092453003,-0.015449389815330505,0.005178965628147123,C0,-0.0452803373336792,-0.045339435338974,-0.08230308145284652,-0.010244385898113256, +C4,0.3/location_start_V,rmse,0.9415890528052248,0.9415106465643814,0.8595077376405041,1.0215671911531066,1000,paired source-video group resample,,,,,C0,0.004747732734014742,0.003983340253788881,-0.053199589657461716,0.06099362941240704, +C4,0.3/location_start_V,pearson,0.5754445195198059,0.575415164232254,0.5078396260738373,0.6420080974698067,1000,paired source-video group resample,,,,,C0,0.05440407991409302,0.05496908724308014,0.0004307940602302552,0.10456847399473188, +C4,0.3/location_middle_V,accuracy,0.6071428571428571,0.6071955012694887,0.5683029061102831,0.6456618448906281,1000,paired source-video group resample,,,,,C0,0.015109890109890056,0.015294773151633467,-0.01784007918702528,0.04965746868675814, +C4,0.3/location_middle_V,macro_f1,0.553655293772217,0.5531277377444697,0.5171830259776296,0.5908444347533164,1000,paired source-video group resample,,,,,C0,-0.0020536852641991343,-0.002108644696043438,-0.03839353117784675,0.036919005034184146, +C4,0.3/location_middle_V,mae,0.6922222375869751,0.692369818687439,0.6424834653735161,0.746068362891674,1000,paired source-video group resample,0.0008943080902099609,0.000631183385848999,-0.0019501745700836182,0.005158641934394836,C0,-0.04158782958984375,-0.04110836982727051,-0.08166107088327408,-0.002532562613487252, +C4,0.3/location_middle_V,rmse,0.950975965811902,0.9486362412363583,0.8707361240836737,1.0297706771238666,1000,paired source-video group resample,,,,,C0,0.012094759503309072,0.010718642307371296,-0.05088819473683391,0.07095180562433087, +C4,0.3/location_middle_V,pearson,0.5665525794029236,0.5664742290973663,0.4957543410360813,0.6316719993948936,1000,paired source-video group resample,,,,,C0,0.04752910137176514,0.04912266135215759,-0.0075067438185214995,0.10192761495709415, +C4,0.3/location_end_V,accuracy,0.6057692307692307,0.6053591222854839,0.5681639057663649,0.6441447978665842,1000,paired source-video group resample,,,,,C0,0.016483516483516425,0.017110048529295874,-0.017249583480587596,0.05125793386033617, +C4,0.3/location_end_V,macro_f1,0.5521449299042166,0.5514753803600823,0.515248592345577,0.5886324559134246,1000,paired source-video group resample,,,,,C0,-0.00113146496645522,-0.001169045605038166,-0.03738438055058349,0.040225813248454374, +C4,0.3/location_end_V,mae,0.6931080222129822,0.6930986046791077,0.6441185280680657,0.7455450564622879,1000,paired source-video group resample,0.001780092716217041,0.0017779767513275146,-0.00388869047164917,0.007756507396697995,C0,-0.04011034965515137,-0.0398043692111969,-0.07953879833221436,-0.0014643937349319521, +C4,0.3/location_end_V,rmse,0.9515387358305389,0.9496333154445911,0.8711832364153007,1.0303974832407807,1000,paired source-video group resample,,,,,C0,0.014094241318878709,0.01301374503743924,-0.0484319504924083,0.07437573592282591, +C4,0.3/location_end_V,pearson,0.5671343207359314,0.5668396651744843,0.4972432076931,0.6327486664056777,1000,paired source-video group resample,,,,,C0,0.04798591136932373,0.04912319779396057,-0.006960563361644743,0.10373104065656659, +C4,0.3/span_long_V,accuracy,0.6098901098901099,0.609464184501904,0.5718217881118767,0.6482020869524391,1000,paired source-video group resample,,,,,C0,0.02472527472527475,0.025332387627948316,-0.009538749738000396,0.059953322726046615, +C4,0.3/span_long_V,macro_f1,0.555693356057808,0.5550399886311363,0.5188260515060411,0.5939150426885366,1000,paired source-video group resample,,,,,C0,0.007079839289691359,0.00704152972715788,-0.02812408681546271,0.04638382489429994, +C4,0.3/span_long_V,mae,0.688922107219696,0.6888969540596008,0.6390544906258583,0.7416572377085685,1000,paired source-video group resample,-0.002405822277069092,-0.0015902519226074219,-0.013155204057693482,0.004599024355411529,C0,-0.045436203479766846,-0.04532217979431152,-0.08265226632356644,-0.009790235757827776, +C4,0.3/span_long_V,rmse,0.9425208746624658,0.9422279012667416,0.862917312088929,1.0218132755982934,1000,paired source-video group resample,,,,,C0,0.004688736943831873,0.004317377144248957,-0.05692454870517905,0.061420643870575574, +C4,0.3/span_long_V,pearson,0.5753633975982666,0.5755282938480377,0.5071772664785386,0.6410521879792214,1000,paired source-video group resample,,,,,C0,0.05548280477523804,0.05620492994785309,0.002496258914470673,0.106709149479866, +C4,0.3/span_multi_short_V,accuracy,0.6098901098901099,0.609464184501904,0.5718217881118767,0.6482020869524391,1000,paired source-video group resample,,,,,C0,0.02197802197802201,0.021881849715903012,-0.010613388654941802,0.055874467841324604, +C4,0.3/span_multi_short_V,macro_f1,0.555693356057808,0.5550399886311363,0.5188260515060411,0.5939150426885366,1000,paired source-video group resample,,,,,C0,0.004234038226899828,0.0038746096087625137,-0.029668562014692118,0.044096183012624926, +C4,0.3/span_multi_short_V,mae,0.6889951825141907,0.6890010237693787,0.639178791642189,0.7416124239563942,1000,paired source-video group resample,-0.002332746982574463,-0.0015556812286376953,-0.01300254613161087,0.004587188363075256,C0,-0.04460775852203369,-0.044737935066223145,-0.08183411806821823,-0.008328133821487428, +C4,0.3/span_multi_short_V,rmse,0.9427705115507411,0.9424460374810953,0.8631158468029052,1.0218428302376044,1000,paired source-video group resample,,,,,C0,0.004837675118837481,0.004518249453551282,-0.05652440566177884,0.061117590216774216, +C4,0.3/span_multi_short_V,pearson,0.5754638910293579,0.5754131376743317,0.5072209224104881,0.6412623688578606,1000,paired source-video group resample,,,,,C0,0.05594789981842041,0.056406646966934204,0.003109640628099442,0.10829408168792724, +C4,0.3/synchrony_sync,accuracy,0.5961538461538461,0.5959867411101085,0.555393902972028,0.6361055974593093,1000,paired source-video group resample,,,,,C0,0.008241758241758212,0.008374044552488247,-0.025258605888917447,0.04389920618219235, +C4,0.3/synchrony_sync,macro_f1,0.5258506273708355,0.5244779848401776,0.49009650984081754,0.5632905687525905,1000,paired source-video group resample,,,,,C0,-0.02310160364292657,-0.022726375514355107,-0.0624034316894524,0.017386968486657006, +C4,0.3/synchrony_sync,mae,0.7077205181121826,0.7074550688266754,0.6537706241011619,0.758461058139801,1000,paired source-video group resample,0.01639258861541748,0.016555309295654297,-0.0013306394219398494,0.03358944058418274,C0,-0.03522008657455444,-0.035465240478515625,-0.07858646959066391,0.006282724440097805, +C4,0.3/synchrony_sync,rmse,0.9560675927013004,0.9551122104523612,0.8696379379751709,1.0436135602575933,1000,paired source-video group resample,,,,,C0,0.004674381349467294,0.0032286897958956895,-0.06435707311241817,0.06818059062307473, +C4,0.3/synchrony_sync,pearson,0.5673331022262573,0.5673994421958923,0.49657903909683226,0.6367281049489975,1000,paired source-video group resample,,,,,C0,0.052408576011657715,0.05398523807525635,-0.006735920906066893,0.11301209479570387, +C4,0.3/synchrony_partial,accuracy,0.6112637362637363,0.6103404791929382,0.5730130170004186,0.6496646488573058,1000,paired source-video group resample,,,,,C0,0.019230769230769273,0.018979633495549486,-0.013817864869290921,0.052127990322434786, +C4,0.3/synchrony_partial,macro_f1,0.5397402621085391,0.5381593785942845,0.5058382088887607,0.5745024038171301,1000,paired source-video group resample,,,,,C0,-0.017108665167761772,-0.01684095401832092,-0.05359744168653078,0.022017980789076783, +C4,0.3/synchrony_partial,mae,0.7134761810302734,0.7127018570899963,0.6604793936014175,0.7686468824744225,1000,paired source-video group resample,0.0221482515335083,0.021813631057739258,0.0018928438425064088,0.041410765051841734,C0,-0.041478872299194336,-0.04257315397262573,-0.07854734212160111,-0.002421370148658756, +C4,0.3/synchrony_partial,rmse,0.9666930171784202,0.9656093040807874,0.882873354402018,1.0470702920859325,1000,paired source-video group resample,,,,,C0,0.01294501807172832,0.011485648644923241,-0.051722574225022,0.07514754408225525, +C4,0.3/synchrony_partial,pearson,0.5559995770454407,0.5558315515518188,0.4843445435166359,0.6264936864376068,1000,paired source-video group resample,,,,,C0,0.048255324363708496,0.05024687945842743,-0.007562454044818877,0.10297195315361023, +C4,0.3/synchrony_async,accuracy,0.5892857142857143,0.5892351274787535,0.5502652440959878,0.6294386503220362,1000,paired source-video group resample,,,,,C0,-0.005494505494505475,-0.0054127198917455766,-0.03918709633453072,0.03047944939748756, +C4,0.3/synchrony_async,macro_f1,0.5175130281347898,0.5162631338558028,0.481827840059868,0.5548441668033376,1000,paired source-video group resample,,,,,C0,-0.03983671700099645,-0.03970683281875331,-0.07898035308180724,0.0009444363566895716, +C4,0.3/synchrony_async,mae,0.7202104926109314,0.7198311686515808,0.6697185352444649,0.7694956123828888,1000,paired source-video group resample,0.02888256311416626,0.028883039951324463,0.008957298099994659,0.04829235672950744,C0,-0.03701227903366089,-0.03639209270477295,-0.08269908577203751,0.0054870292544364745, +C4,0.3/synchrony_async,rmse,0.9671278570023761,0.9661532790439151,0.8839723248694198,1.0447085618970586,1000,paired source-video group resample,,,,,C0,3.747211481985868e-05,-0.0011229982802531402,-0.06660517447043851,0.06444759447127826, +C4,0.3/synchrony_async,pearson,0.5520230531692505,0.5524864196777344,0.4808399774134159,0.6209137916564941,1000,paired source-video group resample,,,,,C0,0.054305821657180786,0.05511748790740967,-0.009989745914936066,0.11805987060070036, +C5,0.0/none,accuracy,0.6167582417582418,0.6174448268574706,0.5778945933253549,0.6570134032122021,1000,paired source-video group resample,,,,,C0,0.02472527472527475,0.02560733181248731,-0.008294396211523317,0.059783204460265485, +C5,0.0/none,macro_f1,0.5472420438041464,0.5470019765193006,0.5082240778210202,0.5881773088328391,1000,paired source-video group resample,,,,,C0,-0.008692568846884074,-0.008028345055340003,-0.04910408605171346,0.03265260294718926, +C5,0.0/none,mae,0.6614851951599121,0.6602856814861298,0.6084787353873253,0.7173394575715065,1000,paired source-video group resample,,,,,C0,-0.07192873954772949,-0.07313820719718933,-0.10894413143396378,-0.03438142836093903, +C5,0.0/none,rmse,0.8930216549130521,0.8905225485217502,0.8017799633854067,0.9807500224994694,1000,paired source-video group resample,,,,,C0,-0.04415200451513812,-0.04439683844200054,-0.09975240823670369,0.004358749946905626, +C5,0.0/none,pearson,0.6175699830055237,0.6177495419979095,0.5514360681176186,0.6802031084895134,1000,paired source-video group resample,,,,,C0,0.0983273983001709,0.10003140568733215,0.059197811782360076,0.14177455455064772, +C5,0.1/single,accuracy,0.6181318681318682,0.6186085006839723,0.5798055372322085,0.6586640142782776,1000,paired source-video group resample,,,,,C0,0.030219780219780223,0.03115495900237575,-0.003932496360360571,0.0665886257375042, +C5,0.1/single,macro_f1,0.5489006023531419,0.5484867554723718,0.5114355922532952,0.5888877522805573,1000,paired source-video group resample,,,,,C0,-0.0009841950837644609,0.000448095542178506,-0.044306510317224816,0.042624628729549724, +C5,0.1/single,mae,0.6595794558525085,0.6582507789134979,0.6068299800157547,0.713190658390522,1000,paired source-video group resample,-0.0019057393074035645,-0.0016411244869232178,-0.00848318338394165,0.0037412419915199267,C0,-0.07617974281311035,-0.07774436473846436,-0.1124132215976715,-0.037781545519828805, +C5,0.1/single,rmse,0.88945874600651,0.8870676840782842,0.799755965853932,0.974990938500631,1000,paired source-video group resample,,,,,C0,-0.04986382955473723,-0.05076335250031433,-0.10508071290579507,-0.0015151530157494603, +C5,0.1/single,pearson,0.6203741431236267,0.6203532814979553,0.5530810311436654,0.6826400563120842,1000,paired source-video group resample,,,,,C0,0.10379862785339355,0.1053595244884491,0.06459681838750839,0.1458058662712574, +C5,0.1/sync,accuracy,0.6153846153846154,0.6154971166613568,0.577239088159032,0.6585057596241002,1000,paired source-video group resample,,,,,C0,0.028846153846153855,0.0296883896115272,-0.005791299838490028,0.06355993435877333, +C5,0.1/sync,macro_f1,0.5396342159238499,0.5389522740985058,0.5030716309104615,0.5779685932318424,1000,paired source-video group resample,,,,,C0,-0.010693847170903381,-0.010488537842988255,-0.05566676426392393,0.030574780682534216, +C5,0.1/sync,mae,0.6589372158050537,0.6575060784816742,0.6062387838959694,0.7110101982951165,1000,paired source-video group resample,-0.0025479793548583984,-0.0021879076957702637,-0.011493320763111114,0.004896733164787292,C0,-0.07610565423965454,-0.07726475596427917,-0.11505046635866165,-0.03576845824718477, +C5,0.1/sync,rmse,0.8847905843889949,0.8817921000530142,0.7936764359307756,0.9740802814592796,1000,paired source-video group resample,,,,,C0,-0.06039267996629172,-0.06090499734592847,-0.1147743491979141,-0.008589555370286467, +C5,0.1/sync,pearson,0.6247382164001465,0.6260117888450623,0.5564168065786361,0.685821920633316,1000,paired source-video group resample,,,,,C0,0.11133837699890137,0.11266416311264038,0.07084224075078964,0.15586579889059066, +C5,0.1/partial,accuracy,0.6181318681318682,0.618917039431643,0.5794525871641129,0.657546844089433,1000,paired source-video group resample,,,,,C0,0.02472527472527475,0.026056152094636298,-0.008286672338721842,0.06008412823523739, +C5,0.1/partial,macro_f1,0.5483021392524529,0.548322290653267,0.5091359630544848,0.5856877126151286,1000,paired source-video group resample,,,,,C0,-0.00933079875085241,-0.00877955207919312,-0.05151021675166008,0.03299523256103716, +C5,0.1/partial,mae,0.6611794233322144,0.6607233583927155,0.6118624240159989,0.7139238744974137,1000,paired source-video group resample,-0.0003057718276977539,-0.0003565549850463867,-0.011735492944717407,0.012616954743862145,C0,-0.07403796911239624,-0.07549718022346497,-0.11318938732147217,-0.03448656946420671, +C5,0.1/partial,rmse,0.8960318825873537,0.8933713795786515,0.8084281411140013,0.9830589223497863,1000,paired source-video group resample,,,,,C0,-0.04141156281985836,-0.04159639034557555,-0.09571983676816578,0.010143649676356729, +C5,0.1/partial,pearson,0.6156103610992432,0.6159515678882599,0.545941884815693,0.6794859409332276,1000,paired source-video group resample,,,,,C0,0.09503680467605591,0.0947815477848053,0.05349807590246201,0.143044114112854, +C5,0.1/async,accuracy,0.6167582417582418,0.6173241321622751,0.5784985250174229,0.6584279594821426,1000,paired source-video group resample,,,,,C0,0.02472527472527475,0.025535768761439925,-0.007267779390420838,0.058993791445122894, +C5,0.1/async,macro_f1,0.5432278166156101,0.5428441387180909,0.5048966824745945,0.5822229389067095,1000,paired source-video group resample,,,,,C0,-0.015579205263796969,-0.0143862588852251,-0.055255449283815275,0.026911559329767704, +C5,0.1/async,mae,0.6622811555862427,0.6617320775985718,0.6094011038541793,0.715896600484848,1000,paired source-video group resample,0.0007959604263305664,0.0006207525730133057,-0.011902736127376556,0.015412087738513946,C0,-0.07661247253417969,-0.07695284485816956,-0.11345113515853882,-0.04077400863170624, +C5,0.1/async,rmse,0.893508026072056,0.8901125953086796,0.8009454623271993,0.981121817640356,1000,paired source-video group resample,,,,,C0,-0.05022661522546834,-0.05028099046458101,-0.10760793981896045,-0.004095489461959853, +C5,0.1/async,pearson,0.6171056628227234,0.6173247694969177,0.5476546123623848,0.6805330649018287,1000,paired source-video group resample,,,,,C0,0.10308969020843506,0.1037624180316925,0.06364450305700302,0.1497537426650524, +C5,0.3/single,accuracy,0.6112637362637363,0.6120765077595522,0.5708392603129445,0.6520712848881066,1000,paired source-video group resample,,,,,C0,0.005494505494505586,0.006738544474393537,-0.028452550294655564,0.03841248184917535, +C5,0.3/single,macro_f1,0.5380377076765831,0.5376473905814645,0.5013534813638537,0.576437152493533,1000,paired source-video group resample,,,,,C0,-0.03126154173186513,-0.02991512211217956,-0.07265549047129469,0.008309844808166576, +C5,0.3/single,mae,0.669231653213501,0.6684945523738861,0.6160126030445099,0.7217559829354286,1000,paired source-video group resample,0.007746458053588867,0.007629573345184326,-0.0006890207529067993,0.01628504991531372,C0,-0.06189948320388794,-0.06266501545906067,-0.10087120682001113,-0.02257130444049836, +C5,0.3/single,rmse,0.8956744622403668,0.8924178255812203,0.8055188971864561,0.9809837338468704,1000,paired source-video group resample,,,,,C0,-0.044093112493178044,-0.0446386391184051,-0.10189892852550446,0.003302885233127095, +C5,0.3/single,pearson,0.6156596541404724,0.6156827807426453,0.5484904825687409,0.6806976512074471,1000,paired source-video group resample,,,,,C0,0.09424406290054321,0.09480741620063782,0.05368910431861877,0.14008321315050123, 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+C5,0.3/sync,pearson,0.5995095372200012,0.6001969277858734,0.5284788087010384,0.6684618756175041,1000,paired source-video group resample,,,,,C0,0.10127460956573486,0.10190087556838989,0.057439330220222476,0.14840833172202106, +C5,0.3/partial,accuracy,0.6112637362637363,0.6115354745980781,0.5727776284932578,0.6533655264192815,1000,paired source-video group resample,,,,,C0,0.016483516483516536,0.016927198128242504,-0.019830555536029373,0.0517015406280375, +C5,0.3/partial,macro_f1,0.5357198308570972,0.534382215133005,0.4985075807986767,0.5769385075530687,1000,paired source-video group resample,,,,,C0,-0.02751581678637216,-0.02617659851200277,-0.06965420826362252,0.014140691478006282, +C5,0.3/partial,mae,0.6784146428108215,0.6774928569793701,0.6257377818226815,0.731720969080925,1000,paired source-video group resample,0.016929447650909424,0.01699259877204895,-0.0005366280674934386,0.03569522500038146,C0,-0.06813704967498779,-0.06802546977996826,-0.1087718516588211,-0.02949374914169312, +C5,0.3/partial,rmse,0.9127770212416307,0.9108662041789992,0.8266640688430141,0.9998227018465569,1000,paired source-video group resample,,,,,C0,-0.04002117202234534,-0.039810379438308174,-0.09732989068285845,0.014100179504775157, +C5,0.3/partial,pearson,0.6027075052261353,0.6012693643569946,0.5325523853302002,0.666956402361393,1000,paired source-video group resample,,,,,C0,0.09399372339248657,0.09407122433185577,0.047241609543561935,0.14467905685305593, +C5,0.3/async,accuracy,0.6098901098901099,0.609928306969384,0.5688335937237823,0.6498561040919049,1000,paired source-video group resample,,,,,C0,0.030219780219780223,0.030116372767648003,-0.0026865104379101444,0.06500896167350044, +C5,0.3/async,macro_f1,0.5325178988754369,0.5313623255360191,0.49498035817622293,0.5688828485511105,1000,paired source-video group resample,,,,,C0,-0.013632571673238059,-0.014008485596130993,-0.04997390593264904,0.023262404593584095, 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+C5,0.5/sync,pearson,0.5873285531997681,0.5883788466453552,0.5128410547971726,0.6587404772639275,1000,paired source-video group resample,,,,,C0,0.10767027735710144,0.10909104347229004,0.0563979908823967,0.15688585266470909, +C5,0.5/partial,accuracy,0.6236263736263736,0.6248489909168674,0.5831928833323315,0.6622698974163987,1000,paired source-video group resample,,,,,C0,0.038461538461538436,0.03962576874427526,0.0027456855225311523,0.07479743767313025, +C5,0.5/partial,macro_f1,0.5500356253422286,0.5499092856544123,0.5130001003720696,0.5865038610900174,1000,paired source-video group resample,,,,,C0,-0.0015606053972024858,0.00014429321071840473,-0.04408441503824628,0.04228639692593168, +C5,0.5/partial,mae,0.6918403506278992,0.6905665993690491,0.6355805084109306,0.7502555206418038,1000,paired source-video group resample,0.03035515546798706,0.030286312103271484,0.004865643382072449,0.05678096860647201,C0,-0.09361875057220459,-0.09479179978370667,-0.13742713630199432,-0.05191514939069748, +C5,0.5/partial,rmse,0.9497894329812627,0.9487661687560613,0.8513864446264464,1.047612682246101,1000,paired source-video group resample,,,,,C0,-0.04982136235518608,-0.0524042909995972,-0.1108396283126531,0.006877627809026932, +C5,0.5/partial,pearson,0.569974958896637,0.5705875754356384,0.492987285554409,0.6450261071324348,1000,paired source-video group resample,,,,,C0,0.08856934309005737,0.09075644612312317,0.0340996190905571,0.14362990260124206, +C5,0.5/async,accuracy,0.603021978021978,0.6042087200398546,0.564725173816083,0.6432590558443736,1000,paired source-video group resample,,,,,C0,0.030219780219780223,0.0315437596549194,-0.0067492470959415515,0.06612947658402203, +C5,0.5/async,macro_f1,0.5244313216277192,0.5249761069772716,0.4891226718603821,0.5627593676616253,1000,paired source-video group resample,,,,,C0,-0.01621667480680755,-0.014450753570766195,-0.061481990663092775,0.02640569683048171, +C5,0.5/async,mae,0.6998383402824402,0.698088526725769,0.6471152454614639,0.7562528371810913,1000,paired source-video group resample,0.038353145122528076,0.03799447417259216,0.01661444455385208,0.06285426914691924,C0,-0.09342634677886963,-0.09459462761878967,-0.13864436596632004,-0.049893257021903996, +C5,0.5/async,rmse,0.9350483627357221,0.931760076324617,0.8490959773132034,1.0295143811673522,1000,paired source-video group resample,,,,,C0,-0.06827937090844871,-0.06862992421046571,-0.12894641136230564,-0.009998180668940182, +C5,0.5/async,pearson,0.5855488777160645,0.5866378247737885,0.5063483864068985,0.6531193315982818,1000,paired source-video group resample,,,,,C0,0.1110541820526123,0.11155159771442413,0.05804614424705505,0.16368017867207527, +C5,0.7/single,accuracy,0.6085164835164835,0.6096999096999097,0.5698728035667454,0.6479589139364399,1000,paired source-video group resample,,,,,C0,0.02335164835164827,0.024797618444754754,-0.007648648119079593,0.05720192513730838, +C5,0.7/single,macro_f1,0.5318305855707431,0.5318346326729932,0.4958140286022408,0.5674433699577554,1000,paired source-video group resample,,,,,C0,-0.019480386931753912,-0.018274728949063124,-0.056390280716586465,0.02172450341801855, +C5,0.7/single,mae,0.6934533715248108,0.6925519704818726,0.6467178225517273,0.7436924785375595,1000,paired source-video group resample,0.03196817636489868,0.03222772479057312,0.017212986946105957,0.046555612981319425,C0,-0.09449523687362671,-0.09601390361785889,-0.13785853534936904,-0.052433338761329655, +C5,0.7/single,rmse,0.9157693039642631,0.9133836382199232,0.8322392478175646,1.0021226824012752,1000,paired source-video group resample,,,,,C0,-0.09455469145966533,-0.09558888347932931,-0.1473768039570103,-0.041841682321613546, +C5,0.7/single,pearson,0.6033442616462708,0.6043498814105988,0.5323374956846237,0.6656245470046996,1000,paired source-video group resample,,,,,C0,0.13070404529571533,0.1322895735502243,0.08611867502331734,0.1755863934755325, +C5,0.7/sync,accuracy,0.5934065934065934,0.5942515663891512,0.5525971904165227,0.6356337631226661,1000,paired source-video group resample,,,,,C0,0.01098901098901095,0.012371139864262304,-0.02414907915808743,0.04471105723246661, +C5,0.7/sync,macro_f1,0.5083952582799544,0.5086132369493293,0.4718724196955079,0.5475914555395283,1000,paired source-video group resample,,,,,C0,-0.04054424182040972,-0.0393390507222639,-0.07988398535392242,-0.00010924261079780321, +C5,0.7/sync,mae,0.7390094995498657,0.7384954392910004,0.681541420519352,0.7954717814922333,1000,paired source-video group resample,0.07752430438995361,0.07706034183502197,0.046081002056598666,0.11002210080623626,C0,-0.04436212778091431,-0.045836418867111206,-0.0922365888953209,0.0034423619508743256, +C5,0.7/sync,rmse,0.98839161373488,0.9860432731238565,0.8936216787687817,1.0813259379512796,1000,paired source-video group resample,,,,,C0,-0.03176382782241749,-0.03359494142126579,-0.10051591992327873,0.03385690563426461, +C5,0.7/sync,pearson,0.5451185703277588,0.5454644560813904,0.46147547140717504,0.6224869906902313,1000,paired source-video group resample,,,,,C0,0.06667351722717285,0.06842862069606781,0.005336447805166245,0.12338066697120664, +C5,0.7/partial,accuracy,0.6057692307692307,0.6065798885626082,0.5649718220891229,0.6457522573061922,1000,paired source-video group resample,,,,,C0,0.012362637362637319,0.01344124873536634,-0.029014652474597235,0.05042505374242724, +C5,0.7/partial,macro_f1,0.5297443556495737,0.5292160081882964,0.49235457736196714,0.5675027320331507,1000,paired source-video group resample,,,,,C0,-0.034269081567036785,-0.03375958482656377,-0.08018433112683677,0.007094542255619827, +C5,0.7/partial,mae,0.7296777367591858,0.7285692095756531,0.673089200258255,0.7863904997706412,1000,paired source-video group resample,0.06819254159927368,0.06846839189529419,0.0400417760014534,0.10023165643215179,C0,-0.06791359186172485,-0.06786951422691345,-0.11655256748199463,-0.02155155390501023, +C5,0.7/partial,rmse,0.9807493560598313,0.9785337764282729,0.8910218883185291,1.074014660160948,1000,paired source-video group resample,,,,,C0,-0.03670733570708462,-0.037647818657670085,-0.10266298393940256,0.026570445457425793, +C5,0.7/partial,pearson,0.5454626083374023,0.5454936921596527,0.4611801363527775,0.6228370890021324,1000,paired source-video group resample,,,,,C0,0.0529857873916626,0.054096102714538574,-0.008433584868907927,0.10945890694856643, +C5,0.7/async,accuracy,0.6057692307692307,0.6059520933977456,0.5673758865248227,0.6455776864101588,1000,paired source-video group resample,,,,,C0,0.027472527472527375,0.028314312055844115,-0.006559320976096869,0.06226780912159116, +C5,0.7/async,macro_f1,0.5185459119627982,0.5176910628380664,0.48698541826672165,0.5540763858068394,1000,paired source-video group resample,,,,,C0,-0.035252151045105595,-0.03451558163152574,-0.0714820530335563,0.0022743613503610365, +C5,0.7/async,mae,0.7206351161003113,0.7201390564441681,0.670122717320919,0.7692815810441971,1000,paired source-video group resample,0.05914992094039917,0.05912920832633972,0.03108673691749573,0.08843531608581542,C0,-0.0958244800567627,-0.09536802768707275,-0.14082530736923218,-0.052093960344791426, +C5,0.7/async,rmse,0.9518248022698312,0.9503059753846939,0.8673562058737093,1.0373387987561378,1000,paired source-video group resample,,,,,C0,-0.08897007650452293,-0.08920454164474667,-0.14695268455581056,-0.028272439016325663, +C5,0.7/async,pearson,0.5787580013275146,0.5805484056472778,0.5062819823622704,0.6396170392632484,1000,paired source-video group resample,,,,,C0,0.09956184029579163,0.1008104532957077,0.04551163017749786,0.15230215191841126, +C5,0.3/modality_T,accuracy,0.6071428571428571,0.6076487252124646,0.5688421655171109,0.6458044830171149,1000,paired source-video group resample,,,,,C0,0.02060439560439553,0.02081978760294756,-0.009648001587523972,0.05270823936250195, +C5,0.3/modality_T,macro_f1,0.5360302739580002,0.5353994157226071,0.49890721271914756,0.5729419362060216,1000,paired source-video group resample,,,,,C0,-0.010733039485706586,-0.010028686944934972,-0.04693672511150813,0.029463524994001646, +C5,0.3/modality_T,mae,0.6954180598258972,0.6941642463207245,0.6448851302266121,0.7517668381333351,1000,paired source-video group resample,0.03393286466598511,0.033868223428726196,0.015646056830883028,0.05387007594108581,C0,-0.054705679416656494,-0.055325090885162354,-0.09539476782083511,-0.011550806462764743, +C5,0.3/modality_T,rmse,0.9434969783910451,0.9415532366605,0.8585889192946239,1.0322126642926777,1000,paired source-video group resample,,,,,C0,-0.019172353263075537,-0.020795850124836257,-0.0769633651624093,0.03335335025534451, +C5,0.3/modality_T,pearson,0.5764783024787903,0.5773822367191315,0.5071498692035675,0.641794653236866,1000,paired source-video group resample,,,,,C0,0.07471591234207153,0.07595844566822052,0.02654767483472824,0.12570081874728203, +C5,0.3/modality_A,accuracy,0.6153846153846154,0.6160220994475138,0.5762822648718291,0.6563825640342561,1000,paired source-video group resample,,,,,C0,0.028846153846153855,0.029861361754527527,-0.0053921191117956456,0.06540856963200284, +C5,0.3/modality_A,macro_f1,0.5432006724156517,0.5421328369907814,0.5056586109420734,0.5849216835826329,1000,paired source-video group resample,,,,,C0,-0.008281096244245556,-0.0065267055469783175,-0.05068411478249238,0.034256340152297116, +C5,0.3/modality_A,mae,0.6611783504486084,0.6598584949970245,0.607609075307846,0.7160015225410461,1000,paired source-video group resample,-0.00030684471130371094,-0.00017210841178894043,-0.006028908491134644,0.004267299175262451,C0,-0.06898868083953857,-0.06981438398361206,-0.10569343715906143,-0.029178433120250702, +C5,0.3/modality_A,rmse,0.8914525052639585,0.8885781876310798,0.8009821896040175,0.9774417525738546,1000,paired source-video group resample,,,,,C0,-0.04285985505212142,-0.043084511813461346,-0.09812734670315743,0.005655513321455769, +C5,0.3/modality_A,pearson,0.6200178265571594,0.6204757988452911,0.5502523198723793,0.6820215284824371,1000,paired source-video group resample,,,,,C0,0.09728080034255981,0.09859022498130798,0.05842569246888161,0.1402342788875103, +C5,0.3/modality_V,accuracy,0.6167582417582418,0.6173587701765059,0.577377915451895,0.6567340137040181,1000,paired source-video group resample,,,,,C0,0.028846153846153855,0.02939119703825588,-0.0027640915235958657,0.06326462235098199, +C5,0.3/modality_V,macro_f1,0.5485761874059746,0.5483582090115451,0.510455454424759,0.5875788797728984,1000,paired source-video group resample,,,,,C0,-0.002517158576874179,-0.002021704413289971,-0.041094832843726156,0.037802982956456926, +C5,0.3/modality_V,mae,0.6621425747871399,0.6610502004623413,0.6088704541325569,0.7176571324467659,1000,paired source-video group resample,0.0006573796272277832,0.0002390742301940918,-0.0031697675585746765,0.0062945038080215445,C0,-0.07119053602218628,-0.07212737202644348,-0.10871490985155105,-0.032627242803573625, +C5,0.3/modality_V,rmse,0.8934156632798638,0.8901246821244995,0.8037058661309707,0.9829488234489103,1000,paired source-video group resample,,,,,C0,-0.04437706903276262,-0.044980138252802726,-0.10017448354957603,0.005290098240728929, +C5,0.3/modality_V,pearson,0.6157838106155396,0.6159536242485046,0.5479116052389145,0.6802024871110917,1000,paired source-video group resample,,,,,C0,0.09633797407150269,0.09782978892326355,0.056782522797584535,0.1395043686032295, +C5,0.3/modality_TA,accuracy,0.6002747252747253,0.6011236509185885,0.5596557088744589,0.6416091318278914,1000,paired source-video group resample,,,,,C0,0.013736263736263687,0.013888996057068337,-0.021393249381864158,0.0452223890450634, +C5,0.3/modality_TA,macro_f1,0.5233145618659637,0.5228193257827172,0.48573627415390586,0.5599326537203672,1000,paired source-video group resample,,,,,C0,-0.030883725294329145,-0.030016458387431277,-0.06856022785581242,0.0059953340736017815, +C5,0.3/modality_TA,mae,0.6914730668067932,0.6911180317401886,0.6369116872549057,0.745648731291294,1000,paired source-video group resample,0.029987871646881104,0.030322611331939697,0.009880371391773224,0.053350406885147084,C0,-0.08411246538162231,-0.08497154712677002,-0.12293794304132462,-0.04647611975669862, +C5,0.3/modality_TA,rmse,0.9404050322694538,0.9379190144335399,0.8452109452603564,1.029760730174613,1000,paired source-video group resample,,,,,C0,-0.03021605408398298,-0.03218094418131645,-0.09298511292887991,0.028058576003468182, +C5,0.3/modality_TA,pearson,0.5784021615982056,0.577923595905304,0.5057521760463715,0.6472062781453133,1000,paired source-video group resample,,,,,C0,0.07996219396591187,0.081090047955513,0.027061453461647032,0.13598913326859474, +C5,0.3/modality_TV,accuracy,0.6181318681318682,0.6182572614107884,0.5806007982842846,0.6562656458611482,1000,paired source-video group resample,,,,,C0,0.0357142857142857,0.0366459491399308,-0.001506309761047242,0.07163204814915372, +C5,0.3/modality_TV,macro_f1,0.5516737145829397,0.55092222389238,0.5132057874493045,0.5895703228485055,1000,paired source-video group resample,,,,,C0,0.006829126594081414,0.007596350635836913,-0.036658436724134436,0.04942486006257446, +C5,0.3/modality_TV,mae,0.6674476265907288,0.6667045950889587,0.6149393692612648,0.717955595254898,1000,paired source-video group resample,0.00596243143081665,0.00583803653717041,-0.011944659054279327,0.024874955415725708,C0,-0.09322613477706909,-0.09419572353363037,-0.13567604422569274,-0.05108080953359604, 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+C5,0.3/modality_AV,mae,0.6598120331764221,0.658406674861908,0.6060694009065628,0.7141570314764977,1000,paired source-video group resample,-0.0016731619834899902,-0.001600801944732666,-0.00467679351568222,0.0009610548615455621,C0,-0.07816880941390991,-0.07894295454025269,-0.11528884619474411,-0.04028255939483644, +C5,0.3/modality_AV,rmse,0.8909428347264297,0.8882511787607058,0.7987636190275563,0.9796689104536955,1000,paired source-video group resample,,,,,C0,-0.051092392775160866,-0.051763795586289074,-0.10650983744050518,-0.0024458988637935486, +C5,0.3/modality_AV,pearson,0.6185941100120544,0.6188179850578308,0.5520272150635719,0.682449559867382,1000,paired source-video group resample,,,,,C0,0.10306018590927124,0.10425117611885071,0.06499271392822266,0.1445707194507122, +C5,0.3/modality_TAV,accuracy,0.603021978021978,0.6033067804483595,0.5655034866847607,0.6420213560334528,1000,paired source-video group resample,,,,,C0,0.0219780219780219,0.022346368715083775,-0.014051283916308444,0.057180200049164, +C5,0.3/modality_TAV,macro_f1,0.5319137909339083,0.5311645521593849,0.49679592152051444,0.5687778992296343,1000,paired source-video group resample,,,,,C0,-0.012564107670373859,-0.012415476183482155,-0.05269108524113872,0.02951614390461062, +C5,0.3/modality_TAV,mae,0.694097638130188,0.6934633553028107,0.6405165538191795,0.75175341963768,1000,paired source-video group resample,0.03261244297027588,0.032540589570999146,0.009403140842914581,0.059606750309467306,C0,-0.07683408260345459,-0.076836496591568,-0.11615577489137649,-0.03722198903560638, +C5,0.3/modality_TAV,rmse,0.9548139772438068,0.952293099100463,0.8654652966744457,1.0420719676744228,1000,paired source-video group resample,,,,,C0,-0.025223784417562345,-0.026224639972908248,-0.08004425650360517,0.02810417097187634, +C5,0.3/modality_TAV,pearson,0.5653194785118103,0.5660882294178009,0.49018982201814654,0.6357558324933051,1000,paired source-video group resample,,,,,C0,0.07500997185707092,0.07615083456039429,0.025944364070892335,0.12528085336089131, +C5,0.3/location_start_T,accuracy,0.6085164835164835,0.6090480255669382,0.5675647483366537,0.6490863767084084,1000,paired source-video group resample,,,,,C0,0.016483516483516425,0.017130878061394128,-0.016250241235720726,0.051629193610445705, +C5,0.3/location_start_T,macro_f1,0.5356301115849358,0.5350199057018467,0.4985720143918288,0.5765594249850349,1000,paired source-video group resample,,,,,C0,-0.025561061983387035,-0.024547398437625323,-0.06466428333517839,0.015903618932129403, +C5,0.3/location_start_T,mae,0.6981588006019592,0.6969102621078491,0.6429269164800644,0.7574667185544968,1000,paired source-video group resample,0.03667360544204712,0.035663902759552,0.016821978986263274,0.06182673573493957,C0,-0.07110238075256348,-0.07187321782112122,-0.11269501596689224,-0.029642273485660557, +C5,0.3/location_start_T,rmse,0.9532616314122102,0.9514871814706658,0.8577863467793592,1.04323251366826,1000,paired source-video group resample,,,,,C0,-0.022052298199849885,-0.023013919408661265,-0.08772994526776824,0.03636353097979907, +C5,0.3/location_start_T,pearson,0.574300229549408,0.5754596889019012,0.4993946962058544,0.6431435227394103,1000,paired source-video group resample,,,,,C0,0.09175077080726624,0.09180645644664764,0.03981433734297753,0.14701623320579527, +C5,0.3/location_middle_T,accuracy,0.6126373626373627,0.613325593938832,0.5741425092764378,0.6518261782378919,1000,paired source-video group resample,,,,,C0,0.02335164835164838,0.02318900502031168,-0.009437184245798536,0.05633853700236102, +C5,0.3/location_middle_T,macro_f1,0.5369816261469684,0.5366795300243818,0.4996879010830056,0.575272327161763,1000,paired source-video group resample,,,,,C0,-0.013819877539348435,-0.013493694402282264,-0.05593035964439229,0.024720397529083813, +C5,0.3/location_middle_T,mae,0.6673615574836731,0.6665608882904053,0.6151848301291466,0.7224697530269623,1000,paired source-video group resample,0.005876362323760986,0.00584450364112854,-0.0072991251945495605,0.02197583019733429,C0,-0.08140581846237183,-0.08237221837043762,-0.1213991954922676,-0.04285878986120225, +C5,0.3/location_middle_T,rmse,0.903064390478453,0.8999119475608852,0.811829168485595,0.9945983591014121,1000,paired source-video group resample,,,,,C0,-0.05839288427236222,-0.05966850932646944,-0.11646781009600668,-0.0060932067300689275, +C5,0.3/location_middle_T,pearson,0.6095016002655029,0.6097365021705627,0.5385861277580262,0.6763774067163467,1000,paired source-video group resample,,,,,C0,0.102547287940979,0.10429711639881134,0.05528480112552643,0.15335152968764304, +C5,0.3/location_end_T,accuracy,0.6126373626373627,0.613031914893617,0.5741751700680272,0.6512994904626701,1000,paired source-video group resample,,,,,C0,0.03846153846153855,0.03848799068881609,0.0026666913069190103,0.07407536907536907, +C5,0.3/location_end_T,macro_f1,0.5295160661065462,0.527693914809028,0.49268477855450354,0.5650306578698184,1000,paired source-video group resample,,,,,C0,-0.008452107823346822,-0.008272047325164789,-0.04970229619398096,0.030122367331896535, +C5,0.3/location_end_T,mae,0.6767091751098633,0.6759883165359497,0.6291437387466431,0.7244307547807693,1000,paired source-video group resample,0.015223979949951172,0.014951169490814209,-0.007882599532604216,0.03737065196037292,C0,-0.09244370460510254,-0.09273472428321838,-0.12996283322572708,-0.05346416234970093, +C5,0.3/location_end_T,rmse,0.8915885264184252,0.889991718985562,0.814765303025864,0.9591717321837052,1000,paired source-video group resample,,,,,C0,-0.0859440423096155,-0.08668355384145399,-0.1349910126107949,-0.0379529998050935, +C5,0.3/location_end_T,pearson,0.6239807605743408,0.6253765225410461,0.5599429801106452,0.6804315567016601,1000,paired source-video group resample,,,,,C0,0.11729615926742554,0.117156982421875,0.07457133606076241,0.16153371185064314, +C5,0.3/span_long_T,accuracy,0.6126373626373627,0.6127909504050584,0.5730583756345178,0.6519932682806324,1000,paired source-video group resample,,,,,C0,0.03434065934065933,0.03530242605516787,0.0,0.06583658739651482, +C5,0.3/span_long_T,macro_f1,0.538143207967629,0.5372270701296877,0.5025946483246815,0.5760352704709558,1000,paired source-video group resample,,,,,C0,-0.0019612671023720996,-0.0008375858681893833,-0.043184405332562924,0.0377838705375213, +C5,0.3/span_long_T,mae,0.6797055006027222,0.6787881553173065,0.6276784107089043,0.7338908120989799,1000,paired source-video group resample,0.01822030544281006,0.017963171005249023,-0.000539755821228027,0.039892661571502674,C0,-0.06941604614257812,-0.07032662630081177,-0.10770325213670731,-0.02831045836210253, +C5,0.3/span_long_T,rmse,0.9188844374824722,0.9159145138992394,0.8276414961738702,1.0079620705266628,1000,paired source-video group resample,,,,,C0,-0.04501348354239798,-0.046704633160725095,-0.0993452436120281,0.005693723737451938, +C5,0.3/span_long_T,pearson,0.5985926985740662,0.599888026714325,0.5277152702212333,0.6645459562540055,1000,paired source-video group resample,,,,,C0,0.09861359000205994,0.10008414089679718,0.05531388819217682,0.1470168352127075, +C5,0.3/span_multi_short_T,accuracy,0.6167582417582418,0.6169014084507042,0.5775569703555196,0.6568825623379404,1000,paired source-video group resample,,,,,C0,0.028846153846153855,0.029392983246938564,-0.0026911924610366037,0.06121022408477236, +C5,0.3/span_multi_short_T,macro_f1,0.5488464752023345,0.5483602131156169,0.5111741660107244,0.5866562579052577,1000,paired source-video group resample,,,,,C0,-0.002697980084283791,-0.0007823589108543749,-0.04154526264616793,0.034768689828043146, +C5,0.3/span_multi_short_T,mae,0.671114444732666,0.6700058579444885,0.6179981395602226,0.7231546700000763,1000,paired source-video group resample,0.009629249572753906,0.009887456893920898,-0.00729546993970871,0.024437542259693145,C0,-0.08034110069274902,-0.08123466372489929,-0.11763105690479278,-0.04280281960964204, +C5,0.3/span_multi_short_T,rmse,0.9044235503287618,0.9015272169936351,0.8157443641305223,0.9883118484531209,1000,paired source-video group resample,,,,,C0,-0.05627455535161974,-0.05579709769830227,-0.1139125171113434,-0.00732435331644986, +C5,0.3/span_multi_short_T,pearson,0.6083298325538635,0.6092288792133331,0.5409302666783333,0.6752825602889061,1000,paired source-video group resample,,,,,C0,0.10672128200531006,0.1075608879327774,0.06395334303379059,0.15496109277009965, +C5,0.3/location_start_A,accuracy,0.6098901098901099,0.6099488824840937,0.5720172830777671,0.6506968883565876,1000,paired source-video group resample,,,,,C0,0.026098901098901117,0.026613451568121893,-0.008174354020767863,0.06202328802422211, +C5,0.3/location_start_A,macro_f1,0.5357930060135943,0.5361987381062845,0.4960506049807927,0.573362085125651,1000,paired source-video group resample,,,,,C0,-0.020987154383632967,-0.019883129432166413,-0.0616102501374032,0.01850438531765999, +C5,0.3/location_start_A,mae,0.6655371785163879,0.6637930572032928,0.6130323007702827,0.7204374879598617,1000,paired source-video group resample,0.00405198335647583,0.004248946905136108,-0.0022450610995292664,0.010246545076370238,C0,-0.0694611668586731,-0.07067793607711792,-0.10806942284107209,-0.03189711421728135, +C5,0.3/location_start_A,rmse,0.8954666111577266,0.8924003752637837,0.806789120748491,0.9816205053796141,1000,paired source-video group resample,,,,,C0,-0.045330736536940974,-0.045603976480241726,-0.09636628094327261,-0.0005762965185937751, +C5,0.3/location_start_A,pearson,0.6193514466285706,0.6194441020488739,0.5506680920720101,0.6813395276665688,1000,paired source-video group resample,,,,,C0,0.1016077995300293,0.10253840684890747,0.06379261761903762,0.14461778849363327, +C5,0.3/location_middle_A,accuracy,0.6167582417582418,0.617036649858566,0.5782875615763547,0.6569887374036751,1000,paired source-video group resample,,,,,C0,0.030219780219780223,0.031043500880772013,-0.0028819483430433863,0.06536923065262458, +C5,0.3/location_middle_A,macro_f1,0.5442589070248645,0.5433439541130143,0.5067419659846707,0.5851656476713825,1000,paired source-video group resample,,,,,C0,-0.009503916303176263,-0.008549622216426411,-0.05117221926727898,0.03222820708380797, +C5,0.3/location_middle_A,mae,0.6602234244346619,0.6585668921470642,0.606007145345211,0.7145532667636871,1000,paired source-video group resample,-0.0012617707252502441,-0.0010630786418914795,-0.0067146018147468565,0.00323110520839691,C0,-0.07379984855651855,-0.07455003261566162,-0.11121575981378555,-0.03422249853610993, +C5,0.3/location_middle_A,rmse,0.8904711607194068,0.8878615488757887,0.7994067678581005,0.9770365763061157,1000,paired source-video group resample,,,,,C0,-0.046307774934231216,-0.04659543524196408,-0.10168131057374684,0.0033554251674603234, +C5,0.3/location_middle_A,pearson,0.620025098323822,0.6204262375831604,0.5504714965820312,0.6823737055063248,1000,paired source-video group resample,,,,,C0,0.09966385364532471,0.10146483778953552,0.059577809274196626,0.14283456653356552, +C5,0.3/location_end_A,accuracy,0.6167582417582418,0.6172851711026616,0.5782907625075348,0.6570223964852339,1000,paired source-video group resample,,,,,C0,0.027472527472527486,0.02840107549409876,-0.006601466444097464,0.06311287043124639, +C5,0.3/location_end_A,macro_f1,0.5458873530018568,0.5453522769007162,0.508160759927111,0.5865195962561414,1000,paired source-video group resample,,,,,C0,-0.007511808263201969,-0.006924653336075615,-0.048983638949048745,0.03521830260734082, +C5,0.3/location_end_A,mae,0.6595189571380615,0.6578196585178375,0.6062079817056656,0.714251346886158,1000,paired source-video group resample,-0.001966238021850586,-0.0019105374813079834,-0.007668352127075195,0.0020618915557861326,C0,-0.07522797584533691,-0.07621726393699646,-0.11124959737062454,-0.036311502754688266, +C5,0.3/location_end_A,rmse,0.8893358370213341,0.8867679699710789,0.7981629320567615,0.9755749119119971,1000,paired source-video group resample,,,,,C0,-0.04833358380705832,-0.04862182697271267,-0.10288042921318713,-0.0005244225337664358, +C5,0.3/location_end_A,pearson,0.620370090007782,0.6206704080104828,0.5515141740441323,0.6825070321559906,1000,paired source-video group resample,,,,,C0,0.10141873359680176,0.1026964783668518,0.06290601193904877,0.14431239664554596, +C5,0.3/span_long_A,accuracy,0.6112637362637363,0.6114249968124442,0.5737654665654174,0.6509238647800604,1000,paired source-video group resample,,,,,C0,0.02335164835164838,0.024440019910403232,-0.011739086454165317,0.05866862483311079, +C5,0.3/span_long_A,macro_f1,0.5385156271593234,0.5387250509373693,0.5001646959793897,0.5770798458578061,1000,paired source-video group resample,,,,,C0,-0.015821653493746646,-0.014774538416084004,-0.05642085459824914,0.027050295153386552, +C5,0.3/span_long_A,mae,0.663811981678009,0.6624687314033508,0.610634334385395,0.7185426115989685,1000,paired source-video group resample,0.002326786518096924,0.00249481201171875,-0.003840410709381103,0.007644467055797577,C0,-0.07284688949584961,-0.07407650351524353,-0.11068183332681655,-0.03420552760362625, +C5,0.3/span_long_A,rmse,0.8932535299791378,0.8904144635180028,0.8038609118271303,0.9790565381232091,1000,paired source-video group resample,,,,,C0,-0.04469954657422481,-0.04497329799948868,-0.0986314639431536,0.0045732279237827534, +C5,0.3/span_long_A,pearson,0.6195688843727112,0.6197366118431091,0.5507425963878632,0.6816685333847999,1000,paired source-video group resample,,,,,C0,0.10203897953033447,0.103451207280159,0.0639133483171463,0.1432636797428131, +C5,0.3/span_multi_short_A,accuracy,0.6112637362637363,0.6114249968124442,0.5737654665654174,0.6509238647800604,1000,paired source-video group resample,,,,,C0,0.016483516483516536,0.017543859649122806,-0.016952016689846906,0.05333384146341465, +C5,0.3/span_multi_short_A,macro_f1,0.5385156271593234,0.5387250509373693,0.5001646959793897,0.5770798458578061,1000,paired source-video group resample,,,,,C0,-0.021762208424684903,-0.020348403035290452,-0.063716755834305,0.020380696080072515, +C5,0.3/span_multi_short_A,mae,0.6638219952583313,0.6624291241168976,0.6108277156949043,0.7185739666223526,1000,paired source-video group resample,0.0023368000984191895,0.00247308611869812,-0.003710101544857025,0.007479231059551238,C0,-0.07230204343795776,-0.07330089807510376,-0.10933654308319092,-0.03367463797330858, +C5,0.3/span_multi_short_A,rmse,0.8932042169376566,0.8903901291187053,0.8039937803632548,0.9791722825822947,1000,paired source-video group resample,,,,,C0,-0.04844193270764152,-0.0490530061830845,-0.10282496291473035,0.0010302465293589014, +C5,0.3/span_multi_short_A,pearson,0.6198986768722534,0.6199093461036682,0.5513497069478035,0.6818069875240326,1000,paired source-video group resample,,,,,C0,0.10359829664230347,0.1048528254032135,0.06400079429149627,0.14647755175828933, +C5,0.3/location_start_V,accuracy,0.6167582417582418,0.617463281916488,0.5773761921319293,0.6556986545680217,1000,paired source-video group resample,,,,,C0,0.020604395604395642,0.02141479435795235,-0.012645866773675712,0.05533779344436682, +C5,0.3/location_start_V,macro_f1,0.5530343005051815,0.5533566733396676,0.5142524509886236,0.5905158826159617,1000,paired source-video group resample,,,,,C0,-0.01077637326477876,-0.009952026229943511,-0.05056586549632635,0.03147712730765331, +C5,0.3/location_start_V,mae,0.6567240953445435,0.6557374000549316,0.6024452924728394,0.713523043692112,1000,paired source-video group resample,-0.004761099815368652,-0.0048792362213134766,-0.012267908453941346,0.0028480708599090566,C0,-0.07672232389450073,-0.07771673798561096,-0.11377153992652893,-0.039834848046302794, +C5,0.3/location_start_V,rmse,0.8899500112746497,0.8868274697570158,0.7974229705251669,0.9801437379131275,1000,paired source-video group resample,,,,,C0,-0.04689130879656034,-0.0470018969605665,-0.10171973731205816,0.002384175725714056, +C5,0.3/location_start_V,pearson,0.6147137880325317,0.6148504912853241,0.5442880868911744,0.6799793973565101,1000,paired source-video group resample,,,,,C0,0.09367334842681885,0.09469582140445709,0.054679422080516814,0.137295588850975, +C5,0.3/location_middle_V,accuracy,0.6167582417582418,0.6173401360544217,0.5771770939087535,0.6563442428437237,1000,paired source-video group resample,,,,,C0,0.02472527472527475,0.025672410005335322,-0.0077158210861587445,0.0589202403884392, +C5,0.3/location_middle_V,macro_f1,0.5489591803273203,0.5487432376302912,0.5100752279944809,0.5879106301692308,1000,paired source-video group resample,,,,,C0,-0.006749798709095867,-0.006058223395792872,-0.045642350955244416,0.0337773264659631, +C5,0.3/location_middle_V,mae,0.6577937006950378,0.6567022204399109,0.604664970934391,0.7122140154242516,1000,paired source-video group resample,-0.0036914944648742676,-0.003791123628616333,-0.010448656976222992,0.0036877632141113278,C0,-0.076016366481781,-0.07701104879379272,-0.11337826550006866,-0.03755127191543582, +C5,0.3/location_middle_V,rmse,0.8871376963654639,0.8849492985295806,0.7958755361555169,0.9769370602154452,1000,paired source-video group resample,,,,,C0,-0.05174350994312904,-0.05197325666003677,-0.10739212841389378,-0.0005880851998783844, +C5,0.3/location_middle_V,pearson,0.6200913786888123,0.6200215816497803,0.5511686414480209,0.6830755665898323,1000,paired source-video group resample,,,,,C0,0.10106790065765381,0.10209572315216064,0.06081739813089371,0.14447302520275113, +C5,0.3/location_end_V,accuracy,0.6167582417582418,0.6174448268574706,0.5778945933253549,0.6570134032122021,1000,paired source-video group resample,,,,,C0,0.027472527472527486,0.028128321461998507,-0.004146137285393908,0.06356223478623468, +C5,0.3/location_end_V,macro_f1,0.5472420438041464,0.5470019765193006,0.5082240778210202,0.5881773088328391,1000,paired source-video group resample,,,,,C0,-0.00603435106652539,-0.005244518266972031,-0.04589403100885933,0.03676860368770152, +C5,0.3/location_end_V,mae,0.6608195304870605,0.6594541072845459,0.6077465653419495,0.716711688041687,1000,paired source-video group resample,-0.0006656646728515625,-0.0006363391876220703,-0.0013994038105010985,1.4424324035644423e-06,C0,-0.072398841381073,-0.07349181175231934,-0.11006730198860168,-0.03376631438732147, +C5,0.3/location_end_V,rmse,0.8918785174807694,0.8890750767972911,0.8002282083986828,0.9798842960620406,1000,paired source-video group resample,,,,,C0,-0.045565977030890825,-0.045902076147076365,-0.10130091669033359,0.0028328410836238136, +C5,0.3/location_end_V,pearson,0.6176557540893555,0.61777064204216,0.5511863708496094,0.6806202620267868,1000,paired source-video group resample,,,,,C0,0.0985073447227478,0.10026800632476807,0.05981646105647087,0.14178176075220109, +C5,0.3/span_long_V,accuracy,0.6181318681318682,0.6187882383477326,0.579290274577573,0.6579124221844935,1000,paired source-video group resample,,,,,C0,0.03296703296703296,0.03387439936888914,0.0,0.06815277612295963, +C5,0.3/span_long_V,macro_f1,0.5516421356421356,0.5515572467178523,0.5131837375322028,0.5896849153430991,1000,paired source-video group resample,,,,,C0,0.0030286188740189512,0.00397231580916152,-0.037460493730853195,0.043408144548391814, +C5,0.3/span_long_V,mae,0.6578363180160522,0.656680554151535,0.605210417509079,0.7116457462310791,1000,paired source-video group resample,-0.0036488771438598633,-0.003563612699508667,-0.010926668345928193,0.003454111516475674,C0,-0.07652199268341064,-0.07773047685623169,-0.11295984387397766,-0.038856601715087896, +C5,0.3/span_long_V,rmse,0.8887878342313473,0.8860829783800308,0.7974912840817003,0.9785506501246705,1000,paired source-video group resample,,,,,C0,-0.04904430348728661,-0.04963680613476312,-0.10218470295646308,0.00039055787817003553, +C5,0.3/span_long_V,pearson,0.6190096139907837,0.619177520275116,0.5474731847643852,0.6829074770212173,1000,paired source-video group resample,,,,,C0,0.09912902116775513,0.1005823016166687,0.060778388381004335,0.14115312695503235, +C5,0.3/span_multi_short_V,accuracy,0.6167582417582418,0.6174087814691176,0.5773776083467094,0.6562523045722713,1000,paired source-video group resample,,,,,C0,0.028846153846153855,0.02941176470588236,-0.002722991294419824,0.06293060172542582, +C5,0.3/span_multi_short_V,macro_f1,0.5503033233773417,0.5501905970970853,0.5120014958719122,0.588670924412289,1000,paired source-video group resample,,,,,C0,-0.0011559944535665112,-0.0006465141522210005,-0.040822630580345264,0.03889652694332862, +C5,0.3/span_multi_short_V,mae,0.6602821946144104,0.659216970205307,0.6072147339582443,0.7148182570934295,1000,paired source-video group resample,-0.001203000545501709,-0.001309901475906372,-0.006343851983547211,0.004803398251533508,C0,-0.07332074642181396,-0.0746239721775055,-0.10973096787929534,-0.035242560505867014, +C5,0.3/span_multi_short_V,rmse,0.8922059266013054,0.8888632570082349,0.8003227259356912,0.9815799652658042,1000,paired source-video group resample,,,,,C0,-0.04572690983059824,-0.0461363629295623,-0.10095912686394666,0.004172055962855858, +C5,0.3/span_multi_short_V,pearson,0.6163780093193054,0.6165367364883423,0.5477672636508941,0.6809372186660767,1000,paired source-video group resample,,,,,C0,0.09686201810836792,0.0984409749507904,0.05796915516257286,0.13960231095552444, +C5,0.3/synchrony_sync,accuracy,0.6016483516483516,0.6020334327652914,0.5616916748003244,0.6407864887856651,1000,paired source-video group resample,,,,,C0,0.013736263736263687,0.014255232676285312,-0.021505762021567065,0.046544428772919644, +C5,0.3/synchrony_sync,macro_f1,0.5301058450681209,0.5294952161302341,0.49407112398195746,0.5683185667621833,1000,paired source-video group resample,,,,,C0,-0.018846385945641253,-0.018313036432074825,-0.060850909084266026,0.02182285923991031, +C5,0.3/synchrony_sync,mae,0.6838570833206177,0.6824451684951782,0.6302359208464623,0.7382927909493446,1000,paired source-video group resample,0.022371888160705566,0.022176235914230347,0.007723776996135712,0.04078545421361923,C0,-0.059083521366119385,-0.06016415357589722,-0.09931496977806091,-0.020161135494709024, +C5,0.3/synchrony_sync,rmse,0.9243095385603125,0.9227132860292879,0.8326918713901404,1.015254432644266,1000,paired source-video group resample,,,,,C0,-0.027083672791520574,-0.029200112195836347,-0.08677946328994787,0.0269601142161351, +C5,0.3/synchrony_sync,pearson,0.5931302905082703,0.5942903161048889,0.5192366153001785,0.659320242702961,1000,paired source-video group resample,,,,,C0,0.07820576429367065,0.07950720191001892,0.03292743116617203,0.13067124262452126, +C5,0.3/synchrony_partial,accuracy,0.6181318681318682,0.6176046176046176,0.579011746680286,0.6566051832255536,1000,paired source-video group resample,,,,,C0,0.026098901098901117,0.026573426573426595,-0.00967725353807119,0.06173641173641178, +C5,0.3/synchrony_partial,macro_f1,0.5514262781135847,0.5506518789011738,0.512683010564962,0.5905173058631769,1000,paired source-video group resample,,,,,C0,-0.0054226491627161755,-0.004571034511078209,-0.04656690700753557,0.037182677792043234, +C5,0.3/synchrony_partial,mae,0.6768262386322021,0.6761603653430939,0.6261470034718514,0.7334077298641205,1000,paired source-video group resample,0.015341043472290039,0.01552504301071167,0.00037226974964141865,0.03131441175937652,C0,-0.07812881469726562,-0.07918420433998108,-0.11571809649467468,-0.038361112773418436, +C5,0.3/synchrony_partial,rmse,0.9173706053875333,0.9147987786922868,0.8272156267987004,1.0036308398098943,1000,paired source-video group resample,,,,,C0,-0.03637739371915849,-0.037041999482121335,-0.09221654278949418,0.012785493382196396, +C5,0.3/synchrony_partial,pearson,0.5965014100074768,0.5974459052085876,0.5244996771216393,0.662453955411911,1000,paired source-video group resample,,,,,C0,0.08875715732574463,0.08984643220901489,0.048101408034563066,0.13273231387138368, +C5,0.3/synchrony_async,accuracy,0.6153846153846154,0.616279322165211,0.5769176136363636,0.656141376921455,1000,paired source-video group resample,,,,,C0,0.020604395604395642,0.02132102668229935,-0.009796891327063786,0.05072591525111916, +C5,0.3/synchrony_async,macro_f1,0.5411840411840413,0.5401919255165217,0.5043689504481994,0.5763892381956162,1000,paired source-video group resample,,,,,C0,-0.016165703951744992,-0.01573924675927041,-0.05262883714649558,0.018893797316437935, +C5,0.3/synchrony_async,mae,0.6807641386985779,0.6797074973583221,0.6281941965222358,0.7360720410943031,1000,paired source-video group resample,0.01927894353866577,0.01925826072692871,0.0016055658459663395,0.03773019760847091,C0,-0.0764586329460144,-0.07664704322814941,-0.12043470591306686,-0.032611873745918285, +C5,0.3/synchrony_async,rmse,0.9189795590058603,0.9162397765991429,0.8280127595451835,1.0090879509266915,1000,paired source-video group resample,,,,,C0,-0.04811082588169602,-0.04880307850336052,-0.10922655018507649,0.00685303358846308, +C5,0.3/synchrony_async,pearson,0.5979559421539307,0.5985121130943298,0.5271463096141815,0.6621271416544914,1000,paired source-video group resample,,,,,C0,0.10023871064186096,0.10130748152732849,0.0527540534734726,0.15319585353136062, +C6,0.0/none,accuracy,0.6263736263736264,0.6259630702818945,0.589224194646976,0.6641825253141908,1000,paired source-video group resample,,,,,C0,0.03434065934065933,0.03429812940682503,0.0,0.06780382257482874, +C6,0.0/none,macro_f1,0.5801114274083624,0.5785240057958365,0.5422223679266986,0.6160757043061501,1000,paired source-video group resample,,,,,C0,0.02417681475733191,0.023838536672179056,-0.01515056384533787,0.06159552243952476, +C6,0.0/none,mae,0.6456943154335022,0.6448003053665161,0.5972962126135826,0.7009974539279937,1000,paired source-video group resample,,,,,C0,-0.0877196192741394,-0.08756077289581299,-0.12537434548139573,-0.05080907940864563, +C6,0.0/none,rmse,0.8813849190313564,0.8791790165489568,0.8035965234585467,0.9638092841038779,1000,paired source-video group resample,,,,,C0,-0.05578874039683379,-0.0552391777230169,-0.10409934391730433,-0.010557576672472889, +C6,0.0/none,pearson,0.6157324910163879,0.6157523691654205,0.5528023809194564,0.6728250712156296,1000,paired source-video group resample,,,,,C0,0.09648990631103516,0.09679923951625824,0.052419553697109225,0.14107245728373527, +C6,0.1/single,accuracy,0.6277472527472527,0.6270272639607258,0.5926334685969418,0.6653443456744867,1000,paired source-video group resample,,,,,C0,0.039835164835164805,0.039780262840607594,0.006952242357944159,0.07164294508832465, +C6,0.1/single,macro_f1,0.5824275156133015,0.5807879875195355,0.5453532241310632,0.618095116294259,1000,paired source-video group resample,,,,,C0,0.0325427181763952,0.03226236775208402,-0.005693249753211232,0.06913282036025577, +C6,0.1/single,mae,0.6468294858932495,0.6459291875362396,0.5982175827026367,0.7009683549404144,1000,paired source-video group resample,0.0011351704597473145,0.0011261999607086182,-0.0028207108378410337,0.0050828069448471055,C0,-0.08892971277236938,-0.08840283751487732,-0.12757602483034133,-0.05247070044279099, +C6,0.1/single,rmse,0.8830850231196125,0.8812845642083147,0.8051171795506368,0.9644003721017909,1000,paired source-video group resample,,,,,C0,-0.05623755244163475,-0.055589823221491974,-0.10467991046195708,-0.0101603151786385, +C6,0.1/single,pearson,0.6146003603935242,0.6149593591690063,0.5522068247199059,0.6717073321342468,1000,paired source-video group resample,,,,,C0,0.09802484512329102,0.09865643084049225,0.05448075532913208,0.14260284304618837, +C6,0.1/sync,accuracy,0.6263736263736264,0.6258800463416808,0.5916757754599108,0.663237096784079,1000,paired source-video group resample,,,,,C0,0.039835164835164805,0.03994392112016287,0.005269496842962043,0.07104053775979145, +C6,0.1/sync,macro_f1,0.5785093334257027,0.5767536579405713,0.5401271974374783,0.6149831283557089,1000,paired source-video group resample,,,,,C0,0.028181270330949415,0.028377349591087397,-0.011064450080505172,0.06480102511642888, +C6,0.1/sync,mae,0.645142674446106,0.6451226770877838,0.5973339453339577,0.7008568465709686,1000,paired source-video group resample,-0.0005516409873962402,-0.0005687475204467773,-0.009862250089645386,0.0076546847820281975,C0,-0.0899001955986023,-0.08969986438751221,-0.1270020678639412,-0.05532919317483903, +C6,0.1/sync,rmse,0.8796729579556977,0.878248501754143,0.8032048556568894,0.9616486765521947,1000,paired source-video group resample,,,,,C0,-0.06551030639958899,-0.06524943009661771,-0.11551899218135915,-0.018355227871502837, +C6,0.1/sync,pearson,0.6184161305427551,0.6192063391208649,0.5553588077425957,0.6734680950641632,1000,paired source-video group resample,,,,,C0,0.10501629114151001,0.10503096878528595,0.06484482884407043,0.14698692113161083, +C6,0.1/partial,accuracy,0.6195054945054945,0.6191099947707264,0.5832106565376901,0.6570852285033572,1000,paired source-video group resample,,,,,C0,0.026098901098901117,0.026939578829867916,-0.008506444454936002,0.05573575455126736, +C6,0.1/partial,macro_f1,0.568898052766151,0.5677791322026201,0.5325620753351868,0.6054800078828391,1000,paired source-video group resample,,,,,C0,0.011265114762845752,0.012658229661165254,-0.028515674759764565,0.04641926926047457, +C6,0.1/partial,mae,0.6582462787628174,0.6568759381771088,0.6078082025051117,0.716423037648201,1000,paired source-video group resample,0.012551963329315186,0.012321799993515015,0.001491282880306244,0.025326701998710628,C0,-0.07697111368179321,-0.07724088430404663,-0.11411987096071244,-0.039406712353229525, +C6,0.1/partial,rmse,0.9042675433747003,0.9009485817172627,0.8191925441676337,0.9911974137919459,1000,paired source-video group resample,,,,,C0,-0.03317590203251175,-0.033054024066417276,-0.08673892091406142,0.019486978220451798, +C6,0.1/partial,pearson,0.598304271697998,0.6005784869194031,0.5294778108596802,0.6635158017277718,1000,paired source-video group resample,,,,,C0,0.07773071527481079,0.07739004492759705,0.031303302943706514,0.12826811522245404, +C6,0.1/async,accuracy,0.6263736263736264,0.6255048109499932,0.5906174180698895,0.6656728094944906,1000,paired source-video group resample,,,,,C0,0.03434065934065933,0.03439321942506657,0.0013619852501640772,0.06452484742807328, +C6,0.1/async,macro_f1,0.5764843456205114,0.5745295010445406,0.5383686229965764,0.6147437759133665,1000,paired source-video group resample,,,,,C0,0.01767732374110431,0.018032811857976616,-0.0194606047371667,0.05272928304419034, +C6,0.1/async,mae,0.6489292979240417,0.6481515169143677,0.6014014542102813,0.7057931035757065,1000,paired source-video group resample,0.0032349824905395508,0.0033490359783172607,-0.004847897589206696,0.011079871654510496,C0,-0.08996433019638062,-0.08914902806282043,-0.12853361815214157,-0.05351788997650147, +C6,0.1/async,rmse,0.8809399282497081,0.8792674360162276,0.8036894366146017,0.960408456858387,1000,paired source-video group resample,,,,,C0,-0.06279471304781625,-0.06334460443628764,-0.11291766857065157,-0.016205267244431287, +C6,0.1/async,pearson,0.6172679662704468,0.6173900663852692,0.5569128334522248,0.672800500690937,1000,paired source-video group resample,,,,,C0,0.10325199365615845,0.10295724868774414,0.06099566519260406,0.14805773496627805, +C6,0.3/single,accuracy,0.6277472527472527,0.6272019334049409,0.5915056699504792,0.666193331234859,1000,paired source-video group resample,,,,,C0,0.02197802197802201,0.02185006790018673,-0.012803189103962434,0.05646203393579926, +C6,0.3/single,macro_f1,0.5769832954517803,0.5757843717146154,0.5389016637134717,0.6128442418285024,1000,paired source-video group resample,,,,,C0,0.00768404604333206,0.007981764974288486,-0.032542344235891044,0.04694235225850235, +C6,0.3/single,mae,0.64957594871521,0.6486470699310303,0.601265013217926,0.7048607096076012,1000,paired source-video group resample,0.0038816332817077637,0.0041811466217041016,-0.007191395759582519,0.013500736653804779,C0,-0.08155518770217896,-0.08146494626998901,-0.11967403739690781,-0.04312413036823273, +C6,0.3/single,rmse,0.8826084745162333,0.8809759184615422,0.80751042383915,0.9645364853787182,1000,paired source-video group resample,,,,,C0,-0.05715910021731163,-0.05730342737914634,-0.10881930202405904,-0.007224664053938917, +C6,0.3/single,pearson,0.6178518533706665,0.6177624464035034,0.5546815782785416,0.675531105697155,1000,paired source-video group resample,,,,,C0,0.0964362621307373,0.09576088190078735,0.05198956578969956,0.1449733793735504, +C6,0.3/sync,accuracy,0.625,0.6244238104868235,0.5872364854044656,0.6627762145549314,1000,paired source-video group resample,,,,,C0,0.04532967032967028,0.04462046318402385,0.012078124022556059,0.07529984388539795, +C6,0.3/sync,macro_f1,0.5694580560033625,0.5686324880064232,0.5326683105930722,0.6042972163580005,1000,paired source-video group resample,,,,,C0,0.029357066563874712,0.028520522147942984,-0.005827674228718757,0.06371951230435029, +C6,0.3/sync,mae,0.6604288220405579,0.660707026720047,0.6104607820510864,0.714640511572361,1000,paired source-video group resample,0.014734506607055664,0.014715194702148438,-0.000806458294391632,0.03038416504859924,C0,-0.09247487783432007,-0.09246084094047546,-0.13095220029354096,-0.05423215478658677, +C6,0.3/sync,rmse,0.8929904844988137,0.8915380150228664,0.8138302336855616,0.9699466849555965,1000,paired source-video group resample,,,,,C0,-0.06930223126546364,-0.07001996184785458,-0.11722016992292034,-0.02085290056286221, +C6,0.3/sync,pearson,0.6099379658699036,0.6108051836490631,0.5488109901547432,0.6678569123148919,1000,paired source-video group resample,,,,,C0,0.11170303821563721,0.11222465336322784,0.06846525371074677,0.1558099590241909, +C6,0.3/partial,accuracy,0.6304945054945055,0.6304034237705958,0.5937026063914433,0.6690166735708368,1000,paired source-video group resample,,,,,C0,0.0357142857142857,0.0356662009629376,0.0013945066997835987,0.06916555157258952, +C6,0.3/partial,macro_f1,0.5805366219622385,0.579463694123557,0.542276219325158,0.6184029877856846,1000,paired source-video group resample,,,,,C0,0.017300974318769202,0.01758584551675524,-0.023011795889899104,0.05619700471707877, +C6,0.3/partial,mae,0.6589491963386536,0.6589687466621399,0.6062816068530082,0.7172071889042854,1000,paired source-video group resample,0.013254880905151367,0.012815266847610474,-0.0016933932900428772,0.02748652398586273,C0,-0.08760249614715576,-0.08698275685310364,-0.12883380502462388,-0.049031578004360206, +C6,0.3/partial,rmse,0.9053050409127582,0.9019024579993256,0.8163988760621183,0.9990650886881942,1000,paired source-video group resample,,,,,C0,-0.04749315235121787,-0.04703577802875136,-0.1034087080320593,0.0021087760248480027, +C6,0.3/partial,pearson,0.6000605225563049,0.6013011038303375,0.5290678203105926,0.6649399369955062,1000,paired source-video group resample,,,,,C0,0.09134674072265625,0.09100170433521271,0.04570642560720444,0.1385145731270313, +C6,0.3/async,accuracy,0.6167582417582418,0.6160716174630221,0.579577565291851,0.6535956840836894,1000,paired source-video group resample,,,,,C0,0.03708791208791207,0.037599220893459295,0.004509577306440191,0.06902571929861942, +C6,0.3/async,macro_f1,0.5600885851904333,0.5586585947119738,0.524086411652943,0.595622420144339,1000,paired source-video group resample,,,,,C0,0.013938114641758315,0.0139858515609102,-0.021736723313599753,0.05008664147090091, +C6,0.3/async,mae,0.6701546311378479,0.6700699925422668,0.6218541905283927,0.7250375390052796,1000,paired source-video group resample,0.024460315704345703,0.02446773648262024,0.010647837817668915,0.03773790895938873,C0,-0.09842878580093384,-0.09907644987106323,-0.1390886664390564,-0.06052065640687944, +C6,0.3/async,rmse,0.90098899437452,0.8996072169934809,0.8254661080011451,0.9828361973737371,1000,paired source-video group resample,,,,,C0,-0.08211580018141007,-0.08197589954800588,-0.13516309626128836,-0.034828392360364765, +C6,0.3/async,pearson,0.6035482883453369,0.6052914559841156,0.5392118334770203,0.6610672131180764,1000,paired source-video group resample,,,,,C0,0.11670234799385071,0.11677233874797821,0.07263565361499787,0.1659655451774597, +C6,0.5/single,accuracy,0.6277472527472527,0.6273570901192658,0.5900432039834936,0.6671429871486453,1000,paired source-video group resample,,,,,C0,0.04120879120879117,0.040871934604904625,0.0039510400475329015,0.07680950698948893, +C6,0.5/single,macro_f1,0.5778207210911699,0.5767610585802383,0.5386682698353605,0.6171408576502385,1000,paired source-video group resample,,,,,C0,0.022803438929286934,0.02188880432003759,-0.019037897027161025,0.06456266939768367, +C6,0.5/single,mae,0.6532634496688843,0.6526212096214294,0.6057352647185326,0.7053175881505013,1000,paired source-video group resample,0.00756913423538208,0.00768771767616272,-0.004851731657981873,0.019847670197486875,C0,-0.0957648754119873,-0.09560298919677734,-0.13451822251081466,-0.06019131690263748, +C6,0.5/single,rmse,0.8853428791191722,0.8837982477921378,0.8053024977448885,0.9681035692290034,1000,paired source-video group resample,,,,,C0,-0.07430795839336135,-0.07481442343638589,-0.12219329151333802,-0.02982392881535924, +C6,0.5/single,pearson,0.6187843680381775,0.619404524564743,0.5565291926264763,0.6752105236053466,1000,paired source-video group resample,,,,,C0,0.11055111885070801,0.11191385984420776,0.06964480578899383,0.15620571449398993, +C6,0.5/sync,accuracy,0.6304945054945055,0.6301919052722911,0.5934065934065934,0.6684945031589931,1000,paired source-video group resample,,,,,C0,0.03708791208791207,0.03615295675050689,0.0,0.07133841800959521, +C6,0.5/sync,macro_f1,0.5724655586489998,0.571407231381651,0.5341184392782488,0.6079499311095234,1000,paired source-video group resample,,,,,C0,0.008962019252816367,0.008452223412624749,-0.03287407462042712,0.0486042488088578, +C6,0.5/sync,mae,0.6754302978515625,0.6743738651275635,0.6243621841073036,0.7333655416965484,1000,paired source-video group resample,0.029735982418060303,0.029161572456359863,0.012690386176109314,0.0495238184928894,C0,-0.11186397075653076,-0.11134830117225647,-0.15277546793222427,-0.07127282619476319, +C6,0.5/sync,rmse,0.9176811579398299,0.9138702614281313,0.8358773443473909,1.0069359713517947,1000,paired source-video group resample,,,,,C0,-0.08469038098635862,-0.08605381823509262,-0.1370363017739753,-0.034607917349868005, +C6,0.5/sync,pearson,0.59506756067276,0.5966707170009613,0.5249012053012848,0.6568038940429687,1000,paired source-video group resample,,,,,C0,0.11540928483009338,0.11543568968772888,0.07286486253142357,0.1594613842666149, +C6,0.5/partial,accuracy,0.614010989010989,0.6143790849673203,0.5770739640292267,0.6506222660919401,1000,paired source-video group resample,,,,,C0,0.028846153846153855,0.029735657526066828,-0.005039122657487481,0.06182132535094963, +C6,0.5/partial,macro_f1,0.5518325479272103,0.5511375419182911,0.5153745682779453,0.5876776729579573,1000,paired source-video group resample,,,,,C0,0.000236317187779167,0.00132047878932523,-0.040012195243545524,0.03879239740832505, +C6,0.5/partial,mae,0.6957768201828003,0.6948275566101074,0.6403195127844811,0.7530457586050033,1000,paired source-video group resample,0.050082504749298096,0.050050288438797,0.028554993867874145,0.07471490353345871,C0,-0.08968228101730347,-0.09078571200370789,-0.1313041031360626,-0.047127267718315144, +C6,0.5/partial,rmse,0.9543291209047196,0.9533445851410425,0.8651037496753725,1.0459986172076066,1000,paired source-video group resample,,,,,C0,-0.04528167443172926,-0.047177413863893236,-0.10166247147790163,0.01100029254780634, +C6,0.5/partial,pearson,0.5570251941680908,0.5578035712242126,0.4808178752660751,0.6290390312671661,1000,paired source-video group resample,,,,,C0,0.07561957836151123,0.0771031528711319,0.020975736528635026,0.1301898308098316, +C6,0.5/async,accuracy,0.6277472527472527,0.6273683151678678,0.5936597124235705,0.6648057958051288,1000,paired source-video group resample,,,,,C0,0.05494505494505497,0.05506498788988112,0.018253982981981803,0.08990143135034705, +C6,0.5/async,macro_f1,0.5732193022515603,0.572265298369658,0.5356622925681073,0.6080779768720842,1000,paired source-video group resample,,,,,C0,0.03257130581703349,0.032935481952708345,-0.00812738225672741,0.07408275735195763, +C6,0.5/async,mae,0.6663943529129028,0.6653361320495605,0.6134188175201416,0.7280182734131813,1000,paired source-video group resample,0.020700037479400635,0.020655184984207153,0.00012083500623703003,0.04438918083906174,C0,-0.12687033414840698,-0.1261654794216156,-0.17168737649917604,-0.0839517816901207, +C6,0.5/async,rmse,0.9187985829074612,0.9153430804029683,0.8275794937837166,1.016443167276535,1000,paired source-video group resample,,,,,C0,-0.08452915073670964,-0.08471878736857608,-0.1503063066570472,-0.021232310110935772, +C6,0.5/async,pearson,0.5918467044830322,0.5928572118282318,0.5150987833738327,0.661002142727375,1000,paired source-video group resample,,,,,C0,0.11735200881958008,0.11724241077899933,0.05959264412522316,0.17298821434378625, +C6,0.7/single,accuracy,0.6195054945054945,0.6185007729107599,0.583105761689535,0.6552684402612371,1000,paired source-video group resample,,,,,C0,0.03434065934065933,0.034484581125267755,0.0,0.06996170136072813, +C6,0.7/single,macro_f1,0.561271113032066,0.5598196703254569,0.5244589182010027,0.5953831137040896,1000,paired source-video group resample,,,,,C0,0.00996014052956895,0.009611619175551256,-0.02991207370756685,0.0494389760904737, +C6,0.7/single,mae,0.684191882610321,0.6835354864597321,0.6352564483880997,0.7404286682605743,1000,paired source-video group resample,0.03849756717681885,0.0384581983089447,0.019665913283824922,0.05892469733953475,C0,-0.10375672578811646,-0.10372933745384216,-0.14613682329654692,-0.06129065155982972, +C6,0.7/single,rmse,0.9204068859254733,0.9180408686742598,0.8443404041974957,1.0018218927362856,1000,paired source-video group resample,,,,,C0,-0.08991710949845522,-0.08998995791618125,-0.14376845775918465,-0.03221764565729584, +C6,0.7/single,pearson,0.5912657380104065,0.5914101898670197,0.5259430184960365,0.6510292395949364,1000,paired source-video group resample,,,,,C0,0.11862552165985107,0.11925181746482849,0.06723442003130913,0.167268119007349, +C6,0.7/sync,accuracy,0.6098901098901099,0.6092780201826806,0.5697545577530116,0.6500725714188139,1000,paired source-video group resample,,,,,C0,0.027472527472527486,0.026958909703788503,-0.010207091686232028,0.06368091657968478, +C6,0.7/sync,macro_f1,0.5301995918400428,0.5288312191624097,0.49402487542828394,0.5651681764975259,1000,paired source-video group resample,,,,,C0,-0.018739908260321236,-0.018498907995360747,-0.06515611393526222,0.02537453484467746, +C6,0.7/sync,mae,0.7239429354667664,0.7242822349071503,0.6693039551377297,0.7879881739616394,1000,paired source-video group resample,0.07824862003326416,0.07820576429367065,0.05017886310815811,0.10683500617742538,C0,-0.05942869186401367,-0.059083372354507446,-0.1050514593720436,-0.01350156515836719, +C6,0.7/sync,rmse,0.9768238785950085,0.9737688924060866,0.8794439653842265,1.0750860681595167,1000,paired source-video group resample,,,,,C0,-0.043331562962289016,-0.04478746336393391,-0.10592592239740974,0.019299602443208205, +C6,0.7/sync,pearson,0.5530099868774414,0.5534013509750366,0.47366724014282224,0.6262412533164023,1000,paired source-video group resample,,,,,C0,0.07456493377685547,0.0773281455039978,0.018512722849845887,0.13213614672422408, +C6,0.7/partial,accuracy,0.6208791208791209,0.6219502081571047,0.5842367388423106,0.6569887374036751,1000,paired source-video group resample,,,,,C0,0.027472527472527486,0.02756762625281417,-0.009099167992169394,0.06250684306569343, +C6,0.7/partial,macro_f1,0.5449597151896254,0.5450362427740199,0.5109905718015628,0.5802779136178571,1000,paired source-video group resample,,,,,C0,-0.019053722026985076,-0.018442518408036568,-0.060038550613795934,0.020217888363580953, +C6,0.7/partial,mae,0.7190655469894409,0.7185425460338593,0.6655095353722572,0.7794360682368279,1000,paired source-video group resample,0.07337123155593872,0.07321310043334961,0.04621903747320175,0.10394173860549927,C0,-0.07852578163146973,-0.07786700129508972,-0.1259642496705055,-0.03467246592044832, +C6,0.7/partial,rmse,0.9677142482175759,0.9675701362253517,0.8856128259467869,1.0624334155149826,1000,paired source-video group resample,,,,,C0,-0.04974244354933999,-0.04927179160421086,-0.10452980146724072,0.0048425132182432626, +C6,0.7/partial,pearson,0.5590499639511108,0.5596635043621063,0.48625972494482994,0.6225992769002914,1000,paired source-video group resample,,,,,C0,0.0665731430053711,0.06632930040359497,0.014453580230474473,0.11960095763206482, +C6,0.7/async,accuracy,0.6153846153846154,0.6156414436055823,0.5794592578331809,0.6510990308532172,1000,paired source-video group resample,,,,,C0,0.03708791208791207,0.03789495693889389,0.004041361342121784,0.07102466236054024, +C6,0.7/async,macro_f1,0.5399170479776244,0.5389396513565552,0.5061810003562589,0.5728630268566143,1000,paired source-video group resample,,,,,C0,-0.013881015030279387,-0.013636066559508497,-0.050886268766148025,0.026886916485110813, +C6,0.7/async,mae,0.70497727394104,0.7052985727787018,0.6555742666125297,0.7570146083831787,1000,paired source-video group resample,0.05928295850753784,0.058832764625549316,0.029972578585147857,0.08923029750585555,C0,-0.11148232221603394,-0.11146223545074463,-0.15764341354370118,-0.06567388027906418, +C6,0.7/async,rmse,0.9370124820867136,0.9363480802257044,0.8601740507306637,1.0211163575561817,1000,paired source-video group resample,,,,,C0,-0.10378239668764055,-0.10384520459006313,-0.1662610887820057,-0.04084228113832211, +C6,0.7/async,pearson,0.5893937349319458,0.5900403261184692,0.5234048530459404,0.6464896216988564,1000,paired source-video group resample,,,,,C0,0.11019757390022278,0.11090126633644104,0.049903422594070435,0.16607524305582047, +C6,0.3/modality_T,accuracy,0.6208791208791209,0.6205244980625692,0.5839998042331698,0.6564015369913354,1000,paired source-video group resample,,,,,C0,0.03434065934065933,0.03415928854038758,0.0,0.0668386067435882, +C6,0.3/modality_T,macro_f1,0.5668092055188829,0.5655916610024112,0.5314618283300407,0.6001860604517516,1000,paired source-video group resample,,,,,C0,0.020045892075176153,0.020044580065767703,-0.017575978589090827,0.05590178190455526, +C6,0.3/modality_T,mae,0.674130916595459,0.6743798553943634,0.624034483730793,0.7262702912092209,1000,paired source-video group resample,0.028436601161956787,0.028045833110809326,0.014209657907485962,0.04556165635585785,C0,-0.07599282264709473,-0.07583007216453552,-0.11690436154603959,-0.03638697117567063, +C6,0.3/modality_T,rmse,0.9214409598439718,0.9204873427683381,0.8400379167952748,0.9997098646239339,1000,paired source-video group resample,,,,,C0,-0.04122837181014882,-0.04065613479393149,-0.09886239113523748,0.013788696143694504, +C6,0.3/modality_T,pearson,0.5869950652122498,0.5862540602684021,0.523573462665081,0.6453896939754485,1000,paired source-video group resample,,,,,C0,0.085232675075531,0.08576023578643799,0.0331828884780407,0.13922206461429595, +C6,0.3/modality_A,accuracy,0.6277472527472527,0.6274936061381073,0.5913263243957537,0.6658060374044125,1000,paired source-video group resample,,,,,C0,0.04120879120879117,0.040884516115117175,0.003075757575757587,0.07381024126241503, +C6,0.3/modality_A,macro_f1,0.5820769847634323,0.5805015847991882,0.5440084822865485,0.6192674913447956,1000,paired source-video group resample,,,,,C0,0.030595216103534995,0.031237881122275324,-0.010596175199939193,0.06842671617087384, +C6,0.3/modality_A,mae,0.6429431438446045,0.6420287191867828,0.5944430440664291,0.6992687627673149,1000,paired source-video group resample,-0.002751171588897705,-0.00237429141998291,-0.01085505187511444,0.0027951940894126873,C0,-0.08722388744354248,-0.08686673641204834,-0.12445124387741088,-0.05105866342782974, +C6,0.3/modality_A,rmse,0.8772780532221541,0.8751576611277194,0.8017634143802882,0.9600241747113741,1000,paired source-video group resample,,,,,C0,-0.05703430709392576,-0.05679175920312446,-0.10548947217775902,-0.009803330526180548, +C6,0.3/modality_A,pearson,0.6186560392379761,0.6195796728134155,0.5547406166791916,0.6749848484992981,1000,paired source-video group resample,,,,,C0,0.09591901302337646,0.09634986519813538,0.05307827666401863,0.1395981505513191, +C6,0.3/modality_V,accuracy,0.6263736263736264,0.6259894734643581,0.5885791966041786,0.6651886200716846,1000,paired source-video group resample,,,,,C0,0.038461538461538436,0.03786003033989904,0.003070621468926566,0.07093916137631495, +C6,0.3/modality_V,macro_f1,0.5801114274083624,0.5783745557644306,0.5418912943553472,0.6170331526735346,1000,paired source-video group resample,,,,,C0,0.029018081425513653,0.0292540160659136,-0.009461832733729653,0.06697658136855886, +C6,0.3/modality_V,mae,0.6461413502693176,0.6459362208843231,0.5985287815332413,0.7001462921500206,1000,paired source-video group resample,0.0004470348358154297,0.0005142390727996826,-0.005401884019374847,0.0051294490694999695,C0,-0.08719176054000854,-0.08700400590896606,-0.12514631897211076,-0.05133526176214219, +C6,0.3/modality_V,rmse,0.8814917956385332,0.8798036698276358,0.8041139123872819,0.9619462940352159,1000,paired source-video group resample,,,,,C0,-0.056300936674093194,-0.05582409746918093,-0.1040549030583098,-0.008669381217099712, +C6,0.3/modality_V,pearson,0.6164370775222778,0.6164411008358002,0.5565670803189278,0.6738156646490097,1000,paired source-video group resample,,,,,C0,0.09699124097824097,0.0972900390625,0.05404918044805527,0.14012451618909835, +C6,0.3/modality_TA,accuracy,0.625,0.6241655302726454,0.5885573000622668,0.660642250884246,1000,paired source-video group resample,,,,,C0,0.038461538461538436,0.03859409138406006,0.002831005177297977,0.07224269588313419, +C6,0.3/modality_TA,macro_f1,0.5712587255728624,0.5698691395095818,0.5323590529444752,0.6038990456037657,1000,paired source-video group resample,,,,,C0,0.017060438412569545,0.01662472498078793,-0.022711884041131097,0.054420093626002135, +C6,0.3/modality_TA,mae,0.6697651147842407,0.670187383890152,0.6208338081836701,0.7213385313749313,1000,paired source-video group resample,0.024070799350738525,0.023846983909606934,0.0058538451790809635,0.045036034286022174,C0,-0.1058204174041748,-0.1051415503025055,-0.1444943904876709,-0.06857624351978302, +C6,0.3/modality_TA,rmse,0.9162250271317411,0.9153266697036695,0.8363525469902777,0.9957161805236886,1000,paired source-video group resample,,,,,C0,-0.05439605922169566,-0.054342737320500545,-0.11017437424719173,-0.0003832164683653758, +C6,0.3/modality_TA,pearson,0.5906063318252563,0.5901516973972321,0.5256916761398316,0.6520752370357513,1000,paired source-video group resample,,,,,C0,0.09216636419296265,0.09167109429836273,0.04358871579170227,0.14397578686475754, +C6,0.3/modality_TV,accuracy,0.6167582417582418,0.6169925537531633,0.5810350985221675,0.6537197319249543,1000,paired source-video group resample,,,,,C0,0.03434065934065933,0.0351682779420876,0.0014008620689654769,0.06887753745419495, +C6,0.3/modality_TV,macro_f1,0.5610861796908309,0.5608667651383743,0.5264208797362971,0.5921443937586668,1000,paired source-video group resample,,,,,C0,0.01624159170197259,0.01670802533164173,-0.01922465635122295,0.052239966389992405, +C6,0.3/modality_TV,mae,0.6676788330078125,0.6663912236690521,0.6151431336998939,0.7240702927112579,1000,paired source-video group resample,0.021984517574310303,0.020958691835403442,0.0051517054438591,0.03920954465866088,C0,-0.09299492835998535,-0.09338986873626709,-0.13093894571065903,-0.05662062317132951, +C6,0.3/modality_TV,rmse,0.910910265402555,0.9075624890597285,0.8243401947038562,1.000201443229555,1000,paired source-video group resample,,,,,C0,-0.05665682540333383,-0.058437980006910084,-0.11042392432014712,-0.006589770147839186, +C6,0.3/modality_TV,pearson,0.5962815284729004,0.5972383320331573,0.5239013388752938,0.6630110517144203,1000,paired source-video group resample,,,,,C0,0.09729471802711487,0.09836281836032867,0.054229621589183805,0.14253135025501248, +C6,0.3/modality_AV,accuracy,0.6277472527472527,0.627050159830311,0.5895959718398202,0.6651886200716846,1000,paired source-video group resample,,,,,C0,0.03296703296703296,0.03293905933328678,-0.0014105870695269613,0.06630262696165234, +C6,0.3/modality_AV,macro_f1,0.5824275156133015,0.5808350406265418,0.5444558170431921,0.6184541630825702,1000,paired source-video group resample,,,,,C0,0.022729309374189377,0.02319051564606328,-0.016985076654469692,0.06278011198705867, +C6,0.3/modality_AV,mae,0.6440345048904419,0.643399566411972,0.5964700356125832,0.6978636756539345,1000,paired source-video group resample,-0.0016598105430603027,-0.001532822847366333,-0.006566190719604492,0.00272129476070404,C0,-0.09394633769989014,-0.09350568056106567,-0.13212701082229614,-0.057593864202499394, +C6,0.3/modality_AV,rmse,0.8783947282635551,0.8770855503439923,0.801676323444561,0.9574502034604403,1000,paired source-video group resample,,,,,C0,-0.06364049923803539,-0.06278108812200367,-0.1107090598798522,-0.016612702171606937, +C6,0.3/modality_AV,pearson,0.6178361773490906,0.6179757416248322,0.5569168135523797,0.6743500858545304,1000,paired source-video group resample,,,,,C0,0.10230225324630737,0.10279938578605652,0.059694726765155796,0.1464379660785198, +C6,0.3/modality_TAV,accuracy,0.6181318681318682,0.6178749445289717,0.5806824640443597,0.6549948385616792,1000,paired source-video group resample,,,,,C0,0.03708791208791207,0.038191216541112405,-0.0014164305949008222,0.07172155211298278, +C6,0.3/modality_TAV,macro_f1,0.5645068252473376,0.5628717193400414,0.5275292108204807,0.5997489646557715,1000,paired source-video group resample,,,,,C0,0.020028926643055445,0.021194411776041255,-0.02124788111828262,0.059622611100026424, +C6,0.3/modality_TAV,mae,0.6698520183563232,0.6698058843612671,0.6192029923200607,0.724491061270237,1000,paired source-video group resample,0.024157702922821045,0.024007558822631836,0.0069864243268966675,0.04378594160079956,C0,-0.10107970237731934,-0.10016906261444092,-0.14168426394462585,-0.06223095357418061, +C6,0.3/modality_TAV,rmse,0.9186802156376143,0.9170570064986323,0.8410354873843809,0.9999476575520996,1000,paired source-video group resample,,,,,C0,-0.06135754602375487,-0.06112985197671067,-0.11414218851755967,-0.0056211594291129445, +C6,0.3/modality_TAV,pearson,0.5895363092422485,0.589976966381073,0.5287614956498146,0.6467751398682594,1000,paired source-video group resample,,,,,C0,0.09922680258750916,0.0992690771818161,0.0472841814160347,0.15103637576103207, +C6,0.3/location_start_T,accuracy,0.6167582417582418,0.6169088507265522,0.5811642969955881,0.6529744807777287,1000,paired source-video group resample,,,,,C0,0.02472527472527475,0.024793388429752095,-0.00959036190044909,0.05820436507936513, +C6,0.3/location_start_T,macro_f1,0.5630930531529598,0.5623864694132854,0.526896511654482,0.5977117868179133,1000,paired source-video group resample,,,,,C0,0.0019018795846369452,0.002404119286536388,-0.036564859647661534,0.03858388312835473, +C6,0.3/location_start_T,mae,0.6697315573692322,0.6692146956920624,0.6200978130102157,0.722630287706852,1000,paired source-video group resample,0.02403724193572998,0.023980051279067993,0.009590253233909607,0.038995151221752164,C0,-0.09952962398529053,-0.09927394986152649,-0.1392791673541069,-0.05914814025163651, 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+C6,0.3/location_middle_T,mae,0.6537457704544067,0.6538122594356537,0.6037580773234368,0.7097183033823967,1000,paired source-video group resample,0.008051455020904541,0.008062958717346191,-0.005146263539791107,0.022412119805812834,C0,-0.09502160549163818,-0.09430292248725891,-0.1355411320924759,-0.056366932392120365, +C6,0.3/location_middle_T,rmse,0.8951885024346575,0.8939891146998385,0.8148063178372941,0.9757699518367421,1000,paired source-video group resample,,,,,C0,-0.06626877231615769,-0.06658546755428835,-0.11965405336734239,-0.01605529724759956, +C6,0.3/location_middle_T,pearson,0.6083921790122986,0.6078048944473267,0.5444649964570999,0.665524935722351,1000,paired source-video group resample,,,,,C0,0.10143786668777466,0.10152620077133179,0.053575101494789126,0.1519623890519142, +C6,0.3/location_end_T,accuracy,0.625,0.6254348565823975,0.5874092754336326,0.6634845890410959,1000,paired source-video group resample,,,,,C0,0.050824175824175866,0.050365664869481686,0.01648929633543888,0.08462509115346674, +C6,0.3/location_end_T,macro_f1,0.5562085911377285,0.5551379873999863,0.5191472268777609,0.5922006498708696,1000,paired source-video group resample,,,,,C0,0.018240417207835424,0.01818370692305582,-0.020892007767074346,0.055431973147563735, +C6,0.3/location_end_T,mae,0.6745095252990723,0.6740392446517944,0.6260750144720078,0.7238674178719521,1000,paired source-video group resample,0.02881520986557007,0.028958261013031006,0.008033794164657593,0.04819838404655456,C0,-0.09464335441589355,-0.09462490677833557,-0.13237669914960862,-0.05704405009746552, +C6,0.3/location_end_T,rmse,0.8992605005774826,0.8972597505664551,0.8289509676385216,0.9730926771856521,1000,paired source-video group resample,,,,,C0,-0.0782720681505581,-0.0787490250059184,-0.125716532985795,-0.03221546284618134, 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resample,0.022449791431427002,0.02245423197746277,0.0056373879313468935,0.03842308819293975,C0,-0.0809774398803711,-0.08076784014701843,-0.1206509679555893,-0.04611796438694003, +C6,0.3/span_long_T,rmse,0.9086276139093036,0.9048026133416189,0.8221100238653865,0.9956057541039997,1000,paired source-video group resample,,,,,C0,-0.055270307115566575,-0.05565289768059728,-0.10489994795855687,-0.009599541222743518, +C6,0.3/span_long_T,pearson,0.5969615578651428,0.5995026230812073,0.5257020503282547,0.6632452338933944,1000,paired source-video group resample,,,,,C0,0.0969824492931366,0.09806644916534424,0.05905146896839142,0.13904166743159294, +C6,0.3/span_multi_short_T,accuracy,0.625,0.6248246789140617,0.5885732278237424,0.6642370907338426,1000,paired source-video group resample,,,,,C0,0.03708791208791207,0.03682894874329856,0.0030062880171589676,0.0710546312995198, +C6,0.3/span_multi_short_T,macro_f1,0.5734627561049472,0.5723714821808398,0.5348474803587793,0.6091247873590263,1000,paired source-video group resample,,,,,C0,0.021918300818328906,0.022561137640612072,-0.017008446912909772,0.05968873870881561, +C6,0.3/span_multi_short_T,mae,0.6622699499130249,0.6622036099433899,0.6120727613568306,0.7194575071334839,1000,paired source-video group resample,0.016575634479522705,0.016662389039993286,-0.0005772888660430908,0.032746605575084686,C0,-0.08918559551239014,-0.08907049894332886,-0.12561431527137756,-0.052297250926494614, +C6,0.3/span_multi_short_T,rmse,0.9026666699204757,0.899955131092832,0.8172624870193373,0.9908337564962474,1000,paired source-video group resample,,,,,C0,-0.05803143575990577,-0.057758164446329974,-0.11548100410623403,-0.006992686369865819, +C6,0.3/span_multi_short_T,pearson,0.6045829653739929,0.6058533787727356,0.5354982763528824,0.6677784398198128,1000,paired source-video group resample,,,,,C0,0.10297441482543945,0.10244110226631165,0.05790445804595947,0.1529974803328514, +C6,0.3/location_start_A,accuracy,0.6263736263736264,0.6261474305946857,0.5910260254257615,0.6635144686549427,1000,paired source-video group resample,,,,,C0,0.04258241758241754,0.04305331366476417,0.008348596942202783,0.07334689322344573, +C6,0.3/location_start_A,macro_f1,0.5822810461090445,0.5804615314426376,0.5457431034411657,0.6193909902931826,1000,paired source-video group resample,,,,,C0,0.0255008857118173,0.025828462262441287,-0.01141776708045258,0.060117231840750227, +C6,0.3/location_start_A,mae,0.6407381296157837,0.6395685970783234,0.5927989259362221,0.697523845732212,1000,paired source-video group resample,-0.004956185817718506,-0.004536658525466919,-0.01306808590888977,0.0012655541300773602,C0,-0.09426021575927734,-0.09400171041488647,-0.1308790385723114,-0.0588141143321991, +C6,0.3/location_start_A,rmse,0.8753569419879731,0.8731083517588158,0.7998034647296276,0.9584680468708445,1000,paired source-video group resample,,,,,C0,-0.06544040570669452,-0.06517753278545824,-0.11318354494846775,-0.021595639945902353, +C6,0.3/location_start_A,pearson,0.6183470487594604,0.6192584037780762,0.5548990905284882,0.6732761234045028,1000,paired source-video group resample,,,,,C0,0.10060340166091919,0.10024186968803406,0.06040736436843872,0.14479999393224713, +C6,0.3/location_middle_A,accuracy,0.6263736263736264,0.6259428220384295,0.5907634511738376,0.6630975840747452,1000,paired source-video group resample,,,,,C0,0.039835164835164805,0.039548022598870025,0.0031134483610443246,0.07444188807498912, +C6,0.3/location_middle_A,macro_f1,0.5803686714237174,0.5791860782731915,0.5420682039517328,0.6162126516306562,1000,paired source-video group resample,,,,,C0,0.026605848095676676,0.026481842544015533,-0.014254841452366622,0.0649649783580656, +C6,0.3/location_middle_A,mae,0.6436693668365479,0.6424140930175781,0.5959177881479263,0.7000736773014068,1000,paired source-video group resample,-0.0020249485969543457,-0.0017113685607910156,-0.010459867119789124,0.0036244347691535947,C0,-0.09035390615463257,-0.08965641260147095,-0.12792567312717437,-0.054750975966453556, +C6,0.3/location_middle_A,rmse,0.8773783988598758,0.8756893541884597,0.8024147873499543,0.9598121841270664,1000,paired source-video group resample,,,,,C0,-0.059400536793762226,-0.05922375115504125,-0.10745562288745071,-0.014227317311029912, +C6,0.3/location_middle_A,pearson,0.6178179979324341,0.6187210381031036,0.5540397584438324,0.6734627604484558,1000,paired source-video group resample,,,,,C0,0.09745675325393677,0.09821738302707672,0.05371025651693344,0.14106079488992687, +C6,0.3/location_end_A,accuracy,0.6263736263736264,0.6259630702818945,0.589224194646976,0.6641825253141908,1000,paired source-video group resample,,,,,C0,0.03708791208791207,0.036610186318959514,0.0026896494477842135,0.0696776441497133, +C6,0.3/location_end_A,macro_f1,0.5801114274083624,0.5785240057958365,0.5422223679266986,0.6160757043061501,1000,paired source-video group resample,,,,,C0,0.026712266143303687,0.026937487819835182,-0.012524339204842746,0.0643080569909302, +C6,0.3/location_end_A,mae,0.6450269222259521,0.6441437602043152,0.5967930182814598,0.7004678905010223,1000,paired source-video group resample,-0.0006673932075500488,-0.0006645917892456055,-0.0015774354338645934,0.00022386014461517307,C0,-0.08972001075744629,-0.08944782614707947,-0.12781268656253814,-0.0532892018556595, +C6,0.3/location_end_A,rmse,0.8800981704724973,0.8779094892040946,0.8020415332243113,0.9625747149978905,1000,paired source-video group resample,,,,,C0,-0.057571250355895165,-0.056800335861386386,-0.10634311531412093,-0.012361970207659891, +C6,0.3/location_end_A,pearson,0.6157169342041016,0.6156943142414093,0.5529745221138,0.6724657520651818,1000,paired source-video group resample,,,,,C0,0.09676557779312134,0.09693950414657593,0.05332833528518677,0.14077749550342558, +C6,0.3/span_long_A,accuracy,0.6291208791208791,0.6283929194617861,0.5918814645430616,0.6671514026600093,1000,paired source-video group resample,,,,,C0,0.04120879120879117,0.04116396679561568,0.006993902721750777,0.07377554457668983, +C6,0.3/span_long_A,macro_f1,0.5836016917842176,0.5820494569617948,0.5454275300534668,0.6197315492943145,1000,paired source-video group resample,,,,,C0,0.029264411131147527,0.029192928599056867,-0.01238968636466359,0.06767121697427494, +C6,0.3/span_long_A,mae,0.6432492733001709,0.6422156393527985,0.5947573840618133,0.6994073212146759,1000,paired source-video group resample,-0.002445042133331299,-0.0019661784172058105,-0.010797402262687683,0.0035579964518547037,C0,-0.09340959787368774,-0.0930408239364624,-0.13143193423748017,-0.056802850961685185, +C6,0.3/span_long_A,rmse,0.8773370934469101,0.8756287731766027,0.8013371933938913,0.9606119475339803,1000,paired source-video group resample,,,,,C0,-0.06061598310645244,-0.060435780769780734,-0.10919591161942017,-0.013393170710485734, +C6,0.3/span_long_A,pearson,0.6186637282371521,0.6193471550941467,0.5553623005747795,0.6747015178203583,1000,paired source-video group resample,,,,,C0,0.10113382339477539,0.1011018455028534,0.059654292464256284,0.1466599628329277, +C6,0.3/span_multi_short_A,accuracy,0.6263736263736264,0.6259547681852,0.5897027908273806,0.6643173929998079,1000,paired source-video group resample,,,,,C0,0.03159340659340659,0.031683059422430326,-0.004250818110774551,0.06491937178576077, +C6,0.3/span_multi_short_A,macro_f1,0.5804473956793094,0.5784961116162142,0.5431878530214753,0.6171812334650527,1000,paired source-video group resample,,,,,C0,0.02016956009530102,0.020466082454586476,-0.020576945535528728,0.059198169435769596, +C6,0.3/span_multi_short_A,mae,0.6447508931159973,0.6437675058841705,0.5970920592546463,0.7014265656471252,1000,paired source-video group resample,-0.0009434223175048828,-0.0006857812404632568,-0.00711698979139328,0.003734245896339416,C0,-0.09137314558029175,-0.09123566746711731,-0.1290975570678711,-0.054182834923267365, +C6,0.3/span_multi_short_A,rmse,0.878715358773034,0.8768506027978382,0.8025192295810635,0.962111240106276,1000,paired source-video group resample,,,,,C0,-0.06293079087226416,-0.06283093675256318,-0.11163518348251349,-0.016181484578595254, +C6,0.3/span_multi_short_A,pearson,0.6178956031799316,0.618665337562561,0.5553520858287812,0.6731756642460823,1000,paired source-video group resample,,,,,C0,0.10159522294998169,0.10215967893600464,0.05833812952041626,0.14657608941197395, +C6,0.3/location_start_V,accuracy,0.6277472527472527,0.6271783820403205,0.5912024171333896,0.6652900893095175,1000,paired source-video group resample,,,,,C0,0.03159340659340659,0.03151179840922558,-0.0037450497157578274,0.06374837467782765, +C6,0.3/location_start_V,macro_f1,0.5857335884482785,0.5836563370331576,0.5488292874560496,0.6222248194725433,1000,paired source-video group resample,,,,,C0,0.021922914678318195,0.022066992526533602,-0.017077412172006794,0.057710504366834794, +C6,0.3/location_start_V,mae,0.6427589654922485,0.6417631506919861,0.5944004610180855,0.6982526466250419,1000,paired source-video group resample,-0.002935349941253662,-0.0026719272136688232,-0.010365691781044007,0.0037300541996955865,C0,-0.09068745374679565,-0.09000760316848755,-0.12714000344276427,-0.05365794301033021, +C6,0.3/location_start_V,rmse,0.8790809966255867,0.8775307127425118,0.8018118995909784,0.9622773803341302,1000,paired source-video group resample,,,,,C0,-0.05776032344562332,-0.05645125017313313,-0.1058436852424995,-0.00789667713425235, +C6,0.3/location_start_V,pearson,0.6176730394363403,0.6184651851654053,0.555501563847065,0.6733982369303703,1000,paired source-video group resample,,,,,C0,0.09663259983062744,0.09626996517181396,0.053830135613679886,0.13936344385147093, +C6,0.3/location_middle_V,accuracy,0.6277472527472527,0.6271379267155601,0.592486036748489,0.6648030010126116,1000,paired source-video group resample,,,,,C0,0.0357142857142857,0.035293554011439965,0.0015357476029149997,0.06779722161078097, +C6,0.3/location_middle_V,macro_f1,0.5826038909733023,0.5810581458513244,0.5449894973749505,0.6183400327614881,1000,paired source-video group resample,,,,,C0,0.0268949119368862,0.027397922245720574,-0.012124924349284612,0.06272634351636101, +C6,0.3/location_middle_V,mae,0.6448013782501221,0.6434501707553864,0.5972618579864502,0.7008282333612442,1000,paired source-video group resample,-0.000892937183380127,-0.0005768239498138428,-0.007867692410945893,0.005701729655265807,C0,-0.08900868892669678,-0.0884561836719513,-0.12817552387714387,-0.05207866877317429, +C6,0.3/location_middle_V,rmse,0.880420516282954,0.8785840099492486,0.803051689591502,0.962450669608429,1000,paired source-video group resample,,,,,C0,-0.05846069002563892,-0.05798477838553767,-0.10892254807567778,-0.010000244887873662, +C6,0.3/location_middle_V,pearson,0.6177749633789062,0.6182215511798859,0.5543897047638893,0.673091122508049,1000,paired source-video group resample,,,,,C0,0.0987514853477478,0.09847578406333923,0.05571479946374893,0.14450727701187133, +C6,0.3/location_end_V,accuracy,0.6263736263736264,0.6259630702818945,0.589224194646976,0.6641825253141908,1000,paired source-video group resample,,,,,C0,0.03708791208791207,0.03671521288622648,0.0015345690088767738,0.07096891070593732, +C6,0.3/location_end_V,macro_f1,0.5801906992539759,0.5786427252163182,0.5422533318806465,0.6160757043061501,1000,paired source-video group resample,,,,,C0,0.02691430438330411,0.02756262163464207,-0.012230419164828699,0.06580898101849594, 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resample,,,,,C0,0.038461538461538436,0.03846153846153855,0.0027893031549748896,0.07057379238228491, +C6,0.3/span_long_V,macro_f1,0.577936604681967,0.5759241160271482,0.5403604779030109,0.6155869346789644,1000,paired source-video group resample,,,,,C0,0.0293230879138503,0.02948280076674087,-0.008437343726181204,0.06716602211827032, +C6,0.3/span_long_V,mae,0.6484933495521545,0.6475788056850433,0.5998246893286705,0.704801370203495,1000,paired source-video group resample,0.0027990341186523438,0.0026989877223968506,-0.00021813809871673584,0.006608706712722777,C0,-0.08586496114730835,-0.08576786518096924,-0.1234629288315773,-0.0486878275871277, +C6,0.3/span_long_V,rmse,0.8850554608354086,0.8830367097387846,0.80689614884601,0.9675284307842917,1000,paired source-video group resample,,,,,C0,-0.05277667688322529,-0.0517153738854072,-0.1010313590273741,-0.006700434127836959, +C6,0.3/span_long_V,pearson,0.6139591336250305,0.6138617992401123,0.5513479113578796,0.6718905806541443,1000,paired source-video group resample,,,,,C0,0.09407854080200195,0.09467889368534088,0.050898519158363346,0.13937990963459015, +C6,0.3/span_multi_short_V,accuracy,0.6263736263736264,0.6257730482916588,0.5906997453034336,0.6632730225440562,1000,paired source-video group resample,,,,,C0,0.038461538461538436,0.03809477915814874,0.002778066492052234,0.07100613154960984, +C6,0.3/span_multi_short_V,macro_f1,0.5814246312735377,0.5797668611319866,0.5441278917509118,0.6169999313888135,1000,paired source-video group resample,,,,,C0,0.029965313442629538,0.029660573816730984,-0.008821305059519861,0.06613104929008726, +C6,0.3/span_multi_short_V,mae,0.6450521349906921,0.6440041363239288,0.5967062428593636,0.7017460688948631,1000,paired source-video group resample,-0.0006421804428100586,-0.00019925832748413086,-0.007709889113903046,0.004703545570373534,C0,-0.08855080604553223,-0.08813515305519104,-0.12654874324798585,-0.05134578347206116, 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+C6,0.3/synchrony_sync,mae,0.662735641002655,0.6618986129760742,0.6144693955779076,0.7188853800296784,1000,paired source-video group resample,0.017041325569152832,0.017226606607437134,-3.795772790908812e-05,0.03561826199293137,C0,-0.08020496368408203,-0.08078503608703613,-0.12018557339906692,-0.04116202890872956, +C6,0.3/synchrony_sync,rmse,0.9098049025944585,0.9073012270656916,0.8268487078614839,0.9992487426152489,1000,paired source-video group resample,,,,,C0,-0.041588308757374626,-0.04126899521474653,-0.09541085327093726,0.016829678137756, +C6,0.3/synchrony_sync,pearson,0.5976772904396057,0.5984918773174286,0.526031206548214,0.658443297445774,1000,paired source-video group resample,,,,,C0,0.0827527642250061,0.08296534419059753,0.03665900155901909,0.13172163516283034, +C6,0.3/synchrony_partial,accuracy,0.6304945054945055,0.630185710305037,0.5965799825174825,0.6657941834451901,1000,paired source-video group resample,,,,,C0,0.038461538461538436,0.03885447304719014,0.003683601994567838,0.0744895189922669, +C6,0.3/synchrony_partial,macro_f1,0.5752769201126008,0.57448665069773,0.5392919347706002,0.6108259845222833,1000,paired source-video group resample,,,,,C0,0.018427992836299922,0.018887515713677194,-0.020479522120186482,0.05923198967338149, +C6,0.3/synchrony_partial,mae,0.6528188586235046,0.6517576575279236,0.6048992693424224,0.7048935711383819,1000,paired source-video group resample,0.007124543190002441,0.007038861513137817,-0.006332166492938995,0.018878442049026486,C0,-0.10213619470596313,-0.10149145126342773,-0.1422506496310234,-0.06324922293424606, +C6,0.3/synchrony_partial,rmse,0.879726417182059,0.8778029432719581,0.8043737712592558,0.9584197837949611,1000,paired source-video group resample,,,,,C0,-0.07402158192463282,-0.07281670567692933,-0.12354901117231318,-0.02587380519968785, +C6,0.3/synchrony_partial,pearson,0.6211951375007629,0.6225436627864838,0.5615370526909829,0.6779387801885605,1000,paired source-video group resample,,,,,C0,0.11345088481903076,0.11378061771392822,0.0685364544391632,0.15837328657507893, +C6,0.3/synchrony_async,accuracy,0.6291208791208791,0.6289297199780375,0.5900531118756144,0.6666903409090909,1000,paired source-video group resample,,,,,C0,0.03434065934065933,0.03466666666666662,0.0037323667711598734,0.06594516594516592, +C6,0.3/synchrony_async,macro_f1,0.5739935955170545,0.573530574832765,0.5370719669837585,0.6083638547370949,1000,paired source-video group resample,,,,,C0,0.016643850381268255,0.017554400718615526,-0.019465206264462857,0.05301971637013987, +C6,0.3/synchrony_async,mae,0.6543288826942444,0.6540375351905823,0.6062479972839355,0.7054497674107552,1000,paired source-video group resample,0.008634567260742188,0.00873112678527832,-0.00905131697654724,0.025604544579982753,C0,-0.1028938889503479,-0.10244420170783997,-0.14450427740812302,-0.06240424066781998, +C6,0.3/synchrony_async,rmse,0.8883779186299061,0.8865692577744952,0.8131770153788133,0.9668810642946492,1000,paired source-video group resample,,,,,C0,-0.07871246625765016,-0.0784705245113636,-0.13011606301745568,-0.02616882407280587, +C6,0.3/synchrony_async,pearson,0.6126687526702881,0.6129338443279266,0.5493811890482903,0.6694739609956741,1000,paired source-video group resample,,,,,C0,0.11495152115821838,0.11435423791408539,0.06534649953246117,0.16202457696199413, +C6_no_distance,0.0/none,accuracy,0.603021978021978,0.6026398637489678,0.5629858868708681,0.6467321135054098,1000,paired source-video group resample,,,,,C0,0.01098901098901095,0.01121238312249545,-0.024121689742422667,0.045231841023298275, +C6_no_distance,0.0/none,macro_f1,0.5116790727202128,0.5111355548586748,0.4771675587600533,0.5498540110001322,1000,paired source-video group resample,,,,,C0,-0.044255539930817656,-0.044406049624162114,-0.0823280409524628,-0.005901193471080078, +C6_no_distance,0.0/none,mae,0.6800156831741333,0.679791271686554,0.6284376338124276,0.7366678848862648,1000,paired source-video group resample,,,,,C0,-0.0533982515335083,-0.05340498685836792,-0.09015405923128128,-0.0167528972029686, +C6_no_distance,0.0/none,rmse,0.9099615977641681,0.9087595393821658,0.8279058903095865,0.9930199615427608,1000,paired source-video group resample,,,,,C0,-0.027212061664022125,-0.027149598725818402,-0.07706640711833511,0.018820655870517577, +C6_no_distance,0.0/none,pearson,0.6044881939888,0.6050049364566803,0.5491477966308593,0.65861576795578,1000,paired source-video group resample,,,,,C0,0.08524560928344727,0.0852268636226654,0.042877747863531115,0.12974787726998327, +C6_no_distance,0.1/single,accuracy,0.6071428571428571,0.6065024752039181,0.5668121091358677,0.6495400023587016,1000,paired source-video group resample,,,,,C0,0.019230769230769162,0.01976014502858736,-0.013932494531262307,0.05228494775327803, +C6_no_distance,0.1/single,macro_f1,0.5188380787823315,0.5187466972660757,0.4848071570047238,0.5562138892529092,1000,paired source-video group resample,,,,,C0,-0.031046718654574867,-0.03064924121595769,-0.06932797456383316,0.007746766956152223, +C6_no_distance,0.1/single,mae,0.6758347153663635,0.6756636798381805,0.6257632166147232,0.7308130741119384,1000,paired source-video group resample,-0.004180967807769775,-0.0037625133991241455,-0.0138916477560997,0.001191940903663635,C0,-0.05992448329925537,-0.0596260130405426,-0.09565144777297974,-0.02263298183679581, +C6_no_distance,0.1/single,rmse,0.9008190600358085,0.8987650215977944,0.8246575130102111,0.9768800416700936,1000,paired source-video group resample,,,,,C0,-0.038503515525438736,-0.03869428958381371,-0.08788922934913761,0.008061739161538373, +C6_no_distance,0.1/single,pearson,0.61191326379776,0.6117317378520966,0.5582579255104065,0.6675219759345055,1000,paired source-video group resample,,,,,C0,0.09533774852752686,0.09623894095420837,0.053429582715034486,0.1412968933582306, +C6_no_distance,0.1/sync,accuracy,0.603021978021978,0.6022727272727273,0.5647062401540347,0.6474630357988274,1000,paired source-video group resample,,,,,C0,0.016483516483516425,0.016713091922005652,-0.018252233669630608,0.05000470514429113, +C6_no_distance,0.1/sync,macro_f1,0.5063580320817459,0.5058935812626986,0.47248709741994416,0.5444114357425678,1000,paired source-video group resample,,,,,C0,-0.04397003101300734,-0.04429281045188027,-0.08226673415387341,-0.005258641019756175, +C6_no_distance,0.1/sync,mae,0.6779942512512207,0.6773664355278015,0.6281680479645729,0.7329886421561241,1000,paired source-video group resample,-0.0020214319229125977,-0.0016721487045288086,-0.01371619701385498,0.006817200779914854,C0,-0.05704861879348755,-0.056878089904785156,-0.09247958958148957,-0.021137613058090213, +C6_no_distance,0.1/sync,rmse,0.9005527309036382,0.8981926123428694,0.8215579103680524,0.9763091742324822,1000,paired source-video group resample,,,,,C0,-0.04463053345164847,-0.04499605061631362,-0.09291212447581322,0.0010276825908552855, +C6_no_distance,0.1/sync,pearson,0.6123272776603699,0.612120658159256,0.5576306879520416,0.6673717468976974,1000,paired source-video group resample,,,,,C0,0.09892743825912476,0.09989219903945923,0.05922408401966095,0.14198051914572715, +C6_no_distance,0.1/partial,accuracy,0.6016483516483516,0.6008970614198779,0.562747187303371,0.6442367361079385,1000,paired source-video group resample,,,,,C0,0.008241758241758212,0.00867701187886899,-0.025176590590335324,0.040193822500301554, +C6_no_distance,0.1/partial,macro_f1,0.5102185746939096,0.5092360229882631,0.4742622319030099,0.5458408556164271,1000,paired source-video group resample,,,,,C0,-0.047414363309395635,-0.047543646081052215,-0.08375181088382405,-0.007867761540580751, +C6_no_distance,0.1/partial,mae,0.6817261576652527,0.6817091405391693,0.6329559579491615,0.7377650216221809,1000,paired source-video group resample,0.0017104744911193848,0.001922607421875,-0.009544441103935241,0.01095788925886154,C0,-0.05349123477935791,-0.052975088357925415,-0.09279899895191193,-0.015948261320590983, +C6_no_distance,0.1/partial,rmse,0.9068343153279091,0.9049704644765035,0.8286021421699121,0.9832478121696989,1000,paired source-video group resample,,,,,C0,-0.030609130079302882,-0.0311065158616477,-0.08195484491447855,0.016517407130563707, +C6_no_distance,0.1/partial,pearson,0.607669472694397,0.6077494323253632,0.5530281871557235,0.6606232821941376,1000,paired source-video group resample,,,,,C0,0.08709591627120972,0.08826461434364319,0.04404052346944809,0.13424870669841765, +C6_no_distance,0.1/async,accuracy,0.603021978021978,0.6026365839294852,0.5617906997824511,0.6468160382330497,1000,paired source-video group resample,,,,,C0,0.01098901098901095,0.011683571902550038,-0.025117933928864595,0.04687878198478561, +C6_no_distance,0.1/async,macro_f1,0.5083962041297005,0.5081892343498254,0.47162999747050555,0.5445756362781621,1000,paired source-video group resample,,,,,C0,-0.05041081774970657,-0.04981456414297544,-0.08945431923270224,-0.009426876096510144, +C6_no_distance,0.1/async,mae,0.6788546442985535,0.6791621446609497,0.6286556139588356,0.735005946457386,1000,paired source-video group resample,-0.001161038875579834,-0.0009022951126098633,-0.009246018528938292,0.006611303985118864,C0,-0.060038983821868896,-0.05975353717803955,-0.09712189584970474,-0.024268282949924485, +C6_no_distance,0.1/async,rmse,0.9037274736944789,0.9025031603497066,0.8237456788060223,0.9828259190431333,1000,paired source-video group resample,,,,,C0,-0.04000716760304546,-0.03942837671280697,-0.08869576784173334,0.007195491127335183, +C6_no_distance,0.1/async,pearson,0.609045147895813,0.6087323725223541,0.5553692549467086,0.6631106823682784,1000,paired source-video group resample,,,,,C0,0.09502917528152466,0.09542733430862427,0.05113050937652588,0.14252619594335555, +C6_no_distance,0.3/single,accuracy,0.6016483516483516,0.6010931001784501,0.5635266614529462,0.6426783240997229,1000,paired source-video group resample,,,,,C0,-0.004120879120879106,-0.004357319157015371,-0.03709494448003414,0.026287672745446737, +C6_no_distance,0.3/single,macro_f1,0.5104171172143991,0.5097364382565918,0.4752482787226155,0.5461952677702288,1000,paired source-video group resample,,,,,C0,-0.05888213219404914,-0.059110845363387454,-0.09865743264760428,-0.020383790465546163, +C6_no_distance,0.3/single,mae,0.6842509508132935,0.684078574180603,0.6324597015976906,0.7382100984454155,1000,paired source-video group resample,0.004235267639160156,0.0042663514614105225,-0.0043605402112007145,0.012982231378555297,C0,-0.04688018560409546,-0.046760350465774536,-0.08550285249948501,-0.009069225192070008, +C6_no_distance,0.3/single,rmse,0.9118921646165563,0.9105014711226871,0.8307105626390858,0.9911086559668894,1000,paired source-video group resample,,,,,C0,-0.027875410116988575,-0.027532397112620066,-0.08062306254734868,0.02163658217946041, +C6_no_distance,0.3/single,pearson,0.6017282605171204,0.6026300489902496,0.5477945238351822,0.6576978951692581,1000,paired source-video group resample,,,,,C0,0.08031266927719116,0.0804678201675415,0.03561806082725525,0.12729103937745095, +C6_no_distance,0.3/sync,accuracy,0.6002747252747253,0.5997170579630975,0.5590393591357248,0.640964186135116,1000,paired source-video group resample,,,,,C0,0.02060439560439553,0.020833368654664175,-0.011552245028498305,0.0546271538918598, +C6_no_distance,0.3/sync,macro_f1,0.5078592967988163,0.5069371918044316,0.47362651589014615,0.5439042053222863,1000,paired source-video group resample,,,,,C0,-0.03224169264067156,-0.03187425079701656,-0.07046573985341419,0.00842179809485205, +C6_no_distance,0.3/sync,mae,0.6915753483772278,0.6914781033992767,0.6402065277099609,0.7491971671581268,1000,paired source-video group resample,0.011559665203094482,0.011315405368804932,0.0006261348724365235,0.022852244973182674,C0,-0.061328351497650146,-0.061937808990478516,-0.0990903615951538,-0.02607672065496445, +C6_no_distance,0.3/sync,rmse,0.9221619304963045,0.9203861092045048,0.8437086533126685,1.004368628715088,1000,paired source-video group resample,,,,,C0,-0.04013078526797287,-0.04120258575130137,-0.09074930892147691,0.009478599018470073, +C6_no_distance,0.3/sync,pearson,0.5919369459152222,0.593182772397995,0.5368838891386986,0.6459000706672668,1000,paired source-video group resample,,,,,C0,0.09370201826095581,0.09424459934234619,0.05233248025178909,0.1366196550428867, +C6_no_distance,0.3/partial,accuracy,0.6002747252747253,0.6006006344539615,0.5621542969373743,0.6414847883597884,1000,paired source-video group resample,,,,,C0,0.005494505494505475,0.005468238987833829,-0.028537839500747113,0.04090012987352256, +C6_no_distance,0.3/partial,macro_f1,0.5035969855838348,0.5029597082064474,0.47069334981440397,0.5369584983785787,1000,paired source-video group resample,,,,,C0,-0.05963866205963453,-0.05942528306499806,-0.09713489788361351,-0.02182431442059757, +C6_no_distance,0.3/partial,mae,0.6867015361785889,0.6866210401058197,0.6335279956459999,0.7448189347982406,1000,paired source-video group resample,0.006685853004455566,0.006714910268783569,-0.005245634913444519,0.018911044299602504,C0,-0.05985015630722046,-0.060145288705825806,-0.09811316430568695,-0.02081519365310669, +C6_no_distance,0.3/partial,rmse,0.9168567496513598,0.9161602136896481,0.8340994156936492,0.9972924728280642,1000,paired source-video group resample,,,,,C0,-0.03594144361261631,-0.03643219127773584,-0.08945212631806747,0.015263885270606318, +C6_no_distance,0.3/partial,pearson,0.5981215238571167,0.5985745489597321,0.5406485006213189,0.6549313783645629,1000,paired source-video group resample,,,,,C0,0.08940774202346802,0.08939002454280853,0.04618964791297913,0.136671644449234, +C6_no_distance,0.3/async,accuracy,0.5865384615384616,0.5858582743444707,0.546802797870777,0.6269580978309117,1000,paired source-video group resample,,,,,C0,0.006868131868131844,0.006418654472047092,-0.029854151666699184,0.04688169642857142, +C6_no_distance,0.3/async,macro_f1,0.4937375742619148,0.4929350192056887,0.46034326695739725,0.5265616624598534,1000,paired source-video group resample,,,,,C0,-0.05241289628676016,-0.052573200487035704,-0.09388482339956247,-0.007732643567813278, +C6_no_distance,0.3/async,mae,0.7048642635345459,0.7043125927448273,0.6484320372343063,0.7668754935264587,1000,paired source-video group resample,0.024848580360412598,0.024382323026657104,0.00980701893568039,0.04157221615314483,C0,-0.06371915340423584,-0.06345507502555847,-0.10368645489215851,-0.023354734480381015, +C6_no_distance,0.3/async,rmse,0.9449383334066542,0.9428827722484002,0.8592292097899129,1.0372603288523237,1000,paired source-video group resample,,,,,C0,-0.0381664611492758,-0.037583216661503216,-0.09480661288512783,0.01691645778017849, +C6_no_distance,0.3/async,pearson,0.5716733932495117,0.5736545920372009,0.49693788066506384,0.6415420830249786,1000,paired source-video group resample,,,,,C0,0.08482745289802551,0.08424031734466553,0.039307430386543274,0.1361108511686325, +C6_no_distance,0.5/single,accuracy,0.5975274725274725,0.5972378338427426,0.555971153436221,0.6397290452947042,1000,paired source-video group resample,,,,,C0,0.01098901098901095,0.011347517730496415,-0.0287005171451374,0.046674866790519125, +C6_no_distance,0.5/single,macro_f1,0.5034451788004649,0.5026727760051062,0.46864860697094857,0.5378941666456194,1000,paired source-video group resample,,,,,C0,-0.05157210336141804,-0.051087530458785974,-0.09196765537192808,-0.012880937993765927, +C6_no_distance,0.5/single,mae,0.6825225949287415,0.6822837293148041,0.6319397255778313,0.73894761800766,1000,paired source-video group resample,0.0025069117546081543,0.0025321543216705322,-0.006622087955474853,0.012626881897449493,C0,-0.06650573015213013,-0.0665358304977417,-0.10445470362901688,-0.031015312671661386, +C6_no_distance,0.5/single,rmse,0.9092156457397311,0.9081326855698024,0.8313727144561734,0.9878781284743168,1000,paired source-video group resample,,,,,C0,-0.050435191772802423,-0.05056573020012162,-0.0993294352046299,-0.00574766673958739, +C6_no_distance,0.5/single,pearson,0.6047633290290833,0.6054808497428894,0.5493793025612831,0.6608808696269989,1000,paired source-video group resample,,,,,C0,0.09653007984161377,0.09685501456260681,0.05430091023445129,0.14254063218832017, +C6_no_distance,0.5/sync,accuracy,0.6002747252747253,0.6005876566221393,0.5631486630067278,0.6386471404041738,1000,paired source-video group resample,,,,,C0,0.006868131868131844,0.006956542779713526,-0.02896069153617585,0.03905357467709659, +C6_no_distance,0.5/sync,macro_f1,0.5037948026643373,0.5022730330456028,0.47268752396152103,0.5343634112983572,1000,paired source-video group resample,,,,,C0,-0.05970873673184618,-0.06027665417895223,-0.09706496610510072,-0.02296598239969296, +C6_no_distance,0.5/sync,mae,0.6847909688949585,0.6839244365692139,0.6336637765169144,0.7351895317435264,1000,paired source-video group resample,0.004775285720825195,0.004725426435470581,-0.018620078265666962,0.026213394105434416,C0,-0.10250329971313477,-0.10376611351966858,-0.1427326485514641,-0.06500558257102967, +C6_no_distance,0.5/sync,rmse,0.8960111944189016,0.8952923931987009,0.8203415772561824,0.9672248185749626,1000,paired source-video group resample,,,,,C0,-0.10636034450728682,-0.10721847406190732,-0.16072841996634207,-0.059465181866464795, +C6_no_distance,0.5/sync,pearson,0.61216139793396,0.6127872169017792,0.5551311656832695,0.6656348183751106,1000,paired source-video group resample,,,,,C0,0.13250312209129333,0.13345970213413239,0.09146784022450447,0.17776883617043496, +C6_no_distance,0.5/partial,accuracy,0.5989010989010989,0.5991501416430595,0.5596158694145081,0.6371776603477518,1000,paired source-video group resample,,,,,C0,0.013736263736263687,0.014174351556064557,-0.021768756849619382,0.04740784670285347, +C6_no_distance,0.5/partial,macro_f1,0.5050668816026986,0.5022674136740581,0.469538339902314,0.5377502583840961,1000,paired source-video group resample,,,,,C0,-0.046529349136732456,-0.0467916407815423,-0.08805230075448242,-0.007345109010310534, +C6_no_distance,0.5/partial,mae,0.6986975073814392,0.6981326639652252,0.644594968855381,0.7553542017936706,1000,paired source-video group resample,0.018681824207305908,0.018660277128219604,9.562969207763676e-05,0.03577067703008651,C0,-0.08676159381866455,-0.08740514516830444,-0.12710451185703278,-0.04766393899917603, +C6_no_distance,0.5/partial,rmse,0.9324403285552503,0.9309198558154381,0.8504106189831045,1.0144435994949226,1000,paired source-video group resample,,,,,C0,-0.06717046678119853,-0.06875724053492022,-0.1241882849121136,-0.01657788359516037, +C6_no_distance,0.5/partial,pearson,0.579910933971405,0.5802221298217773,0.5142928302288056,0.6426989540457725,1000,paired source-video group resample,,,,,C0,0.09850531816482544,0.10009738802909851,0.051431185007095336,0.15068632438778876, +C6_no_distance,0.5/async,accuracy,0.5961538461538461,0.5966440699991337,0.5563066533720087,0.63729632201453,1000,paired source-video group resample,,,,,C0,0.02335164835164838,0.023337631755999122,-0.014380242311276803,0.060996940072089896, +C6_no_distance,0.5/async,macro_f1,0.49672251941318407,0.496013355847769,0.4620192333636321,0.5316091915409743,1000,paired source-video group resample,,,,,C0,-0.043925477021342696,-0.044034467811644884,-0.08326437990236261,-0.0012564103966166927, +C6_no_distance,0.5/async,mae,0.6976437568664551,0.6977263689041138,0.6461130276322364,0.7518456816673278,1000,paired source-video group resample,0.017628073692321777,0.01752912998199463,-0.0025043621659278864,0.036573633551597595,C0,-0.09562093019485474,-0.09465107321739197,-0.1374524787068367,-0.052634289860725415, +C6_no_distance,0.5/async,rmse,0.921867305917475,0.9216773579193855,0.8460563823944631,1.0020780355782044,1000,paired source-video group resample,,,,,C0,-0.08146042772669582,-0.08107240194812121,-0.13393482650724536,-0.026801749759197024, +C6_no_distance,0.5/async,pearson,0.5922781825065613,0.5932337641716003,0.5353990465402603,0.6483898550271988,1000,paired source-video group resample,,,,,C0,0.11778348684310913,0.1168685108423233,0.0705943837761879,0.16527902334928513, +C6_no_distance,0.7/single,accuracy,0.6016483516483516,0.6009515327558677,0.5632629745446566,0.6423739247987418,1000,paired source-video group resample,,,,,C0,0.016483516483516425,0.016914245892018787,-0.01653943129289822,0.055476480129764756, +C6_no_distance,0.7/single,macro_f1,0.5070397297060157,0.5060551735999144,0.4732247382704948,0.5419256295465614,1000,paired source-video group resample,,,,,C0,-0.044271242796481314,-0.04413917974325221,-0.08313354869343513,-0.0025462079525285755, +C6_no_distance,0.7/single,mae,0.6993075609207153,0.6993314623832703,0.6487176880240441,0.7551153317093849,1000,paired source-video group resample,0.01929187774658203,0.01944217085838318,0.005565670132637024,0.03435665667057037,C0,-0.08864104747772217,-0.08793234825134277,-0.13224689960479735,-0.045784451067447676, +C6_no_distance,0.7/single,rmse,0.9227717289377729,0.9222794778936058,0.8428237466836117,1.005840735382858,1000,paired source-video group resample,,,,,C0,-0.08755226648615555,-0.08817705940623488,-0.1453630252572913,-0.03265180743808382, +C6_no_distance,0.7/single,pearson,0.5944802165031433,0.5948635339736938,0.5377781704068184,0.6496812015771866,1000,paired source-video group resample,,,,,C0,0.12184000015258789,0.12208554148674011,0.07248420491814614,0.17525987774133683, +C6_no_distance,0.7/sync,accuracy,0.5947802197802198,0.5945152253456707,0.5550566148127754,0.6358502688227845,1000,paired source-video group resample,,,,,C0,0.012362637362637319,0.012396788294578354,-0.02449567723342938,0.04955168672321951, +C6_no_distance,0.7/sync,macro_f1,0.5069876749474366,0.5055441862388907,0.474213513458175,0.5421369720499958,1000,paired source-video group resample,,,,,C0,-0.0419518251529275,-0.042228613670342474,-0.08484048100100516,0.002868398339762268, +C6_no_distance,0.7/sync,mae,0.713942289352417,0.7139276266098022,0.6605738505721093,0.7720478773117065,1000,paired source-video group resample,0.03392660617828369,0.03337574005126953,0.013393722474575043,0.055271640419960015,C0,-0.06942933797836304,-0.07017171382904053,-0.1170486256480217,-0.02559065967798233, +C6_no_distance,0.7/sync,rmse,0.9592106196830549,0.9584545723782454,0.8800149764991602,1.0427798969080748,1000,paired source-video group resample,,,,,C0,-0.06094482187424266,-0.0611245242546799,-0.11992679864405073,-0.0065709591608013275, +C6_no_distance,0.7/sync,pearson,0.5535411834716797,0.5534327924251556,0.4878692977130413,0.6185216188430785,1000,paired source-video group resample,,,,,C0,0.07509613037109375,0.0753360390663147,0.030808966606855392,0.1259769283235073, +C6_no_distance,0.7/partial,accuracy,0.6112637362637363,0.6116977266850971,0.5707725835808027,0.652293987921069,1000,paired source-video group resample,,,,,C0,0.017857142857142905,0.017794006015904418,-0.01761637283492404,0.052704230612522086, +C6_no_distance,0.7/partial,macro_f1,0.5271121447457674,0.5256841923654311,0.4879724071234662,0.5649870276252033,1000,paired source-video group resample,,,,,C0,-0.03690129247084306,-0.03797682949239023,-0.08003476327321189,0.004388483367654255, +C6_no_distance,0.7/partial,mae,0.7028897404670715,0.7030632197856903,0.6465465798974037,0.7634827777743339,1000,paired source-video group resample,0.022874057292938232,0.02286502718925476,-0.0013167306780815125,0.0482688471674919,C0,-0.09470158815383911,-0.09486371278762817,-0.14086198955774307,-0.04986833930015564, +C6_no_distance,0.7/partial,rmse,0.9405053604435603,0.9394341861436948,0.8548688710541694,1.0249659930631778,1000,paired source-video group resample,,,,,C0,-0.07695133132335563,-0.0773200630977321,-0.13080361122390666,-0.025436521747563418, +C6_no_distance,0.7/partial,pearson,0.5665954947471619,0.5669914484024048,0.5003538012504578,0.631548897922039,1000,paired source-video group resample,,,,,C0,0.07411867380142212,0.07460296154022217,0.025863377749919893,0.12699559926986692, +C6_no_distance,0.7/async,accuracy,0.5796703296703297,0.5792313345411946,0.5411345106912427,0.6206908797021944,1000,paired source-video group resample,,,,,C0,0.0013736263736263687,0.002536487134203791,-0.03657077038465663,0.03816873542303001, +C6_no_distance,0.7/async,macro_f1,0.48219456316660897,0.4812865958554713,0.4501917371919864,0.5153952389846538,1000,paired source-video group resample,,,,,C0,-0.07160349984129483,-0.07052235473116941,-0.1116876989875115,-0.032147755411140115, +C6_no_distance,0.7/async,mae,0.7193584442138672,0.7196758091449738,0.670970244705677,0.7692043289542199,1000,paired source-video group resample,0.03934276103973389,0.039588212966918945,0.012165753543376923,0.06793600171804427,C0,-0.09710115194320679,-0.09716054797172546,-0.14050834327936174,-0.049619425833225254, +C6_no_distance,0.7/async,rmse,0.9436757759565018,0.9431208219479332,0.8680350897802439,1.0180255665362505,1000,paired source-video group resample,,,,,C0,-0.09711910281785241,-0.09813560202247446,-0.16086089604010098,-0.036155097218016206, +C6_no_distance,0.7/async,pearson,0.56895512342453,0.5691666901111603,0.5084297373890877,0.6228904455900192,1000,paired source-video group resample,,,,,C0,0.089758962392807,0.09057790040969849,0.03450645208358765,0.14522775858640669, +C6_no_distance,0.3/modality_T,accuracy,0.6071428571428571,0.6073826350100662,0.5677076139502762,0.6464750242147503,1000,paired source-video group resample,,,,,C0,0.02060439560439553,0.019816004263315867,-0.013228683803904958,0.05252965008004696, +C6_no_distance,0.3/modality_T,macro_f1,0.5105005695523733,0.5099129756363234,0.4768093560755081,0.5416544599826751,1000,paired source-video group resample,,,,,C0,-0.03626274389133344,-0.037132161333922664,-0.07409464248498966,0.0033585357504769472, +C6_no_distance,0.3/modality_T,mae,0.6831811666488647,0.6829142272472382,0.6305804938077927,0.7365404143929482,1000,paired source-video group resample,0.0031654834747314453,0.003241240978240967,-0.01274697333574295,0.01865003705024719,C0,-0.06694257259368896,-0.06659263372421265,-0.10593879967927933,-0.027418437600135823, +C6_no_distance,0.3/modality_T,rmse,0.9098118142588387,0.909168188395739,0.8340809729438159,0.9839961922832731,1000,paired source-video group resample,,,,,C0,-0.05285751739528188,-0.05321726182272657,-0.1089285984990596,-0.0013008171072916538, +C6_no_distance,0.3/modality_T,pearson,0.6064049601554871,0.6067328453063965,0.5518755689263344,0.661211122572422,1000,paired source-video group resample,,,,,C0,0.10464257001876831,0.10514169931411743,0.05782427340745926,0.1575210817158222, +C6_no_distance,0.3/modality_A,accuracy,0.6043956043956044,0.6042810916067696,0.5651498403580988,0.646576910263194,1000,paired source-video group resample,,,,,C0,0.017857142857142794,0.018169121381411857,-0.020189495017076536,0.05327204065716641, +C6_no_distance,0.3/modality_A,macro_f1,0.5148487753353405,0.5151401672149964,0.48208001842043174,0.5504224284161782,1000,paired source-video group resample,,,,,C0,-0.03663299332455683,-0.03581869040289998,-0.07706037660049629,0.003100678407576196, +C6_no_distance,0.3/modality_A,mae,0.6773197054862976,0.6769469082355499,0.627687183022499,0.7341747716069221,1000,paired source-video group resample,-0.0026959776878356934,-0.0025325119495391846,-0.007897944748401641,0.0014104902744293212,C0,-0.052847325801849365,-0.05227309465408325,-0.08946355134248733,-0.016406604647636415, +C6_no_distance,0.3/modality_A,rmse,0.9072500498906466,0.9063761885165291,0.82620956392892,0.9882183527368089,1000,paired source-video group resample,,,,,C0,-0.027062310425433278,-0.0270211581570175,-0.07695486002099045,0.01906193540697641, +C6_no_distance,0.3/modality_A,pearson,0.6065755486488342,0.6073621511459351,0.5527412682771683,0.6601326897740364,1000,paired source-video group resample,,,,,C0,0.08383852243423462,0.08396837115287781,0.041651637852191926,0.1280905112624168, +C6_no_distance,0.3/modality_V,accuracy,0.6043956043956044,0.6037591592151018,0.5648001485446776,0.6469009443752595,1000,paired source-video group resample,,,,,C0,0.016483516483516425,0.016689847009735748,-0.01971130221130217,0.050484946035863225, +C6_no_distance,0.3/modality_V,macro_f1,0.5145608034694523,0.5145043115388981,0.4801817656186176,0.550913998536648,1000,paired source-video group resample,,,,,C0,-0.03653254251339644,-0.03681032218307137,-0.0764008543500739,0.0042916967046716875, +C6_no_distance,0.3/modality_V,mae,0.678547203540802,0.6785908639431,0.6273660108447074,0.7341142177581786,1000,paired source-video group resample,-0.0014684796333312988,-0.0014541149139404297,-0.005781054496765137,0.001964646577835082,C0,-0.05478590726852417,-0.05456185340881348,-0.09129244685173035,-0.01814011186361313, +C6_no_distance,0.3/modality_V,rmse,0.9072436442989554,0.9059707605988674,0.8243482719596239,0.9909197982460429,1000,paired source-video group resample,,,,,C0,-0.030549088013670955,-0.030546394629758,-0.08285067905458773,0.015037658770227997, +C6_no_distance,0.3/modality_V,pearson,0.6043447852134705,0.6049643456935883,0.5509040161967278,0.6589729055762291,1000,paired source-video group resample,,,,,C0,0.0848989486694336,0.08515186607837677,0.043469575047492985,0.12916478440165516, +C6_no_distance,0.3/modality_TA,accuracy,0.5989010989010989,0.5985557872784151,0.5566256530236404,0.6415192464044408,1000,paired source-video group resample,,,,,C0,0.012362637362637319,0.013019322761685936,-0.022104064390033755,0.0462444476046276, +C6_no_distance,0.3/modality_TA,macro_f1,0.5021633572311629,0.5013609497657744,0.4658475573147752,0.5378876557658099,1000,paired source-video group resample,,,,,C0,-0.05203492992912995,-0.05075104762524174,-0.09080410583016336,-0.013862518707021015, +C6_no_distance,0.3/modality_TA,mae,0.6920380592346191,0.6920689642429352,0.6386180087924004,0.7475346386432647,1000,paired source-video group resample,0.01202237606048584,0.011730432510375977,-0.00464494377374649,0.029753479361534118,C0,-0.08354747295379639,-0.08368974924087524,-0.1233528956770897,-0.04292213767766953, +C6_no_distance,0.3/modality_TA,rmse,0.9218276060173938,0.9212869286499629,0.8396271181479794,0.9987989797864383,1000,paired source-video group resample,,,,,C0,-0.04879348033604303,-0.04912970311135273,-0.10622052465949088,0.00494916781254752, +C6_no_distance,0.3/modality_TA,pearson,0.5942491888999939,0.5952686369419098,0.5358537688851357,0.6554137870669364,1000,paired source-video group resample,,,,,C0,0.0958092212677002,0.09614792466163635,0.04963812977075577,0.14822548627853394, +C6_no_distance,0.3/modality_TV,accuracy,0.6043956043956044,0.6043045846472754,0.5650406504065041,0.644198064814429,1000,paired source-video group resample,,,,,C0,0.0219780219780219,0.022849503644755964,-0.012924990431634855,0.05774429930362748, +C6_no_distance,0.3/modality_TV,macro_f1,0.5020356082918148,0.5010510405641763,0.4701174275890804,0.5347567698140203,1000,paired source-video group resample,,,,,C0,-0.04280897969704345,-0.04245135492598384,-0.0831490780668454,-0.0017504549662807638, +C6_no_distance,0.3/modality_TV,mae,0.6817017793655396,0.6817908883094788,0.6318092927336693,0.7354638054966927,1000,paired source-video group resample,0.00168609619140625,0.0014712512493133545,-0.01133023202419281,0.01568959653377533,C0,-0.0789719820022583,-0.07957589626312256,-0.11942778080701828,-0.04193838685750963, +C6_no_distance,0.3/modality_TV,rmse,0.9059872739710719,0.90417039492693,0.825758004617698,0.9858194398807506,1000,paired source-video group resample,,,,,C0,-0.06157981683481695,-0.06227233216591427,-0.11374699606041853,-0.012112402672646742, +C6_no_distance,0.3/modality_TV,pearson,0.6048891544342041,0.6056332588195801,0.5497946679592133,0.660351175069809,1000,paired source-video group resample,,,,,C0,0.10590234398841858,0.10757681727409363,0.06166244298219681,0.15207844227552414, +C6_no_distance,0.3/modality_AV,accuracy,0.6085164835164835,0.6078431372549019,0.5697339481969745,0.6519536984754376,1000,paired source-video group resample,,,,,C0,0.013736263736263687,0.014075501602968221,-0.020722560365656572,0.0496586063814566, +C6_no_distance,0.3/modality_AV,macro_f1,0.5212891742088941,0.5214124791018626,0.4876253162982765,0.5592264581505841,1000,paired source-video group resample,,,,,C0,-0.03840903203021806,-0.03845809299305103,-0.0773316867758721,0.004059029356156699, +C6_no_distance,0.3/modality_AV,mae,0.6742284297943115,0.6744580268859863,0.6226706400513649,0.7304720997810363,1000,paired source-video group resample,-0.005787253379821777,-0.00576472282409668,-0.011275267601013184,-0.001457916200160982,C0,-0.06375241279602051,-0.06388232111930847,-0.10041384845972061,-0.025782616436481477, +C6_no_distance,0.3/modality_AV,rmse,0.9051976506547028,0.9037101440439337,0.822690518583142,0.9887647343025446,1000,paired source-video group resample,,,,,C0,-0.03683757684688771,-0.036568082151149095,-0.08782472543060396,0.009634487549168534, +C6_no_distance,0.3/modality_AV,pearson,0.6055561304092407,0.6063191592693329,0.55161452293396,0.6601675674319267,1000,paired source-video group resample,,,,,C0,0.09002220630645752,0.09034186601638794,0.04789337664842606,0.13460040315985675, +C6_no_distance,0.3/modality_TAV,accuracy,0.6002747252747253,0.6008316907009718,0.5613674904757253,0.6424684985509334,1000,paired source-video group resample,,,,,C0,0.019230769230769162,0.019417513080947968,-0.015418407247292034,0.058583242325400756, +C6_no_distance,0.3/modality_TAV,macro_f1,0.5066865802368145,0.5060123171711257,0.472258485082648,0.5429782064969388,1000,paired source-video group resample,,,,,C0,-0.03779131836746774,-0.03793591242802705,-0.0770484228465453,0.0063202225347847064, +C6_no_distance,0.3/modality_TAV,mae,0.6833959817886353,0.6830960810184479,0.6312042579054833,0.7372541323304176,1000,paired source-video group resample,0.003380298614501953,0.00295102596282959,-0.011132171750068665,0.016208761930465696,C0,-0.08753573894500732,-0.08787289261817932,-0.12771486043930053,-0.05036211162805559, +C6_no_distance,0.3/modality_TAV,rmse,0.9079413908494766,0.9071947960618563,0.8295264531098412,0.9825675360657629,1000,paired source-video group resample,,,,,C0,-0.07209637081189257,-0.073355309973413,-0.12478324834896178,-0.024354276698242968, +C6_no_distance,0.3/modality_TAV,pearson,0.6042477488517761,0.6041037440299988,0.548663541674614,0.6596623823046684,1000,paired source-video group resample,,,,,C0,0.11393824219703674,0.11494022607803345,0.07065803036093712,0.16135158985853196, +C6_no_distance,0.3/location_start_T,accuracy,0.5879120879120879,0.588074001405756,0.548289536208054,0.6283269937380324,1000,paired source-video group resample,,,,,C0,-0.004120879120879106,-0.004065048114085701,-0.03940721857511836,0.031359537178832754, +C6_no_distance,0.3/location_start_T,macro_f1,0.4893747104576598,0.4880558502748882,0.4564716217811785,0.524138902220992,1000,paired source-video group resample,,,,,C0,-0.07181646311066303,-0.07180781623030594,-0.1115665733003981,-0.03202383113587436, +C6_no_distance,0.3/location_start_T,mae,0.6954659819602966,0.6951927244663239,0.6413548871874809,0.7509262457489967,1000,paired source-video group resample,0.01545029878616333,0.015051543712615967,-0.0022524252533912656,0.03256071507930755,C0,-0.07379519939422607,-0.07355454564094543,-0.11831386089324951,-0.030964617431163792, +C6_no_distance,0.3/location_start_T,rmse,0.9306510291933171,0.9300330024671861,0.8483769961692225,1.0135951918368766,1000,paired source-video group resample,,,,,C0,-0.04466290041874299,-0.04412675704832647,-0.10314624275466681,0.010852738473683324, +C6_no_distance,0.3/location_start_T,pearson,0.5888088345527649,0.5892627537250519,0.5280090346932411,0.6496727511286735,1000,paired source-video group resample,,,,,C0,0.10625937581062317,0.10519741475582123,0.05634962320327759,0.16294242367148398, +C6_no_distance,0.3/location_middle_T,accuracy,0.592032967032967,0.5917121358999216,0.5524789782041164,0.6327517279756326,1000,paired source-video group resample,,,,,C0,0.0027472527472527375,0.0026954226855055996,-0.0272331520510547,0.03518049938518622, +C6_no_distance,0.3/location_middle_T,macro_f1,0.4963007191571796,0.4954705327455966,0.461353847115416,0.5312951859436659,1000,paired source-video group resample,,,,,C0,-0.05450078452913726,-0.055097102220088456,-0.08906382456803257,-0.016705456032082046, +C6_no_distance,0.3/location_middle_T,mae,0.697198748588562,0.6975924372673035,0.6443684190511704,0.7525483444333076,1000,paired source-video group resample,0.01718306541442871,0.017098546028137207,0.0041922926902771,0.03152896910905838,C0,-0.05156862735748291,-0.051762014627456665,-0.09372474402189254,-0.015295752882957467, +C6_no_distance,0.3/location_middle_T,rmse,0.9261711361937229,0.9249817805192437,0.8481432913313384,1.0016564001241568,1000,paired source-video group resample,,,,,C0,-0.035286138557092284,-0.03519375765553928,-0.08762113062196746,0.01317517542309016, +C6_no_distance,0.3/location_middle_T,pearson,0.5909598469734192,0.5914804339408875,0.536239019036293,0.6474247336387634,1000,paired source-video group resample,,,,,C0,0.08400553464889526,0.08460558950901031,0.03918929547071457,0.13379246816039084, +C6_no_distance,0.3/location_end_T,accuracy,0.5934065934065934,0.5936252727545783,0.5534218750884663,0.6350106930549514,1000,paired source-video group resample,,,,,C0,0.019230769230769273,0.01872333458534381,-0.015633311170212764,0.055407542899786284, +C6_no_distance,0.3/location_end_T,macro_f1,0.48598837043921583,0.48489302176471716,0.4520842682791946,0.5203693065463767,1000,paired source-video group resample,,,,,C0,-0.05197980349067721,-0.05171559095304207,-0.09241294787285055,-0.01474759483763069, +C6_no_distance,0.3/location_end_T,mae,0.6978398561477661,0.6976021230220795,0.6460037723183631,0.7536772340536118,1000,paired source-video group resample,0.017824172973632812,0.01755988597869873,-0.0004191040992736815,0.03410300463438034,C0,-0.07131302356719971,-0.07146558165550232,-0.10881319046020507,-0.03227854073047639, +C6_no_distance,0.3/location_end_T,rmse,0.9193112559882304,0.9161555445187026,0.8395180509977564,1.000767167323748,1000,paired source-video group resample,,,,,C0,-0.05822131273981035,-0.05904180644800722,-0.10914967119216452,-0.010576113315627475, +C6_no_distance,0.3/location_end_T,pearson,0.5979259610176086,0.5982822477817535,0.5348668962717056,0.6585419461131096,1000,paired source-video group resample,,,,,C0,0.09124135971069336,0.09206759929656982,0.05126476585865021,0.13352287262678145, +C6_no_distance,0.3/span_long_T,accuracy,0.6002747252747253,0.600263852242744,0.5602291473347768,0.6401785463222209,1000,paired source-video group resample,,,,,C0,0.0219780219780219,0.02231520223152028,-0.012872051333124645,0.05548644170728918, +C6_no_distance,0.3/span_long_T,macro_f1,0.5000450516824094,0.4989471839197418,0.469017748646508,0.530500555649131,1000,paired source-video group resample,,,,,C0,-0.04005942338759172,-0.03998159066765955,-0.07913758612917529,-0.0025428002869228882, +C6_no_distance,0.3/span_long_T,mae,0.6942288875579834,0.694132924079895,0.6438016518950462,0.7506473943591118,1000,paired source-video group resample,0.014213204383850098,0.014257252216339111,0.0027299419045448306,0.027539451420307157,C0,-0.054892659187316895,-0.055063605308532715,-0.09295637905597687,-0.01850040107965471, +C6_no_distance,0.3/span_long_T,rmse,0.9208790846861307,0.9198777642046915,0.8419773892153576,0.9996021814186258,1000,paired source-video group resample,,,,,C0,-0.043018836338739486,-0.043085831966564514,-0.09226800075141693,0.004852822329755415, +C6_no_distance,0.3/span_long_T,pearson,0.5963420271873474,0.5959692895412445,0.5412931367754936,0.6523815780878067,1000,paired source-video group resample,,,,,C0,0.09636291861534119,0.09676522016525269,0.053998954594135284,0.14043554365634917, +C6_no_distance,0.3/span_multi_short_T,accuracy,0.603021978021978,0.6023102952404249,0.5612241388990259,0.6467334951025361,1000,paired source-video group resample,,,,,C0,0.015109890109890056,0.015905552672548007,-0.018183093204131077,0.04954317269076299, +C6_no_distance,0.3/span_multi_short_T,macro_f1,0.5032310215396025,0.5022350686256208,0.4673927981841599,0.5407659667843805,1000,paired source-video group resample,,,,,C0,-0.0483134337470158,-0.04782617672860687,-0.08493049999110452,-0.009160593115724551, +C6_no_distance,0.3/span_multi_short_T,mae,0.6897515058517456,0.6894582509994507,0.6388137087225914,0.7429283320903778,1000,paired source-video group resample,0.009735822677612305,0.009093612432479858,-0.0024637043476104735,0.021739560365676876,C0,-0.061704039573669434,-0.06208869814872742,-0.10215657502412796,-0.02376569509506226, +C6_no_distance,0.3/span_multi_short_T,rmse,0.9201244285135006,0.9184808149636732,0.8420892801547336,0.999485255168359,1000,paired source-video group resample,,,,,C0,-0.04057367716688087,-0.0414925721077794,-0.09335523259267127,0.01088962798351652, +C6_no_distance,0.3/span_multi_short_T,pearson,0.5958517789840698,0.5969451367855072,0.5411904573440551,0.6492987185716629,1000,paired source-video group resample,,,,,C0,0.09424322843551636,0.09431678056716919,0.049300917983055116,0.14299838095903397, +C6_no_distance,0.3/location_start_A,accuracy,0.6057692307692307,0.6047657683497503,0.5675080169923175,0.6485813316477034,1000,paired source-video group resample,,,,,C0,0.0219780219780219,0.022630459538112102,-0.011726986069277108,0.05666046079116084, +C6_no_distance,0.3/location_start_A,macro_f1,0.5135247095407428,0.5137115826099237,0.4781962595440806,0.5513693484886969,1000,paired source-video group resample,,,,,C0,-0.04325545085648441,-0.04225991215523245,-0.08025369259057169,-0.004866502824879801, +C6_no_distance,0.3/location_start_A,mae,0.6756117343902588,0.6755348742008209,0.62426398396492,0.7302185386419295,1000,paired source-video group resample,-0.004403948783874512,-0.004351675510406494,-0.01112593114376068,0.0013272061944007863,C0,-0.059386610984802246,-0.058791160583496094,-0.09753849655389786,-0.022841042280197146, +C6_no_distance,0.3/location_start_A,rmse,0.905872364946262,0.9047811706743863,0.8229783427596435,0.9880056854180989,1000,paired source-video group resample,,,,,C0,-0.03492498274840561,-0.035114973229736335,-0.08468699018705127,0.010834449386239823, +C6_no_distance,0.3/location_start_A,pearson,0.6068800687789917,0.6077457368373871,0.5522304147481918,0.6604126214981079,1000,paired source-video group resample,,,,,C0,0.08913642168045044,0.09054127335548401,0.04778495281934738,0.13329783380031585, +C6_no_distance,0.3/location_middle_A,accuracy,0.6071428571428571,0.6069739820062473,0.5675239004577531,0.649925799086758,1000,paired source-video group resample,,,,,C0,0.02060439560439553,0.020862308762169712,-0.015410526816959133,0.0556544321601722, +C6_no_distance,0.3/location_middle_A,macro_f1,0.5171098774574694,0.5172801722845833,0.4824342432384057,0.5538697123242345,1000,paired source-video group resample,,,,,C0,-0.03665294587057133,-0.03653759183172589,-0.07685027227359957,0.004710511388760525, +C6_no_distance,0.3/location_middle_A,mae,0.6732667088508606,0.6731349527835846,0.6233459278941155,0.728960146009922,1000,paired source-video group resample,-0.006748974323272705,-0.006491959095001221,-0.012545476853847503,-0.002023525536060334,C0,-0.060756564140319824,-0.06041547656059265,-0.09644584655761719,-0.024092639982700347, +C6_no_distance,0.3/location_middle_A,rmse,0.9033247664058273,0.902262692739513,0.8212301104726956,0.9850418494826245,1000,paired source-video group resample,,,,,C0,-0.03345416924781075,-0.03298109564853968,-0.08413616436621796,0.011977670113837083, +C6_no_distance,0.3/location_middle_A,pearson,0.6088435053825378,0.6096804738044739,0.5544972315430641,0.6624010145664215,1000,paired source-video group resample,,,,,C0,0.08848226070404053,0.08854138851165771,0.04567490220069885,0.134719567745924, +C6_no_distance,0.3/location_end_A,accuracy,0.603021978021978,0.6026398637489678,0.5629858868708681,0.6467321135054098,1000,paired source-video group resample,,,,,C0,0.013736263736263687,0.01384372970498371,-0.020992805058870082,0.04774694326143699, +C6_no_distance,0.3/location_end_A,macro_f1,0.5116790727202128,0.5111355548586748,0.4771675587600533,0.5498540110001322,1000,paired source-video group resample,,,,,C0,-0.04172008854484588,-0.041677929255178825,-0.07980315888936798,-0.00382163812725503, +C6_no_distance,0.3/location_end_A,mae,0.6792832016944885,0.6792460381984711,0.6275723919272422,0.7365644738078118,1000,paired source-video group resample,-0.0007324814796447754,-0.0007198154926300049,-0.0014134004712104797,-1.2911856174469177e-05,C0,-0.05546373128890991,-0.05517110228538513,-0.09274040162563324,-0.018677924573421486, +C6_no_distance,0.3/location_end_A,rmse,0.9091004891324282,0.9080524601179611,0.8274900636483686,0.9924691708556653,1000,paired source-video group resample,,,,,C0,-0.028568931695964195,-0.028433400774197592,-0.07913103459110726,0.017668794011305815, +C6_no_distance,0.3/location_end_A,pearson,0.6043553352355957,0.6049699783325195,0.5491509005427361,0.6587622866034508,1000,paired source-video group resample,,,,,C0,0.08540397882461548,0.08559542894363403,0.04295356571674347,0.1298963904380798, +C6_no_distance,0.3/span_long_A,accuracy,0.6071428571428571,0.6060798583034923,0.567909365660166,0.6500051440329219,1000,paired source-video group resample,,,,,C0,0.019230769230769162,0.01932375432941258,-0.016578048292525342,0.05365853281471274, +C6_no_distance,0.3/span_long_A,macro_f1,0.5185456899839284,0.5186354372064486,0.4830073754262091,0.5579470694116077,1000,paired source-video group resample,,,,,C0,-0.035791590669141726,-0.03515490820876446,-0.0733991811525178,0.00468492659251774, +C6_no_distance,0.3/span_long_A,mae,0.6740279793739319,0.6737452447414398,0.6245040744543076,0.7291699796915054,1000,paired source-video group resample,-0.005987703800201416,-0.005953043699264526,-0.012467892467975616,-0.0006256818771362313,C0,-0.06263089179992676,-0.062466591596603394,-0.09814398288726807,-0.02647525668144227, +C6_no_distance,0.3/span_long_A,rmse,0.9042254228149597,0.9031875091477429,0.8218866015647968,0.985989161302349,1000,paired source-video group resample,,,,,C0,-0.03372765373840292,-0.033207236699642595,-0.08255347472797714,0.012202470618040372, +C6_no_distance,0.3/span_long_A,pearson,0.6088837385177612,0.6095013618469238,0.5550060048699379,0.6619788929820061,1000,paired source-video group resample,,,,,C0,0.09135383367538452,0.0916202962398529,0.04951408505439758,0.1362604551017284, +C6_no_distance,0.3/span_multi_short_A,accuracy,0.6071428571428571,0.6064246937951456,0.5689858429258551,0.6495948753462604,1000,paired source-video group resample,,,,,C0,0.012362637362637319,0.013093777621993874,-0.022535114815860555,0.04523996951855123, +C6_no_distance,0.3/span_multi_short_A,macro_f1,0.5183366478838859,0.517945644077638,0.48351096738980603,0.5554283128909802,1000,paired source-video group resample,,,,,C0,-0.04194118770012245,-0.04183337002165424,-0.07956808023266729,-0.002190573606875674, +C6_no_distance,0.3/span_multi_short_A,mae,0.6754654049873352,0.6756650507450104,0.6262660458683967,0.7299988463521003,1000,paired source-video group resample,-0.004550278186798096,-0.004438042640686035,-0.0107537180185318,0.00038827508687973024,C0,-0.06065863370895386,-0.059912264347076416,-0.09695959240198135,-0.0231249213218689, +C6_no_distance,0.3/span_multi_short_A,rmse,0.9055388389759383,0.9045557269786743,0.824232143462961,0.9877224642357332,1000,paired source-video group resample,,,,,C0,-0.03610731066935979,-0.03630708747473377,-0.08509347927694827,0.010571674334546272, +C6_no_distance,0.3/span_multi_short_A,pearson,0.6082422137260437,0.6093773245811462,0.5536778107285499,0.662341071665287,1000,paired source-video group resample,,,,,C0,0.09194183349609375,0.09271872043609619,0.04961540848016739,0.135122837126255, +C6_no_distance,0.3/location_start_V,accuracy,0.6043956043956044,0.6035901773606691,0.5661587836846661,0.6455566037735849,1000,paired source-video group resample,,,,,C0,0.008241758241758212,0.008097165991902855,-0.027821125120712723,0.04324320221680037, +C6_no_distance,0.3/location_start_V,macro_f1,0.5183406318518838,0.5179850869121482,0.4838550924371913,0.5541485841836649,1000,paired source-video group resample,,,,,C0,-0.045470041918076465,-0.045247083870863486,-0.08525900182653937,-0.0032835545901719284, +C6_no_distance,0.3/location_start_V,mae,0.6725002527236938,0.6728144288063049,0.6216966837644577,0.7279955983161925,1000,paired source-video group resample,-0.007515430450439453,-0.00760379433631897,-0.014302222430706025,-0.0005099162459373478,C0,-0.06094616651535034,-0.06045430898666382,-0.09603227823972701,-0.024805711209774026, +C6_no_distance,0.3/location_start_V,rmse,0.8997585038856168,0.8984124701137081,0.8200967717531196,0.9779728584280273,1000,paired source-video group resample,,,,,C0,-0.03708281618559317,-0.03746356742767165,-0.08661023145165034,0.008745183721395454, +C6_no_distance,0.3/location_start_V,pearson,0.6068794131278992,0.607274204492569,0.5540251120924949,0.6616467401385308,1000,paired source-video group resample,,,,,C0,0.08583897352218628,0.0859651267528534,0.04559860825538636,0.12924280762672422, +C6_no_distance,0.3/location_middle_V,accuracy,0.6071428571428571,0.6065350193107546,0.5666643059490085,0.6499473508108959,1000,paired source-video group resample,,,,,C0,0.015109890109890056,0.015320363979880625,-0.01847419964188781,0.04964563462949372, +C6_no_distance,0.3/location_middle_V,macro_f1,0.5153088857899227,0.5150767662017512,0.4803515929014019,0.553747600582001,1000,paired source-video group resample,,,,,C0,-0.04040009324649341,-0.04087361753711305,-0.0768086898508883,-0.0009413093091841448, +C6_no_distance,0.3/location_middle_V,mae,0.6730220913887024,0.6730170249938965,0.6213815405964851,0.7288648635149002,1000,paired source-video group resample,-0.006993591785430908,-0.0067175328731536865,-0.01421525627374649,-0.0011521160602569584,C0,-0.060787975788116455,-0.060674697160720825,-0.0975407376885414,-0.023282161355018625, +C6_no_distance,0.3/location_middle_V,rmse,0.9007587466443898,0.8999213528699386,0.8184605658308555,0.9841025304924587,1000,paired source-video group resample,,,,,C0,-0.038122459664203134,-0.037798724612141954,-0.08945478769871937,0.009716745266446848, +C6_no_distance,0.3/location_middle_V,pearson,0.6085426211357117,0.6094817817211151,0.5534730732440949,0.6622316643595695,1000,paired source-video group resample,,,,,C0,0.08951914310455322,0.08965295553207397,0.04746417850255966,0.13622241988778114, +C6_no_distance,0.3/location_end_V,accuracy,0.603021978021978,0.6027779563326263,0.5629858868708681,0.6463856805950293,1000,paired source-video group resample,,,,,C0,0.013736263736263687,0.013937288998185637,-0.021508087756809503,0.046581749566098174, +C6_no_distance,0.3/location_end_V,macro_f1,0.5136445088160463,0.5133764465638571,0.4782641849904406,0.5510982495828787,1000,paired source-video group resample,,,,,C0,-0.03963188605462553,-0.03994722499554504,-0.07831782797274248,-0.0001618595312533431, +C6_no_distance,0.3/location_end_V,mae,0.6810232996940613,0.6806755065917969,0.6296386599540711,0.7376977294683457,1000,paired source-video group resample,0.0010076165199279785,0.0008841156959533691,-0.0015940606594085692,0.004761771857738494,C0,-0.052195072174072266,-0.051664143800735474,-0.08967986106872558,-0.014797382056713106, +C6_no_distance,0.3/location_end_V,rmse,0.9109967979642871,0.9098681334687474,0.828888076874033,0.9935300517587224,1000,paired source-video group resample,,,,,C0,-0.026447696547373112,-0.026448202310992985,-0.07791027323378574,0.02138912824198318, +C6_no_distance,0.3/location_end_V,pearson,0.6025092601776123,0.6032519340515137,0.5471886813640594,0.6569269433617592,1000,paired source-video group resample,,,,,C0,0.08336085081100464,0.08391168713569641,0.04078173637390137,0.12738524973392482, +C6_no_distance,0.3/span_long_V,accuracy,0.6043956043956044,0.6031632328193932,0.5648001485446776,0.6478377219944392,1000,paired source-video group resample,,,,,C0,0.019230769230769162,0.019849712934819297,-0.015554259076626676,0.05286171687303637, +C6_no_distance,0.3/span_long_V,macro_f1,0.5161005032109142,0.5157880204955193,0.479848487360397,0.5559419491687456,1000,paired source-video group resample,,,,,C0,-0.032513013557202486,-0.032050546321265666,-0.07013965363564433,0.006074207995866641, +C6_no_distance,0.3/span_long_V,mae,0.6788328289985657,0.6788617372512817,0.6276738092303276,0.7347359299659729,1000,paired source-video group resample,-0.001182854175567627,-0.0012531578540802002,-0.004327632486820221,0.0016925409436225885,C0,-0.05552548170089722,-0.05560261011123657,-0.09227334409952163,-0.018883605301380165, +C6_no_distance,0.3/span_long_V,rmse,0.9080120911213286,0.9067061194900178,0.8258834406503366,0.9906192018590946,1000,paired source-video group resample,,,,,C0,-0.029820046597305305,-0.029739544024082687,-0.08055428232286278,0.016254458170088942, +C6_no_distance,0.3/span_long_V,pearson,0.6032225489616394,0.6037887930870056,0.5480007007718086,0.6572015076875687,1000,paired source-video group resample,,,,,C0,0.08334195613861084,0.08349329233169556,0.041774360835552214,0.1268745824694633, +C6_no_distance,0.3/span_multi_short_V,accuracy,0.6043956043956044,0.6039186156390266,0.5648914211172498,0.6477499309842895,1000,paired source-video group resample,,,,,C0,0.016483516483516425,0.016654059505799346,-0.017694673071627406,0.05092578463536926, +C6_no_distance,0.3/span_multi_short_V,macro_f1,0.512375512418798,0.5122159062901244,0.47707670406905556,0.5508054825569428,1000,paired source-video group resample,,,,,C0,-0.039083805412110206,-0.03852224937951801,-0.07810850137104394,-0.0012592907889780627, +C6_no_distance,0.3/span_multi_short_V,mae,0.6780402660369873,0.6780124604701996,0.6259615316987037,0.734613373875618,1000,paired source-video group resample,-0.001975417137145996,-0.0019236505031585693,-0.006075067818164825,0.0012141093611717222,C0,-0.05556267499923706,-0.0553114116191864,-0.09153527915477752,-0.019386257231235517, +C6_no_distance,0.3/span_multi_short_V,rmse,0.9066544320938281,0.9051096251855731,0.82355586131811,0.9902580808823706,1000,paired source-video group resample,,,,,C0,-0.031278404338075494,-0.03150410409682136,-0.08245492562646596,0.01456524469632337, +C6_no_distance,0.3/span_multi_short_V,pearson,0.6052189469337463,0.605832040309906,0.5512047082185745,0.6598473578691483,1000,paired source-video group resample,,,,,C0,0.08570295572280884,0.08592328429222107,0.044320431351661686,0.13131532371044158, +C6_no_distance,0.3/synchrony_sync,accuracy,0.5961538461538461,0.5963809557020143,0.5541922135381574,0.6389384215940822,1000,paired source-video group resample,,,,,C0,0.008241758241758212,0.008026845637583935,-0.025725766286872717,0.044217518157551663, +C6_no_distance,0.3/synchrony_sync,macro_f1,0.5004410501920359,0.49968594434836155,0.4653287479884455,0.5365835697001358,1000,paired source-video group resample,,,,,C0,-0.04851118082172623,-0.04809461462050674,-0.08862803151734229,-0.006163406999749574, +C6_no_distance,0.3/synchrony_sync,mae,0.6964983940124512,0.6960991322994232,0.6448387145996094,0.7496112331748008,1000,paired source-video group resample,0.01648271083831787,0.01636570692062378,0.004298843443393707,0.02920690923929214,C0,-0.04644221067428589,-0.04619938135147095,-0.08801864087581635,-0.007703779637813583, +C6_no_distance,0.3/synchrony_sync,rmse,0.9240079224936297,0.923103739598899,0.8444537655272623,1.0028904913178183,1000,paired source-video group resample,,,,,C0,-0.02738528885820335,-0.028096443486125444,-0.08280566133671077,0.019186767514783636, +C6_no_distance,0.3/synchrony_sync,pearson,0.5917818546295166,0.5933710336685181,0.5378638848662376,0.6466580107808113,1000,paired source-video group resample,,,,,C0,0.07685732841491699,0.077365443110466,0.03625890016555786,0.12611867785453795, +C6_no_distance,0.3/synchrony_partial,accuracy,0.5961538461538461,0.5963593123276973,0.5576812977099237,0.6387411112290383,1000,paired source-video group resample,,,,,C0,0.004120879120879106,0.005250437967143418,-0.028828163515609715,0.03897609893517124, +C6_no_distance,0.3/synchrony_partial,macro_f1,0.5051836334462471,0.5034453402051208,0.4723854537400199,0.5432110916405742,1000,paired source-video group resample,,,,,C0,-0.051665293830053804,-0.050109919055638774,-0.09013791579103118,-0.01074129259960491, +C6_no_distance,0.3/synchrony_partial,mae,0.6970412135124207,0.6967003345489502,0.6449227169156074,0.7529611438512802,1000,paired source-video group resample,0.017025530338287354,0.016774028539657593,0.002102650701999665,0.03267039209604263,C0,-0.05791383981704712,-0.05816757678985596,-0.09547595381736755,-0.022973996400833138, +C6_no_distance,0.3/synchrony_partial,rmse,0.9225480160713003,0.9214541699144887,0.8426421986850113,0.9976290345007027,1000,paired source-video group resample,,,,,C0,-0.03119998303539151,-0.031158386892654766,-0.08370323824593082,0.01521193665883915, +C6_no_distance,0.3/synchrony_partial,pearson,0.5913355350494385,0.5923283100128174,0.5370146811008454,0.646767595410347,1000,paired source-video group resample,,,,,C0,0.0835912823677063,0.08412402868270874,0.04289351850748062,0.12802685499191283, +C6_no_distance,0.3/synchrony_async,accuracy,0.6016483516483516,0.6021798365122616,0.5616518407574848,0.6428620085636435,1000,paired source-video group resample,,,,,C0,0.006868131868131844,0.007570027048090622,-0.028051256692623948,0.039896725830419276, +C6_no_distance,0.3/synchrony_async,macro_f1,0.5039578620584847,0.5036727134392929,0.4693576128133631,0.53854991509124,1000,paired source-video group resample,,,,,C0,-0.05339188307730158,-0.05229822688075014,-0.09108258449387906,-0.01579545522052272, +C6_no_distance,0.3/synchrony_async,mae,0.6824854016304016,0.6833882629871368,0.6323874816298485,0.7320513457059861,1000,paired source-video group resample,0.0024697184562683105,0.002121448516845703,-0.016196534037590027,0.019979842007160183,C0,-0.07473737001419067,-0.07458886504173279,-0.11554302722215652,-0.036389541625976574, +C6_no_distance,0.3/synchrony_async,rmse,0.9049218738934315,0.9040832757015778,0.82744848128836,0.977413845001378,1000,paired source-video group resample,,,,,C0,-0.06216851099412479,-0.061730674932142626,-0.11286689717222952,-0.014527166575771898, +C6_no_distance,0.3/synchrony_async,pearson,0.6063346862792969,0.6073586046695709,0.5515517443418503,0.6605975359678269,1000,paired source-video group resample,,,,,C0,0.10861745476722717,0.10875672101974487,0.06464903205633163,0.15904329046607016, +C6_no_reconstruction,0.0/none,accuracy,0.6016483516483516,0.6017280852062254,0.5609272885704604,0.6432766587250017,1000,paired source-video group resample,,,,,C0,0.009615384615384581,0.010457677165354395,-0.02766636464891881,0.04482742249442144, +C6_no_reconstruction,0.0/none,macro_f1,0.5202652256673378,0.5203553109992045,0.4851983139228883,0.5553108031424159,1000,paired source-video group resample,,,,,C0,-0.03566938698369271,-0.03402358493974689,-0.0759059387252187,0.0057171310493897235, +C6_no_reconstruction,0.0/none,mae,0.6958225965499878,0.6964207589626312,0.6458705514669418,0.7496166065335274,1000,paired source-video group resample,,,,,C0,-0.03759133815765381,-0.03791210055351257,-0.0794791340827942,-9.415596723556991e-05, +C6_no_reconstruction,0.0/none,rmse,0.9330084973405222,0.9318957472351366,0.8478240086451476,1.0181696454408478,1000,paired source-video group resample,,,,,C0,-0.0041651620876680395,-0.005679100792277902,-0.06416159146592862,0.0550816128063761, +C6_no_reconstruction,0.0/none,pearson,0.5885183215141296,0.589328795671463,0.5195324063301087,0.6504251748323441,1000,paired source-video group resample,,,,,C0,0.06927573680877686,0.07028566300868988,0.017761725187301635,0.12056075558066366, +C6_no_reconstruction,0.1/single,accuracy,0.6002747252747253,0.599589867822687,0.5614468133622164,0.6417563549814078,1000,paired source-video group resample,,,,,C0,0.012362637362637319,0.013363213079480407,-0.023354064039408894,0.04615961800818548, +C6_no_reconstruction,0.1/single,macro_f1,0.5169083449614574,0.5170627048001704,0.482896070077999,0.5518501933539061,1000,paired source-video group resample,,,,,C0,-0.03297645247544889,-0.031158005148610612,-0.07322790217133007,0.008468806136319812, +C6_no_reconstruction,0.1/single,mae,0.6993690729141235,0.7000056207180023,0.6504463076591491,0.7533994853496552,1000,paired source-video group resample,0.003546476364135742,0.003475099802017212,-0.0016334578394889832,0.009827175736427307,C0,-0.03639012575149536,-0.036643147468566895,-0.07695655971765518,0.0016384199261665108, +C6_no_reconstruction,0.1/single,rmse,0.9348456954617017,0.9339675952799329,0.8526661181794714,1.0197049278381036,1000,paired source-video group resample,,,,,C0,-0.004476880099545499,-0.005585259597312764,-0.062270791488956014,0.05507160687373654, +C6_no_reconstruction,0.1/single,pearson,0.5868916511535645,0.5878130793571472,0.5196388199925422,0.6480072662234306,1000,paired source-video group resample,,,,,C0,0.0703161358833313,0.07181811332702637,0.018886981904506682,0.12157251685857773, +C6_no_reconstruction,0.1/sync,accuracy,0.6016483516483516,0.6011043281432197,0.5627551661046136,0.6420527123424021,1000,paired source-video group resample,,,,,C0,0.015109890109890056,0.015965200539265312,-0.021869556447916164,0.04945257219353609, +C6_no_reconstruction,0.1/sync,macro_f1,0.5187734410912527,0.5190147570555426,0.4852771281096114,0.552232095909566,1000,paired source-video group resample,,,,,C0,-0.031554622003500565,-0.029905097703319783,-0.07141178610952582,0.006304120383117161, +C6_no_reconstruction,0.1/sync,mae,0.6921753287315369,0.6926219761371613,0.644938762485981,0.7446777254343033,1000,paired source-video group resample,-0.0036472678184509277,-0.0031768977642059326,-0.01630156934261322,0.007156990468502042,C0,-0.04286754131317139,-0.043194591999053955,-0.08030295670032501,-0.0063266381621360935, +C6_no_reconstruction,0.1/sync,rmse,0.9179788791828124,0.915640517060542,0.8405438113659175,0.9957317500109284,1000,paired source-video group resample,,,,,C0,-0.027204385172474255,-0.02768753093629278,-0.08041534760492525,0.023402620922737337, +C6_no_reconstruction,0.1/sync,pearson,0.601701021194458,0.602507621049881,0.5344796240329742,0.6630344793200493,1000,paired source-video group resample,,,,,C0,0.08830118179321289,0.08948183059692383,0.04094051718711853,0.13489424288272858, +C6_no_reconstruction,0.1/partial,accuracy,0.6016483516483516,0.60113176814761,0.5629838189983285,0.6408977381528419,1000,paired source-video group resample,,,,,C0,0.008241758241758212,0.00875914275484635,-0.026692861601569504,0.04298438887750219, +C6_no_reconstruction,0.1/partial,macro_f1,0.5157735122089314,0.5157033432273953,0.4813253362955183,0.5504705462017853,1000,paired source-video group resample,,,,,C0,-0.04185942579437385,-0.04106960857030889,-0.08445940030459496,0.004751180722262332, +C6_no_reconstruction,0.1/partial,mae,0.7000133395195007,0.70014688372612,0.6497037842869758,0.7541456893086433,1000,paired source-video group resample,0.0041907429695129395,0.0038747191429138184,-0.006315056979656219,0.017356635630130766,C0,-0.03520405292510986,-0.03512978553771973,-0.07554790228605271,0.004512783885002117, +C6_no_reconstruction,0.1/partial,rmse,0.9417619152059631,0.9402865938588764,0.8569988785644691,1.0272111940422075,1000,paired source-video group resample,,,,,C0,0.004318469798751057,0.003441370263469412,-0.05622697092136462,0.06483443733255029, +C6_no_reconstruction,0.1/partial,pearson,0.5820462703704834,0.5832860767841339,0.5124794065952301,0.6438716486096382,1000,paired source-video group resample,,,,,C0,0.06147271394729614,0.0621606707572937,0.006740096211433412,0.1129103384912014, +C6_no_reconstruction,0.1/async,accuracy,0.5989010989010989,0.5985381988903116,0.5583055603193658,0.6408813227909979,1000,paired source-video group resample,,,,,C0,0.006868131868131844,0.007457125697889089,-0.029991916008983134,0.0439421223962689, +C6_no_reconstruction,0.1/async,macro_f1,0.5128310047552057,0.5124832229183948,0.47755591001785863,0.5466819530745922,1000,paired source-video group resample,,,,,C0,-0.04597601712420141,-0.04440720141880372,-0.08801413116824221,-0.0038401220532795145, +C6_no_reconstruction,0.1/async,mae,0.6975716948509216,0.6976723074913025,0.6505478650331498,0.7506108179688453,1000,paired source-video group resample,0.0017490983009338379,0.0022414028644561768,-0.009551692008972167,0.012288868427276611,C0,-0.04132193326950073,-0.041594475507736206,-0.0796442374587059,-0.007118165493011481, +C6_no_reconstruction,0.1/async,rmse,0.9257568484925308,0.9245030053521999,0.8421176681539589,1.0126199014959316,1000,paired source-video group resample,,,,,C0,-0.017977792804993564,-0.01938969460345763,-0.07420472957036398,0.036560155543958604, +C6_no_reconstruction,0.1/async,pearson,0.5936945080757141,0.5946870446205139,0.5264300525188446,0.6553369671106338,1000,paired source-video group resample,,,,,C0,0.07967853546142578,0.08199219405651093,0.031212711334228517,0.13282157257199287, +C6_no_reconstruction,0.3/single,accuracy,0.6002747252747253,0.6002878641761207,0.559726345083488,0.6422355822860117,1000,paired source-video group resample,,,,,C0,-0.005494505494505475,-0.004451077768385436,-0.04349193327864367,0.027913019836663906, +C6_no_reconstruction,0.3/single,macro_f1,0.5206449767886464,0.5197187980513638,0.48438421819503347,0.5550826791114251,1000,paired source-video group resample,,,,,C0,-0.04865427261980182,-0.04750248198311918,-0.09172706466784838,-0.009077057037226529, +C6_no_reconstruction,0.3/single,mae,0.703782320022583,0.7041794657707214,0.6531866580247879,0.7569875389337539,1000,paired source-video group resample,0.007959723472595215,0.0073938071727752686,-0.004646816849708557,0.02502852827310562,C0,-0.027348816394805908,-0.027734309434890747,-0.06770771592855454,0.011727604269981368, +C6_no_reconstruction,0.3/single,rmse,0.9444478707313719,0.9439549587189158,0.8649174760652101,1.0299511315801524,1000,paired source-video group resample,,,,,C0,0.004680295997827044,0.004561995549023867,-0.05852523407328612,0.06312180610449412, +C6_no_reconstruction,0.3/single,pearson,0.5792710781097412,0.5798234939575195,0.5125776499509811,0.6422992557287216,1000,paired source-video group resample,,,,,C0,0.05785548686981201,0.05806697905063629,0.0038426458835601808,0.11285488158464431, +C6_no_reconstruction,0.3/sync,accuracy,0.592032967032967,0.5923183690227689,0.5518560092476708,0.6335925809366212,1000,paired source-video group resample,,,,,C0,0.012362637362637319,0.012959131206408958,-0.02260590368866484,0.04701591301868661, +C6_no_reconstruction,0.3/sync,macro_f1,0.49867915829165493,0.4979720949980706,0.46800369533473096,0.5320529312037454,1000,paired source-video group resample,,,,,C0,-0.04142183114783288,-0.04055283679519178,-0.08172763193607835,0.0005195167456978935, +C6_no_reconstruction,0.3/sync,mae,0.7136086225509644,0.7132914066314697,0.6656482517719269,0.7658197343349457,1000,paired source-video group resample,0.017786026000976562,0.01809793710708618,-0.0008281096816062924,0.03793524503707885,C0,-0.039295077323913574,-0.03982764482498169,-0.08114957511425018,-0.0027217015624046346, +C6_no_reconstruction,0.3/sync,rmse,0.9357202484737509,0.9339652339110426,0.8576348665891794,1.016581448798069,1000,paired source-video group resample,,,,,C0,-0.026572467290526425,-0.027239971004746788,-0.08075452012781063,0.02090074448203468, +C6_no_reconstruction,0.3/sync,pearson,0.5889030694961548,0.5895508825778961,0.5233234733343124,0.6459899067878723,1000,paired source-video group resample,,,,,C0,0.09066814184188843,0.09153659641742706,0.046491888165473935,0.13963594883680341, +C6_no_reconstruction,0.3/partial,accuracy,0.5975274725274725,0.5979531069980399,0.556310987509758,0.6376862953832362,1000,paired source-video group resample,,,,,C0,0.0027472527472527375,0.002816906996443158,-0.0346310041238815,0.03994490358126723, +C6_no_reconstruction,0.3/partial,macro_f1,0.5091381972477246,0.5098303307097489,0.4711648806306814,0.5441027555469318,1000,paired source-video group resample,,,,,C0,-0.05409745039574476,-0.053061839619135465,-0.0982999690379976,-0.010115799998480562, +C6_no_reconstruction,0.3/partial,mae,0.708671510219574,0.709564596414566,0.6581668123602867,0.7625367805361748,1000,paired source-video group resample,0.012848913669586182,0.012689828872680664,-0.008069761097431183,0.03449654579162598,C0,-0.03788018226623535,-0.03798842430114746,-0.08075023144483566,0.007021638751029958, +C6_no_reconstruction,0.3/partial,rmse,0.943148824442679,0.9421967475868849,0.8545794798625612,1.0223890115687726,1000,paired source-video group resample,,,,,C0,-0.009649368821297077,-0.01052384485755209,-0.07682632336793904,0.048700676380509136, +C6_no_reconstruction,0.3/partial,pearson,0.5819876194000244,0.5819212794303894,0.5123929187655449,0.6453823402523994,1000,paired source-video group resample,,,,,C0,0.07327383756637573,0.07423461973667145,0.020316384732723236,0.1318066269159317, +C6_no_reconstruction,0.3/async,accuracy,0.6098901098901099,0.6096404204314955,0.5700473306062512,0.649930312303072,1000,paired source-video group resample,,,,,C0,0.030219780219780223,0.030868946456562962,-0.007590167984189715,0.07009170612683766, +C6_no_reconstruction,0.3/async,macro_f1,0.525559035291173,0.5256544398612254,0.4912141353599759,0.5600117932362613,1000,paired source-video group resample,,,,,C0,-0.020591435257501955,-0.01975369519128939,-0.06314517889591692,0.02239360072737087, +C6_no_reconstruction,0.3/async,mae,0.7013431787490845,0.7009817361831665,0.6493517383933067,0.7523402199149132,1000,paired source-video group resample,0.00552058219909668,0.005323052406311035,-0.014402690529823303,0.024107447266578673,C0,-0.06724023818969727,-0.06800463795661926,-0.11037461459636688,-0.02407689392566681, +C6_no_reconstruction,0.3/async,rmse,0.9232647651960552,0.9217003958827004,0.8411740114741184,1.0019436186856854,1000,paired source-video group resample,,,,,C0,-0.05984002935987487,-0.061278533959525316,-0.11835857332998591,-0.002823298910944218, +C6_no_reconstruction,0.3/async,pearson,0.5978975296020508,0.5989178121089935,0.5281966626644135,0.6637837007641793,1000,paired source-video group resample,,,,,C0,0.11105158925056458,0.1121150553226471,0.05980259776115417,0.1654071919620037, +C6_no_reconstruction,0.5/single,accuracy,0.6057692307692307,0.6057057185692868,0.5653449764717661,0.6463646897253095,1000,paired source-video group resample,,,,,C0,0.019230769230769162,0.019382325135923917,-0.02216220375500155,0.054020226933786594, +C6_no_reconstruction,0.5/single,macro_f1,0.521565604364054,0.5211696731384515,0.4853333181902831,0.5570982290845086,1000,paired source-video group resample,,,,,C0,-0.03345167779782898,-0.03285784326849048,-0.07715692889166743,0.00758240536733762, +C6_no_reconstruction,0.5/single,mae,0.7003881931304932,0.7004623413085938,0.6516345962882042,0.7549573078751564,1000,paired source-video group resample,0.004565596580505371,0.004457414150238037,-0.007535707950592041,0.019880063831806183,C0,-0.04864013195037842,-0.04897549748420715,-0.08995816707611085,-0.006528341770172122, +C6_no_reconstruction,0.5/single,rmse,0.9394121061954498,0.9378222206118607,0.8558315057847241,1.0275749212720109,1000,paired source-video group resample,,,,,C0,-0.020238731317083758,-0.02236512532341356,-0.08033314705085455,0.038476345471925695, +C6_no_reconstruction,0.5/single,pearson,0.5878214240074158,0.5889238715171814,0.5162480935454369,0.6524826392531394,1000,paired source-video group resample,,,,,C0,0.07958817481994629,0.0815889835357666,0.026595011353492737,0.13267479091882706, +C6_no_reconstruction,0.5/sync,accuracy,0.603021978021978,0.6036838612502982,0.5618867812860652,0.6453429663390596,1000,paired source-video group resample,,,,,C0,0.009615384615384581,0.010487038491751755,-0.02994334197767504,0.04369229878092248, +C6_no_reconstruction,0.5/sync,macro_f1,0.5103805957593329,0.5098532217330716,0.47411821618306477,0.5453559458588176,1000,paired source-video group resample,,,,,C0,-0.05312294363685055,-0.0525746552389367,-0.09788847720024461,-0.014165318951977373, +C6_no_reconstruction,0.5/sync,mae,0.7190809845924377,0.7190803289413452,0.669126358628273,0.7702048316597938,1000,paired source-video group resample,0.02325838804244995,0.023453086614608765,0.0031349807977676396,0.04312411397695541,C0,-0.06821328401565552,-0.06949171423912048,-0.11132173389196395,-0.02606598883867264, +C6_no_reconstruction,0.5/sync,rmse,0.9376486978225157,0.9341441323393087,0.8555448283815249,1.0186369323554094,1000,paired source-video group resample,,,,,C0,-0.06472284110367277,-0.0667263709692108,-0.12220305145771657,-0.008707487913603457, +C6_no_reconstruction,0.5/sync,pearson,0.5898188948631287,0.5910450220108032,0.5220049679279327,0.6520001381635666,1000,paired source-video group resample,,,,,C0,0.11016061902046204,0.11142131686210632,0.05852596908807754,0.15958839505910874, +C6_no_reconstruction,0.5/partial,accuracy,0.6057692307692307,0.6051692634143466,0.5636844050258684,0.6467197616396553,1000,paired source-video group resample,,,,,C0,0.02060439560439553,0.02185796429044662,-0.018409259781415572,0.05791205356188684, +C6_no_reconstruction,0.5/partial,macro_f1,0.5154088848751237,0.5145882664558656,0.47987356280679455,0.5496337847872139,1000,paired source-video group resample,,,,,C0,-0.036187345864307385,-0.03527035314067961,-0.08157541165158572,0.0076475070283494526, +C6_no_reconstruction,0.5/partial,mae,0.7154918909072876,0.7160096168518066,0.6686419010162353,0.7663619160652161,1000,paired source-video group resample,0.019669294357299805,0.019778668880462646,0.0011587783694267273,0.03628048151731491,C0,-0.06996721029281616,-0.0710250735282898,-0.11524091213941574,-0.0250303715467453, +C6_no_reconstruction,0.5/partial,rmse,0.9406249417022992,0.9394536167024281,0.8650559534084261,1.0220722583526904,1000,paired source-video group resample,,,,,C0,-0.058985853634149654,-0.061510862511074405,-0.1256605497495668,0.003793565270356052, +C6_no_reconstruction,0.5/partial,pearson,0.5862635970115662,0.5873501598834991,0.5206451117992401,0.6467884749174118,1000,paired source-video group resample,,,,,C0,0.10485798120498657,0.1062563806772232,0.04526093825697899,0.16494970843195914, +C6_no_reconstruction,0.5/async,accuracy,0.5906593406593407,0.5911364128724244,0.5482927839606749,0.6336502251727619,1000,paired source-video group resample,,,,,C0,0.017857142857142905,0.018718512221922723,-0.018549268856393557,0.05409837092731828, +C6_no_reconstruction,0.5/async,macro_f1,0.4909340577214805,0.49085591316559796,0.4529520447901854,0.5252749619098335,1000,paired source-video group resample,,,,,C0,-0.049713938713046246,-0.04831248412200165,-0.09022126263315575,-0.009610342757061942, +C6_no_reconstruction,0.5/async,mae,0.7356505393981934,0.7349706888198853,0.6865068569779396,0.7926585331559182,1000,paired source-video group resample,0.039827942848205566,0.04042816162109375,0.018352548778057098,0.06115699112415313,C0,-0.057614147663116455,-0.05800151824951172,-0.10346926152706146,-0.01306344419717789, +C6_no_reconstruction,0.5/async,rmse,0.9709581619583614,0.9681973868791497,0.8838462202852256,1.0562134874516507,1000,paired source-video group resample,,,,,C0,-0.03236957168580945,-0.03375047257277408,-0.09106854734733093,0.03146163312546493, +C6_no_reconstruction,0.5/async,pearson,0.5602580904960632,0.5619353950023651,0.4883867844939232,0.6277107775211335,1000,paired source-video group resample,,,,,C0,0.08576339483261108,0.0876150131225586,0.029457331448793412,0.14153081253170965, +C6_no_reconstruction,0.7/single,accuracy,0.5892857142857143,0.5886185401584263,0.549719730038819,0.6300034246575342,1000,paired source-video group resample,,,,,C0,0.004120879120879106,0.005280548758809678,-0.03338948787061993,0.04294983740816574, +C6_no_reconstruction,0.7/single,macro_f1,0.4937095651523246,0.49390779718070893,0.46058682125044403,0.5245254068061638,1000,paired source-video group resample,,,,,C0,-0.05760140735017244,-0.056280417730205035,-0.09918270225110845,-0.012785657921114621, +C6_no_reconstruction,0.7/single,mae,0.7239422798156738,0.7249148786067963,0.6758632570505142,0.7743990182876587,1000,paired source-video group resample,0.028119683265686035,0.028295785188674927,0.010219092667102815,0.04521540701389313,C0,-0.06400632858276367,-0.06330391764640808,-0.11267685145139694,-0.016777162253856687, +C6_no_reconstruction,0.7/single,rmse,0.9459090124149964,0.9436947084977317,0.8669198480495307,1.0254766741083536,1000,paired source-video group resample,,,,,C0,-0.06441498300893211,-0.06546519579285143,-0.13393049124444129,0.0022501894101047185, +C6_no_reconstruction,0.7/single,pearson,0.5851625204086304,0.5859684646129608,0.5176752850413322,0.6464971274137497,1000,paired source-video group resample,,,,,C0,0.11252230405807495,0.11370842158794403,0.05163313001394272,0.17346914038062095, +C6_no_reconstruction,0.7/sync,accuracy,0.592032967032967,0.5924249927426102,0.552596619776563,0.6353323434932018,1000,paired source-video group resample,,,,,C0,0.009615384615384581,0.01042345719252502,-0.027708590361352255,0.04662180541115595, +C6_no_reconstruction,0.7/sync,macro_f1,0.4835011880150848,0.48229984142829946,0.44933654543876356,0.5185309394835411,1000,paired source-video group resample,,,,,C0,-0.06543831208527928,-0.06486709345213781,-0.10753787132615442,-0.02370852365011574, +C6_no_reconstruction,0.7/sync,mae,0.7612572908401489,0.7616379261016846,0.7078869417309761,0.8145117148756981,1000,paired source-video group resample,0.06543469429016113,0.06520134210586548,0.03823104500770569,0.0929135113954544,C0,-0.022114336490631104,-0.021562546491622925,-0.0731981337070465,0.029057143628597244, +C6_no_reconstruction,0.7/sync,rmse,0.9936205809669257,0.9922537792486399,0.9129359006363931,1.0813338828705075,1000,paired source-video group resample,,,,,C0,-0.0265348605903718,-0.026917536674208264,-0.08866429109738579,0.03393103799273377, +C6_no_reconstruction,0.7/sync,pearson,0.545553982257843,0.5457391738891602,0.47951278686523435,0.6072404101490975,1000,paired source-video group resample,,,,,C0,0.06710892915725708,0.06739519536495209,0.010531093925237656,0.12339756712317466, +C6_no_reconstruction,0.7/partial,accuracy,0.6016483516483516,0.6023345059162136,0.5597885130638087,0.6426554650453072,1000,paired source-video group resample,,,,,C0,0.008241758241758212,0.00861471861471863,-0.03509519210871215,0.04964069798006349, +C6_no_reconstruction,0.7/partial,macro_f1,0.49671535080173523,0.4958906218720371,0.46277099377062986,0.5310659362634447,1000,paired source-video group resample,,,,,C0,-0.06729808641487522,-0.0660261782353525,-0.11452552717033017,-0.019639305777445153, +C6_no_reconstruction,0.7/partial,mae,0.7489723563194275,0.7484162747859955,0.6973376154899598,0.80584567040205,1000,paired source-video group resample,0.0531497597694397,0.05330681800842285,0.024607035517692565,0.08039242029190063,C0,-0.048618972301483154,-0.04794040322303772,-0.10048371106386185,0.004543457925319652, +C6_no_reconstruction,0.7/partial,rmse,0.9816708433734875,0.9806974527311626,0.8983693113400931,1.0698049829948433,1000,paired source-video group resample,,,,,C0,-0.035785848393428354,-0.03639894853843434,-0.09886138257899979,0.02905125235607648, +C6_no_reconstruction,0.7/partial,pearson,0.5501648187637329,0.5509316325187683,0.47910491600632665,0.6166832238435745,1000,paired source-video group resample,,,,,C0,0.057687997817993164,0.0582202672958374,-0.0009498290717601771,0.11751230210065841, +C6_no_reconstruction,0.7/async,accuracy,0.6016483516483516,0.6019772119298498,0.5618833056478405,0.6440071428571429,1000,paired source-video group resample,,,,,C0,0.02335164835164827,0.02353755906794852,-0.0151355322764506,0.06442177163691246, +C6_no_reconstruction,0.7/async,macro_f1,0.4913258251714236,0.49095136565466546,0.45946001362093797,0.5230216535860422,1000,paired source-video group resample,,,,,C0,-0.062472237836480204,-0.06113330254765004,-0.10450357013013217,-0.019965354575085765, +C6_no_reconstruction,0.7/async,mae,0.7631208896636963,0.7628655731678009,0.7119999468326569,0.8181118220090866,1000,paired source-video group resample,0.0672982931137085,0.06699061393737793,0.0413764089345932,0.09406275600194931,C0,-0.053338706493377686,-0.05356666445732117,-0.10400903522968293,-0.001850567758083344, +C6_no_reconstruction,0.7/async,rmse,0.9862647612208,0.9856204808664659,0.9099094745558057,1.0633920289768366,1000,paired source-video group resample,,,,,C0,-0.05453011755355419,-0.05632615892300186,-0.12565868336519542,0.012118124068425874, +C6_no_reconstruction,0.7/async,pearson,0.5544081330299377,0.5557579100131989,0.4905871316790581,0.6165219947695731,1000,paired source-video group resample,,,,,C0,0.07521197199821472,0.07667076587677002,0.012432076036930084,0.13568276017904282, +C6_no_reconstruction,0.3/modality_T,accuracy,0.6002747252747253,0.600273813941459,0.5614901543961339,0.6380040636613827,1000,paired source-video group resample,,,,,C0,0.013736263736263687,0.014583059445832158,-0.02276318603538,0.04836709787649494, +C6_no_reconstruction,0.3/modality_T,macro_f1,0.5072452753711304,0.5072671222146805,0.47391253943863176,0.5382211884499295,1000,paired source-video group resample,,,,,C0,-0.03951803807257637,-0.03834483404941197,-0.08171123784976024,0.0017609214032805152, +C6_no_reconstruction,0.3/modality_T,mae,0.7134279608726501,0.7132214903831482,0.6646231845021248,0.7653302624821663,1000,paired source-video group resample,0.017605364322662354,0.017633497714996338,-0.0024992600083351135,0.03653452843427658,C0,-0.036695778369903564,-0.03672969341278076,-0.07808723747730255,0.009173944592475891, +C6_no_reconstruction,0.3/modality_T,rmse,0.9437716197385886,0.9416663889119097,0.8570370967205123,1.0259088264887541,1000,paired source-video group resample,,,,,C0,-0.018897711915532023,-0.019614522572560356,-0.08020220871096233,0.043106504935015846, +C6_no_reconstruction,0.3/modality_T,pearson,0.5802155137062073,0.5803194642066956,0.5102706536650657,0.644300203025341,1000,paired source-video group resample,,,,,C0,0.07845312356948853,0.07999703288078308,0.023288001865148546,0.13482860401272773, +C6_no_reconstruction,0.3/modality_A,accuracy,0.6016483516483516,0.6014761956640158,0.5618748781913857,0.6443344779234851,1000,paired source-video group resample,,,,,C0,0.015109890109890056,0.01608483715241643,-0.022754329004328985,0.05047817878650077, +C6_no_reconstruction,0.3/modality_A,macro_f1,0.5199799259397838,0.520136287498961,0.4855288717955636,0.5545582072923695,1000,paired source-video group resample,,,,,C0,-0.03150184272011347,-0.02986144106101568,-0.0740175889367767,0.009528483867340114, +C6_no_reconstruction,0.3/modality_A,mae,0.6972677707672119,0.697597473859787,0.6475002929568291,0.7515588298439979,1000,paired source-video group resample,0.001445174217224121,0.0013778209686279297,-0.0015966415405273438,0.004476188123226164,C0,-0.03289926052093506,-0.033307552337646484,-0.07411524057388305,0.005035452544689177, +C6_no_reconstruction,0.3/modality_A,rmse,0.9354649071831923,0.9347405187985087,0.8506115459965365,1.020856017899952,1000,paired source-video group resample,,,,,C0,0.001152546867112414,-0.000343173144731701,-0.057946862504605956,0.06034039559617243, +C6_no_reconstruction,0.3/modality_A,pearson,0.5884665250778198,0.5890539884567261,0.5204186990857125,0.6496650442481041,1000,paired source-video group resample,,,,,C0,0.06572949886322021,0.06693020462989807,0.01444903016090393,0.11780844628810883, +C6_no_reconstruction,0.3/modality_V,accuracy,0.6016483516483516,0.6017280852062254,0.5609272885704604,0.6432766587250017,1000,paired source-video group resample,,,,,C0,0.013736263736263687,0.014416800648610062,-0.02351508839860131,0.05022033203525308, +C6_no_reconstruction,0.3/modality_V,macro_f1,0.5202926276965792,0.5204018057997192,0.4854070475051152,0.5552978777636753,1000,paired source-video group resample,,,,,C0,-0.030800718286269513,-0.02927005256680454,-0.07323881907024601,0.011781167564147281, +C6_no_reconstruction,0.3/modality_V,mae,0.6950706839561462,0.6956386864185333,0.6448626726865768,0.749152560532093,1000,paired source-video group resample,-0.0007519125938415527,-0.0005843043327331543,-0.002493259310722351,0.0004536733031272886,C0,-0.03826242685317993,-0.03823411464691162,-0.07969615161418915,-0.0007913976907730256, +C6_no_reconstruction,0.3/modality_V,rmse,0.9329375510684372,0.9319338060376783,0.8476097608651332,1.018864565546721,1000,paired source-video group resample,,,,,C0,-0.004855181244189155,-0.0064991083678968,-0.06413287791689677,0.05488511719363961, +C6_no_reconstruction,0.3/modality_V,pearson,0.5886265635490417,0.5895117819309235,0.5200189217925072,0.6505468532443046,1000,paired source-video group resample,,,,,C0,0.06918072700500488,0.07009263336658478,0.017952145636081697,0.12039183229207992, +C6_no_reconstruction,0.3/modality_TA,accuracy,0.5961538461538461,0.5967196059839865,0.5546083172147002,0.6362350299875237,1000,paired source-video group resample,,,,,C0,0.009615384615384581,0.010655596443741588,-0.028581280788177347,0.04654813712017102, +C6_no_reconstruction,0.3/modality_TA,macro_f1,0.5065902931756591,0.5056025533359227,0.47217497441495443,0.5405716911175215,1000,paired source-video group resample,,,,,C0,-0.04760799398463378,-0.0465887894797567,-0.09241797402512636,-0.005900985782493881, +C6_no_reconstruction,0.3/modality_TA,mae,0.7176585793495178,0.7185400724411011,0.668278893828392,0.7708938300609588,1000,paired source-video group resample,0.02183598279953003,0.021763980388641357,0.003173661231994629,0.04271617531776428,C0,-0.057926952838897705,-0.05872666835784912,-0.10129168629646301,-0.016358146071434022, +C6_no_reconstruction,0.3/modality_TA,rmse,0.953675783201997,0.9526528725812127,0.8669660170916866,1.0370081822596762,1000,paired source-video group resample,,,,,C0,-0.016945303151439828,-0.018503779037496837,-0.08067982133201262,0.044367635515995874, +C6_no_reconstruction,0.3/modality_TA,pearson,0.5720103979110718,0.5724660456180573,0.4995699696242809,0.6351143196225166,1000,paired source-video group resample,,,,,C0,0.07357043027877808,0.07377636432647705,0.018554048985242842,0.13360835388302802, +C6_no_reconstruction,0.3/modality_TV,accuracy,0.5989010989010989,0.5990225893934882,0.5579764745472344,0.6401755766105328,1000,paired source-video group resample,,,,,C0,0.016483516483516425,0.017457489372343038,-0.021617704718775162,0.05302522508035435, +C6_no_reconstruction,0.3/modality_TV,macro_f1,0.5037696301538707,0.5038456461476408,0.4696326547378405,0.5374214851861254,1000,paired source-video group resample,,,,,C0,-0.0410749578349876,-0.039542318460987214,-0.08204277277710198,-0.0007585160010206269, +C6_no_reconstruction,0.3/modality_TV,mae,0.7069001197814941,0.705607533454895,0.6585742086172104,0.758942648768425,1000,paired source-video group resample,0.011077523231506348,0.010506212711334229,-0.009649047255516052,0.033139726519584654,C0,-0.05377364158630371,-0.05405837297439575,-0.09203779846429824,-0.013623166084289567, +C6_no_reconstruction,0.3/modality_TV,rmse,0.928127293953164,0.9251127928014726,0.848993858067315,1.0102437171457679,1000,paired source-video group resample,,,,,C0,-0.03943979685272492,-0.041153845142981205,-0.09482629201184649,0.015266157986548278, +C6_no_reconstruction,0.3/modality_TV,pearson,0.5936524271965027,0.5950827598571777,0.5276267975568771,0.6527563452720642,1000,paired source-video group resample,,,,,C0,0.09466561675071716,0.0958687961101532,0.046848309040069584,0.14631040692329406, +C6_no_reconstruction,0.3/modality_AV,accuracy,0.6016483516483516,0.6014718614718615,0.562830697383308,0.6422250316055625,1000,paired source-video group resample,,,,,C0,0.006868131868131844,0.007884362680683321,-0.028835256327699423,0.042939904385121144, +C6_no_reconstruction,0.3/modality_AV,macro_f1,0.5182741835926872,0.5184206640079014,0.48512175844107325,0.5513761682200322,1000,paired source-video group resample,,,,,C0,-0.041424022646424974,-0.03981512291497752,-0.08253764876254004,-0.0008734570419697817, +C6_no_reconstruction,0.3/modality_AV,mae,0.6964878439903259,0.6970109343528748,0.6474796876311302,0.7508383765816689,1000,paired source-video group resample,0.0006652474403381348,0.0006784200668334961,-0.00353299081325531,0.005034451186656948,C0,-0.041492998600006104,-0.0413936972618103,-0.0801023468375206,-0.0030207395553588884, +C6_no_reconstruction,0.3/modality_AV,rmse,0.9337154612351619,0.9328526047355498,0.8485444701346018,1.0196983286885817,1000,paired source-video group resample,,,,,C0,-0.008319766266428608,-0.01016527303188336,-0.06831912470866118,0.050633870994409545, +C6_no_reconstruction,0.3/modality_AV,pearson,0.5900610089302063,0.5910139083862305,0.5215256705880165,0.6516669943928719,1000,paired source-video group resample,,,,,C0,0.0745270848274231,0.07554498314857483,0.021893969178199767,0.12573410496115683, +C6_no_reconstruction,0.3/modality_TAV,accuracy,0.5906593406593407,0.5910637893335868,0.5507651062838753,0.633085485680729,1000,paired source-video group resample,,,,,C0,0.009615384615384581,0.010302678497387807,-0.025070666507572798,0.04367722257017123, +C6_no_reconstruction,0.3/modality_TAV,macro_f1,0.4981992029683943,0.4979436609785298,0.46488534398838277,0.5319998241895671,1000,paired source-video group resample,,,,,C0,-0.04627869563588788,-0.045441842421558465,-0.0846723693556232,-0.005561073965158345, +C6_no_reconstruction,0.3/modality_TAV,mae,0.7205085158348083,0.7211007475852966,0.6700850769877433,0.7753981485962868,1000,paired source-video group resample,0.024685919284820557,0.024241328239440918,0.009245531260967254,0.04226437807083129,C0,-0.05042320489883423,-0.050918519496917725,-0.09273956716060638,-0.006801813840866089, +C6_no_reconstruction,0.3/modality_TAV,rmse,0.9581113675734635,0.9569004292472953,0.871292724878957,1.0448431808029774,1000,paired source-video group resample,,,,,C0,-0.021926394087905643,-0.02343627074415411,-0.08536891137381122,0.0382163419729184, +C6_no_reconstruction,0.3/modality_TAV,pearson,0.5690979957580566,0.5683181583881378,0.4996216155588627,0.6322312355041504,1000,paired source-video group resample,,,,,C0,0.07878848910331726,0.08106398582458496,0.02120269536972046,0.13519115671515464, +C6_no_reconstruction,0.3/location_start_T,accuracy,0.6112637362637363,0.6112618949415196,0.5702493038554262,0.6526450742240216,1000,paired source-video group resample,,,,,C0,0.019230769230769273,0.019359300406014412,-0.02069036959420846,0.05806488530357429, +C6_no_reconstruction,0.3/location_start_T,macro_f1,0.5306775590681346,0.5318011498753434,0.4920778723690121,0.5699038379346943,1000,paired source-video group resample,,,,,C0,-0.03051361450018819,-0.030143967884801393,-0.07673054059426461,0.018382955145280575, +C6_no_reconstruction,0.3/location_start_T,mae,0.7143445014953613,0.7134253680706024,0.6635509178042411,0.7660413295030594,1000,paired source-video group resample,0.018521904945373535,0.01836833357810974,-0.0046179905533790585,0.04300687164068221,C0,-0.05491667985916138,-0.05540984869003296,-0.09787418991327286,-0.011271966993808794, +C6_no_reconstruction,0.3/location_start_T,rmse,0.9498935388843496,0.9480360535592737,0.8675572920442193,1.0284106175677075,1000,paired source-video group resample,,,,,C0,-0.025420390727710518,-0.025782486938055016,-0.08693721559634247,0.035912694341994705, +C6_no_reconstruction,0.3/location_start_T,pearson,0.5800430178642273,0.5811472833156586,0.5166231125593186,0.6376386463642121,1000,paired source-video group resample,,,,,C0,0.09749355912208557,0.09780342876911163,0.038559286296367644,0.1536217875778675, +C6_no_reconstruction,0.3/location_middle_T,accuracy,0.5975274725274725,0.5973855092276145,0.5585574776785714,0.6388196015970711,1000,paired source-video group resample,,,,,C0,0.008241758241758212,0.009265586017436156,-0.029461846524937055,0.04415415891690807, +C6_no_reconstruction,0.3/location_middle_T,macro_f1,0.5109217211763902,0.5107142694364472,0.476183068742702,0.544654907257549,1000,paired source-video group resample,,,,,C0,-0.03987978250992663,-0.038987977629144466,-0.08528260455541924,0.005435494771406493, +C6_no_reconstruction,0.3/location_middle_T,mae,0.7166770100593567,0.7166539132595062,0.6646173894405365,0.7704966917634011,1000,paired source-video group resample,0.020854413509368896,0.02054336667060852,-0.0007646083831787105,0.042653162777423856,C0,-0.03209036588668823,-0.03221908211708069,-0.0750023066997528,0.009258180856704696, +C6_no_reconstruction,0.3/location_middle_T,rmse,0.9623758359807074,0.961429604700629,0.8736280030189385,1.0483928846451578,1000,paired source-video group resample,,,,,C0,0.0009185612298922008,0.0003975950690221497,-0.06175843023111088,0.062005528474132994, +C6_no_reconstruction,0.3/location_middle_T,pearson,0.5646106600761414,0.5651961266994476,0.49708580523729323,0.6299441799521446,1000,paired source-video group resample,,,,,C0,0.05765634775161743,0.05861520767211914,0.0011825397610664371,0.11296885386109351, +C6_no_reconstruction,0.3/location_end_T,accuracy,0.6057692307692307,0.6059324992668168,0.5639604597817932,0.6478475562042255,1000,paired source-video group resample,,,,,C0,0.03159340659340659,0.03136351054996056,-0.01102196576972149,0.07001666500016665, +C6_no_reconstruction,0.3/location_end_T,macro_f1,0.5134057664136272,0.5124973595719328,0.47578526691739104,0.5496614906209832,1000,paired source-video group resample,,,,,C0,-0.024562407516265816,-0.023635390608642448,-0.07157802273716284,0.021637976658669504, +C6_no_reconstruction,0.3/location_end_T,mae,0.7019791007041931,0.7025491893291473,0.650325384736061,0.7574762523174285,1000,paired source-video group resample,0.006156504154205322,0.00623708963394165,-0.01233503371477127,0.025147841870784744,C0,-0.0671737790107727,-0.06722593307495117,-0.10965280085802079,-0.026039399206638347, +C6_no_reconstruction,0.3/location_end_T,rmse,0.9213564756086683,0.9194647590745901,0.8442125630960171,1.0038293089136634,1000,paired source-video group resample,,,,,C0,-0.05617609311937244,-0.05761065059742371,-0.11645488211785876,0.005114437009495319, +C6_no_reconstruction,0.3/location_end_T,pearson,0.591676652431488,0.5919802784919739,0.5229316458106041,0.6513377174735069,1000,paired source-video group resample,,,,,C0,0.08499205112457275,0.08609195053577423,0.02981632053852081,0.13920477777719498, +C6_no_reconstruction,0.3/span_long_T,accuracy,0.6098901098901099,0.6099552167614741,0.5682794353223869,0.6492632639721102,1000,paired source-video group resample,,,,,C0,0.03159340659340659,0.032122651188696394,-0.006961672698938884,0.06799083104744484, +C6_no_reconstruction,0.3/span_long_T,macro_f1,0.5294628957004927,0.5296770325041817,0.4919338719048745,0.5657912126478045,1000,paired source-video group resample,,,,,C0,-0.010641579369508491,-0.010754486531801166,-0.05573453729962699,0.035816251968874835, +C6_no_reconstruction,0.3/span_long_T,mae,0.7097036242485046,0.708601325750351,0.658559262752533,0.7674965590238572,1000,paired source-video group resample,0.013881027698516846,0.01360023021697998,-0.01064838021993637,0.04144228994846343,C0,-0.039417922496795654,-0.0395713746547699,-0.07836540043354034,0.0009934753179549883, +C6_no_reconstruction,0.3/span_long_T,rmse,0.9483153200086865,0.9454982193879615,0.8681903613541241,1.0391550517639299,1000,paired source-video group resample,,,,,C0,-0.015582601016183695,-0.016196576273397434,-0.07532923473748376,0.0449154661014831, +C6_no_reconstruction,0.3/span_long_T,pearson,0.5748408436775208,0.5755937695503235,0.5085138633847237,0.6335016891360282,1000,paired source-video group resample,,,,,C0,0.07486173510551453,0.07612673938274384,0.023258632421493532,0.1289138004183769, +C6_no_reconstruction,0.3/span_multi_short_T,accuracy,0.6016483516483516,0.6023671068067695,0.5596543977773328,0.6434875087863168,1000,paired source-video group resample,,,,,C0,0.013736263736263687,0.014809036777117646,-0.0245107621850244,0.05156574911884899, +C6_no_reconstruction,0.3/span_multi_short_T,macro_f1,0.5183272955146325,0.5179380905033026,0.48100952998002133,0.5560100308778317,1000,paired source-video group resample,,,,,C0,-0.033217159771985805,-0.03199138850721117,-0.08012409821844567,0.011097203607880761, +C6_no_reconstruction,0.3/span_multi_short_T,mae,0.7004514336585999,0.7003215253353119,0.6491809487342834,0.753208801150322,1000,paired source-video group resample,0.0046288371086120605,0.004791200160980225,-0.010900551080703735,0.019429646432399746,C0,-0.051004111766815186,-0.05210885405540466,-0.09361851513385773,-0.008832266926765473, +C6_no_reconstruction,0.3/span_multi_short_T,rmse,0.9246789993870027,0.9228395479861347,0.8406337650168976,1.011215195050125,1000,paired source-video group resample,,,,,C0,-0.03601910629337879,-0.038275077230453924,-0.09816416050149847,0.02538773801636637, +C6_no_reconstruction,0.3/span_multi_short_T,pearson,0.5944291949272156,0.5934838950634003,0.5230156779289246,0.6606207668781281,1000,paired source-video group resample,,,,,C0,0.09282064437866211,0.09306727349758148,0.03295539170503616,0.14813712760806083, +C6_no_reconstruction,0.3/location_start_A,accuracy,0.5934065934065934,0.5925423560482892,0.5528410797103868,0.6349431818181818,1000,paired source-video group resample,,,,,C0,0.009615384615384581,0.010437091503268048,-0.025610989846470786,0.04348692187770653, +C6_no_reconstruction,0.3/location_start_A,macro_f1,0.5082272451336022,0.5080743525172463,0.47523940384121044,0.5428507239715388,1000,paired source-video group resample,,,,,C0,-0.04855291526362504,-0.04699931689374556,-0.0857665618043781,-0.012356363009626416, +C6_no_reconstruction,0.3/location_start_A,mae,0.7033993005752563,0.7037713825702667,0.6544503077864647,0.7583996072411537,1000,paired source-video group resample,0.007576704025268555,0.0077574849128723145,0.002105320990085602,0.013639329373836516,C0,-0.03159904479980469,-0.032588064670562744,-0.07076332718133926,0.008390660583972922, +C6_no_reconstruction,0.3/location_start_A,rmse,0.9406286486684808,0.9391626219780307,0.8570189900695632,1.026408000554078,1000,paired source-video group resample,,,,,C0,-0.00016869902618676935,-0.0017179265630469231,-0.057960739900097154,0.056805722853089685, +C6_no_reconstruction,0.3/location_start_A,pearson,0.5856781601905823,0.5863075256347656,0.5161584720015526,0.6465736478567123,1000,paired source-video group resample,,,,,C0,0.06793451309204102,0.06894546747207642,0.017482712864875793,0.12043658643960953, +C6_no_reconstruction,0.3/location_middle_A,accuracy,0.6002747252747253,0.6002855139863132,0.5600913640068834,0.6419899036727965,1000,paired source-video group resample,,,,,C0,0.013736263736263687,0.014794895729315916,-0.023058937691094687,0.051261670257515074, +C6_no_reconstruction,0.3/location_middle_A,macro_f1,0.5156745016208303,0.5159935245046362,0.4808918381227074,0.5511553781047988,1000,paired source-video group resample,,,,,C0,-0.03808832170721044,-0.03563957093876463,-0.08157451896107598,0.005723402166508242, +C6_no_reconstruction,0.3/location_middle_A,mae,0.7011321783065796,0.7017497718334198,0.6512846618890762,0.7546981766819953,1000,paired source-video group resample,0.005309581756591797,0.005164206027984619,0.002330830693244934,0.008820830285549164,C0,-0.03289109468460083,-0.03319752216339111,-0.0735092967748642,0.005700848996639234, +C6_no_reconstruction,0.3/location_middle_A,rmse,0.9369817572927718,0.9360386744373741,0.851180884025718,1.0225040998612647,1000,paired source-video group resample,,,,,C0,0.0002028216391337656,-0.0009303446090881962,-0.06012480018929942,0.058851403711528756, +C6_no_reconstruction,0.3/location_middle_A,pearson,0.5883570909500122,0.5892817676067352,0.5203455537557602,0.6505161672830582,1000,paired source-video group resample,,,,,C0,0.06799584627151489,0.06946378946304321,0.015924493968486785,0.12111821100115776, +C6_no_reconstruction,0.3/location_end_A,accuracy,0.6002747252747253,0.6005344080992991,0.5604122003508089,0.6421126571217315,1000,paired source-video group resample,,,,,C0,0.01098901098901095,0.011720956146108408,-0.02643208615274017,0.046970724770342316, +C6_no_reconstruction,0.3/location_end_A,macro_f1,0.5176057623064478,0.5178814669300167,0.483029865380548,0.5525074807138538,1000,paired source-video group resample,,,,,C0,-0.03579339895861089,-0.0342032844989863,-0.07699386992873154,0.005590999286030268, +C6_no_reconstruction,0.3/location_end_A,mae,0.6970194578170776,0.697660893201828,0.647500890493393,0.7516730457544327,1000,paired source-video group resample,0.0011968612670898438,0.0010832250118255615,-0.00012624412775039673,0.0029576927423477163,C0,-0.0377274751663208,-0.037801384925842285,-0.07804869562387466,-0.00012400597333908268, +C6_no_reconstruction,0.3/location_end_A,rmse,0.934360747723024,0.9336458611025791,0.8493557080541827,1.019450551009911,1000,paired source-video group resample,,,,,C0,-0.0033086731053684204,-0.004875542740809147,-0.06318945116425811,0.05603405091356633, +C6_no_reconstruction,0.3/location_end_A,pearson,0.5887131690979004,0.5896892547607422,0.5197553917765617,0.65077895373106,1000,paired source-video group resample,,,,,C0,0.06976181268692017,0.07100501656532288,0.01877470314502716,0.1209225758910179, +C6_no_reconstruction,0.3/span_long_A,accuracy,0.5947802197802198,0.5943915522228775,0.5538802134086923,0.6356236253745043,1000,paired source-video group resample,,,,,C0,0.006868131868131844,0.008374044552488247,-0.02937372318692546,0.041346561764819344, +C6_no_reconstruction,0.3/span_long_A,macro_f1,0.5082131513799591,0.5085290500083883,0.47537058547946043,0.5416934847788131,1000,paired source-video group resample,,,,,C0,-0.046124129273110936,-0.04466943130196366,-0.08766848088857167,-0.00869378591894608, +C6_no_reconstruction,0.3/span_long_A,mae,0.7017729878425598,0.7027618288993835,0.6534905642271042,0.7550497144460677,1000,paired source-video group resample,0.0059503912925720215,0.00584036111831665,0.001708240807056427,0.01089041084051132,C0,-0.03488588333129883,-0.03517535328865051,-0.07483797371387482,0.003944317996501913, +C6_no_reconstruction,0.3/span_long_A,rmse,0.9374224948634621,0.9364585765723628,0.8532995027314489,1.0235123545590152,1000,paired source-video group resample,,,,,C0,-0.0005305816899005,-0.0024996163026238527,-0.0590701350869709,0.05815403616510109, +C6_no_reconstruction,0.3/span_long_A,pearson,0.5876383185386658,0.5887414515018463,0.5194365173578263,0.6488138511776924,1000,paired source-video group resample,,,,,C0,0.07010841369628906,0.07137995958328247,0.02011254131793976,0.1207388162612915, +C6_no_reconstruction,0.3/span_multi_short_A,accuracy,0.5989010989010989,0.59857345923444,0.5587410706108618,0.6412815388979741,1000,paired source-video group resample,,,,,C0,0.004120879120879106,0.00567377028071081,-0.03252176466523878,0.03862336051891065, +C6_no_reconstruction,0.3/span_multi_short_A,macro_f1,0.5146589396436304,0.5148007057771414,0.4806373698656552,0.5481600528285259,1000,paired source-video group resample,,,,,C0,-0.045618895940377935,-0.04354743923204177,-0.08635472451608948,-0.005261700370972018, +C6_no_reconstruction,0.3/span_multi_short_A,mae,0.6984926462173462,0.6991333365440369,0.6494137525558472,0.7535555049777031,1000,paired source-video group resample,0.0026700496673583984,0.002589970827102661,-0.0007476910948753356,0.006246051192283629,C0,-0.03763139247894287,-0.03806430101394653,-0.07825032621622086,0.000539021193981153, +C6_no_reconstruction,0.3/span_multi_short_A,rmse,0.9356634907523048,0.9343509405982707,0.8516465502382636,1.0210848115088047,1000,paired source-video group resample,,,,,C0,-0.00598265889299332,-0.007427229453198958,-0.06657559844381877,0.05292244883312937, +C6_no_reconstruction,0.3/span_multi_short_A,pearson,0.5883760452270508,0.5891917943954468,0.5202556803822518,0.6499073341488838,1000,paired source-video group resample,,,,,C0,0.07207566499710083,0.0731239914894104,0.021404150128364566,0.1246558293700218, +C6_no_reconstruction,0.3/location_start_V,accuracy,0.603021978021978,0.602993219441673,0.5629208352743702,0.64396915201917,1000,paired source-video group resample,,,,,C0,0.006868131868131844,0.007894736842105232,-0.03142161549534848,0.04258682266009848, +C6_no_reconstruction,0.3/location_start_V,macro_f1,0.5225492046712977,0.5224289828008064,0.48959713427108126,0.5567918491359286,1000,paired source-video group resample,,,,,C0,-0.04126146909866257,-0.039725678174485524,-0.08316993444584798,0.00023009470907437755, +C6_no_reconstruction,0.3/location_start_V,mae,0.6947979927062988,0.6950227618217468,0.6461153566837311,0.7488212794065475,1000,paired source-video group resample,-0.0010246038436889648,-0.0009163320064544678,-0.00503087043762207,0.0032853454351425156,C0,-0.03864842653274536,-0.03877100348472595,-0.07767102420330048,-0.001254251599311831, +C6_no_reconstruction,0.3/location_start_V,rmse,0.933550462557192,0.9324379142198725,0.8496445613222099,1.019017513729473,1000,paired source-video group resample,,,,,C0,-0.0032908575140180307,-0.004922443802632959,-0.06253934021739486,0.05556027300163325, +C6_no_reconstruction,0.3/location_start_V,pearson,0.588141918182373,0.5885617136955261,0.5198087185621262,0.6508238956332206,1000,paired source-video group resample,,,,,C0,0.06710147857666016,0.06803429126739502,0.016930265724658965,0.11682813316583633, +C6_no_reconstruction,0.3/location_middle_V,accuracy,0.6002747252747253,0.6002719521393814,0.5618010461760462,0.640962429900483,1000,paired source-video group resample,,,,,C0,0.008241758241758212,0.0085696102719931,-0.027463029904699215,0.043354115468485055, +C6_no_reconstruction,0.3/location_middle_V,macro_f1,0.517448436487664,0.518086852657327,0.48464419185861746,0.5504336346016818,1000,paired source-video group resample,,,,,C0,-0.03826054254875211,-0.03651359300322449,-0.07935261066366008,-0.00012599639589758245, +C6_no_reconstruction,0.3/location_middle_V,mae,0.6951202750205994,0.6952370405197144,0.6465926364064216,0.7495913818478585,1000,paired source-video group resample,-0.0007023215293884277,-0.0006534159183502197,-0.005436624586582184,0.004029503464698791,C0,-0.03868979215621948,-0.03943130373954773,-0.07947197258472442,-0.0011318847537040815, +C6_no_reconstruction,0.3/location_middle_V,rmse,0.9325246075919369,0.9314798651023264,0.8476093139514221,1.0180021697043535,1000,paired source-video group resample,,,,,C0,-0.006356598716656059,-0.007858101999522416,-0.06614942650752031,0.053248241473840496, +C6_no_reconstruction,0.3/location_middle_V,pearson,0.5881863236427307,0.5890338718891144,0.5191590473055839,0.6506682276725769,1000,paired source-video group resample,,,,,C0,0.06916284561157227,0.0699189156293869,0.017628856003284454,0.12057905122637748, +C6_no_reconstruction,0.3/location_end_V,accuracy,0.6002747252747253,0.6,0.558010846902102,0.64114110707804,1000,paired source-video group resample,,,,,C0,0.01098901098901095,0.011865529216682158,-0.02490581028228387,0.04661732904734072, +C6_no_reconstruction,0.3/location_end_V,macro_f1,0.5194301869893779,0.5197197304941242,0.4847625604954745,0.5541697305072056,1000,paired source-video group resample,,,,,C0,-0.03384620788129389,-0.03240805863926588,-0.07437405061757504,0.008212510642924779, +C6_no_reconstruction,0.3/location_end_V,mae,0.6964459419250488,0.6970421075820923,0.6467581421136857,0.7500575467944145,1000,paired source-video group resample,0.0006233453750610352,0.0005842745304107666,-0.00043926090002059935,0.0024403735995292652,C0,-0.03677242994308472,-0.03671139478683472,-0.07878662794828414,0.0022190570831298793, +C6_no_reconstruction,0.3/location_end_V,rmse,0.933083718134694,0.9319831010633897,0.8478794337289826,1.018770108170467,1000,paired source-video group resample,,,,,C0,-0.004360776376966191,-0.0058820196672971226,-0.06300624377355488,0.05486749750886077, +C6_no_reconstruction,0.3/location_end_V,pearson,0.5879771113395691,0.5888382792472839,0.5188234254717827,0.6499683037400246,1000,paired source-video group resample,,,,,C0,0.06882870197296143,0.07031083106994629,0.01780301332473755,0.11982305943965911, +C6_no_reconstruction,0.3/span_long_V,accuracy,0.6057692307692307,0.6057292055203283,0.5647971153202125,0.6465680087857727,1000,paired source-video group resample,,,,,C0,0.02060439560439553,0.02161053228514559,-0.015732613451828397,0.05594946937964029, +C6_no_reconstruction,0.3/span_long_V,macro_f1,0.5261936174158057,0.5263610520671111,0.49173936347181846,0.5606819463774958,1000,paired source-video group resample,,,,,C0,-0.022419899352310924,-0.021316143533018472,-0.0639282757910767,0.01509655124069258, +C6_no_reconstruction,0.3/span_long_V,mae,0.6936109066009521,0.6937386393547058,0.6450522094964981,0.748533146083355,1000,paired source-video group resample,-0.0022116899490356445,-0.0019744038581848145,-0.006642834842205047,0.0022706314921379085,C0,-0.04074740409851074,-0.04058730602264404,-0.08057885766029357,-0.003853003680706059, +C6_no_reconstruction,0.3/span_long_V,rmse,0.9329646077572813,0.9322090183839175,0.8484019092847367,1.0190692020516807,1000,paired source-video group resample,,,,,C0,-0.004867529961352646,-0.006879080746531319,-0.06509383360636041,0.054170667230519574, +C6_no_reconstruction,0.3/span_long_V,pearson,0.5887360572814941,0.5892985463142395,0.5200408205389977,0.6510130852460861,1000,paired source-video group resample,,,,,C0,0.06885546445846558,0.06995491683483124,0.018010635673999787,0.11978154554963112, +C6_no_reconstruction,0.3/span_multi_short_V,accuracy,0.6043956043956044,0.6044216163384986,0.5650562328296703,0.6469110066707096,1000,paired source-video group resample,,,,,C0,0.016483516483516425,0.016861483190209414,-0.020455930676277236,0.051742987835528276, +C6_no_reconstruction,0.3/span_multi_short_V,macro_f1,0.5255313251577809,0.525004760022066,0.4916607838714839,0.5602648021628304,1000,paired source-video group resample,,,,,C0,-0.025927992673127287,-0.02486367921751159,-0.0678654343202682,0.01452960312265305, +C6_no_reconstruction,0.3/span_multi_short_V,mae,0.6943562030792236,0.6945986151695251,0.6449353694915771,0.7486310437321663,1000,paired source-video group resample,-0.0014663934707641602,-0.0013447105884552002,-0.003982767462730408,0.0003495499491691588,C0,-0.03924673795700073,-0.03947785496711731,-0.0804594710469246,-0.002724474668502817, +C6_no_reconstruction,0.3/span_multi_short_V,rmse,0.933189112868246,0.9320639036045852,0.8487530310063696,1.0186358901289576,1000,paired source-video group resample,,,,,C0,-0.004743723563657598,-0.006449955785491623,-0.06408956324371544,0.05503902938485168, +C6_no_reconstruction,0.3/span_multi_short_V,pearson,0.5887292623519897,0.589488297700882,0.519934207201004,0.6505296275019645,1000,paired source-video group resample,,,,,C0,0.06921327114105225,0.07009246945381165,0.018848641961812972,0.12056475207209587, +C6_no_reconstruction,0.3/synchrony_sync,accuracy,0.6002747252747253,0.6005832143100047,0.5588139801375096,0.6391927850985515,1000,paired source-video group resample,,,,,C0,0.012362637362637319,0.013020097568326061,-0.025281316880684863,0.050001788268955585, +C6_no_reconstruction,0.3/synchrony_sync,macro_f1,0.5145857470694268,0.5133647177294592,0.47877987630641866,0.5494285474042359,1000,paired source-video group resample,,,,,C0,-0.03436648394433528,-0.0337120162940282,-0.08192454083655831,0.011498619541079303, +C6_no_reconstruction,0.3/synchrony_sync,mae,0.7142950296401978,0.715408205986023,0.6635633438825608,0.7663195177912712,1000,paired source-video group resample,0.01847243309020996,0.018324464559555054,-0.0020442366600036616,0.036870598793029785,C0,-0.028645575046539307,-0.029275864362716675,-0.07354815304279327,0.011162585020065303, +C6_no_reconstruction,0.3/synchrony_sync,rmse,0.9348879347160279,0.9327061954734883,0.8537816825191712,1.011884135920451,1000,paired source-video group resample,,,,,C0,-0.016505276635805144,-0.017632838390646333,-0.07722950549988145,0.04071108147986401, +C6_no_reconstruction,0.3/synchrony_sync,pearson,0.5905910134315491,0.5915088355541229,0.5221387714147567,0.6560831233859062,1000,paired source-video group resample,,,,,C0,0.07566648721694946,0.07649070024490356,0.026917393505573272,0.13256675228476522, +C6_no_reconstruction,0.3/synchrony_partial,accuracy,0.6002747252747253,0.6002855139863132,0.5594456204588364,0.6411395998736027,1000,paired source-video group resample,,,,,C0,0.008241758241758212,0.009269274613863343,-0.02989369579388931,0.04654448171726032, +C6_no_reconstruction,0.3/synchrony_partial,macro_f1,0.5051711057426024,0.504465996024593,0.4708286732133132,0.5400242894455224,1000,paired source-video group resample,,,,,C0,-0.05167782153369849,-0.050600390363317344,-0.09717806299613871,-0.00449554531033852, +C6_no_reconstruction,0.3/synchrony_partial,mae,0.7045269012451172,0.7042336463928223,0.655803494155407,0.7554687976837158,1000,paired source-video group resample,0.008704304695129395,0.00895768404006958,-0.01026345044374466,0.02557868659496307,C0,-0.050428152084350586,-0.05132833123207092,-0.08968364000320435,-0.008310848474502579, +C6_no_reconstruction,0.3/synchrony_partial,rmse,0.9206071314013177,0.9182889825798679,0.8431712308724267,0.9987142594502513,1000,paired source-video group resample,,,,,C0,-0.033140867705374166,-0.03536069020413929,-0.09087783994365407,0.025289524809283193, +C6_no_reconstruction,0.3/synchrony_partial,pearson,0.6023101210594177,0.6038934588432312,0.535568006336689,0.663944385945797,1000,paired source-video group resample,,,,,C0,0.09456586837768555,0.09654459357261658,0.046880753338336946,0.14397840797901154, +C6_no_reconstruction,0.3/synchrony_async,accuracy,0.6112637362637363,0.6117398472891422,0.5725913139580688,0.6550290462310745,1000,paired source-video group resample,,,,,C0,0.016483516483516536,0.017993088202051255,-0.019285283844942908,0.052983650387412866, +C6_no_reconstruction,0.3/synchrony_async,macro_f1,0.524743699631154,0.52496568178905,0.48826082515818386,0.5617646372163477,1000,paired source-video group resample,,,,,C0,-0.03260604550463231,-0.031181284720687152,-0.0768737430941767,0.009563762646841271, +C6_no_reconstruction,0.3/synchrony_async,mae,0.703370988368988,0.7029098272323608,0.6503743633627892,0.7540915384888649,1000,paired source-video group resample,0.007548391819000244,0.007038027048110962,-0.013719014823436737,0.02741359919309616,C0,-0.05385178327560425,-0.05310097336769104,-0.09964919090270996,-0.008747939765453346, +C6_no_reconstruction,0.3/synchrony_async,rmse,0.9253889451790631,0.9231550063588863,0.8410117571456871,0.9999079854606778,1000,paired source-video group resample,,,,,C0,-0.04170143970849316,-0.04255913014120033,-0.10365518249765372,0.015953221256382263, +C6_no_reconstruction,0.3/synchrony_async,pearson,0.5962101221084595,0.5977542698383331,0.5280820548534393,0.6601959243416786,1000,paired source-video group resample,,,,,C0,0.09849289059638977,0.09983876347541809,0.04740248024463654,0.15283198654651636, +C6_pointmask,0.0/none,accuracy,0.6002747252747253,0.6004873734075771,0.5625770741543697,0.6429700501064591,1000,paired source-video group resample,,,,,C0,0.008241758241758212,0.009162319361995519,-0.028337609715320726,0.04438917296576256, +C6_pointmask,0.0/none,macro_f1,0.5482119048463493,0.5474584995449867,0.5126817208494184,0.5859418907145598,1000,paired source-video group resample,,,,,C0,-0.007722707804681206,-0.006856689761272072,-0.05044781709523131,0.03496862300803344, +C6_pointmask,0.0/none,mae,0.695020318031311,0.6941304206848145,0.6443205192685127,0.7461471572518349,1000,paired source-video group resample,,,,,C0,-0.038393616676330566,-0.03965434432029724,-0.08031623363494873,0.0010311543941497687, +C6_pointmask,0.0/none,rmse,0.9554455446308991,0.9535809032888668,0.8733255873574375,1.0319509751897957,1000,paired source-video group resample,,,,,C0,0.01827188520270895,0.016595642082713524,-0.04302532722704946,0.07420725485300263, +C6_pointmask,0.0/none,pearson,0.5645413398742676,0.5651587843894958,0.4983416497707367,0.6273603960871696,1000,paired source-video group resample,,,,,C0,0.045298755168914795,0.04742977023124695,-0.00698881447315216,0.09906484112143517, +C6_pointmask,0.1/single,accuracy,0.6071428571428571,0.6078707928869714,0.569460309572646,0.6489752468898294,1000,paired source-video group resample,,,,,C0,0.019230769230769162,0.020242017498886322,-0.016934251962335733,0.05540502295142979, +C6_pointmask,0.1/single,macro_f1,0.5540610183467326,0.5529900165311044,0.5196761860900341,0.5906311901833194,1000,paired source-video group resample,,,,,C0,0.004176220909826278,0.005465230827072731,-0.037527141733836936,0.04711977494243348, +C6_pointmask,0.1/single,mae,0.6874645948410034,0.6867386400699615,0.636426842212677,0.7369416028261184,1000,paired source-video group resample,-0.007555723190307617,-0.007000058889389038,-0.016838216781616212,-2.4776160717010895e-05,C0,-0.04829460382461548,-0.0490230917930603,-0.08740547448396682,-0.008361552655696871, +C6_pointmask,0.1/single,rmse,0.9450418699666925,0.9435126131998566,0.8633372864596809,1.0207892215037222,1000,paired source-video group resample,,,,,C0,0.005719294405445274,0.0043931791903409345,-0.05094229767538886,0.061567286357781706, +C6_pointmask,0.1/single,pearson,0.5729021430015564,0.5735881328582764,0.5083090901374817,0.6366536602377891,1000,paired source-video group resample,,,,,C0,0.05632662773132324,0.0585198849439621,0.004285109043121339,0.10690525472164152, +C6_pointmask,0.1/sync,accuracy,0.5947802197802198,0.5953155001981083,0.556784897810298,0.6364830746465334,1000,paired source-video group resample,,,,,C0,0.008241758241758212,0.009543325526932045,-0.027895953418965936,0.043788869180571934, +C6_pointmask,0.1/sync,macro_f1,0.5400702500791276,0.5394587911262003,0.504616268489938,0.5774370266805076,1000,paired source-video group resample,,,,,C0,-0.010257813015625672,-0.008408583092114341,-0.05051730800960488,0.030983398909185462, +C6_pointmask,0.1/sync,mae,0.6959730982780457,0.6952901780605316,0.6434992924332619,0.7457843378186226,1000,paired source-video group resample,0.0009527802467346191,0.0009454786777496338,-0.0070977285504341125,0.008108888566493987,C0,-0.0390697717666626,-0.04040127992630005,-0.07956013977527618,5.08010387420646e-05, +C6_pointmask,0.1/sync,rmse,0.9516295598896815,0.9495059704763911,0.867477496788884,1.0302021842718663,1000,paired source-video group resample,,,,,C0,0.006446295534394797,0.0052460886027912434,-0.05334324054614587,0.06303546189396292, +C6_pointmask,0.1/sync,pearson,0.5651708841323853,0.5660054981708527,0.4996610820293427,0.6274351701140404,1000,paired source-video group resample,,,,,C0,0.05177104473114014,0.05339159071445465,-0.0021047428250312796,0.10528886467218397, +C6_pointmask,0.1/partial,accuracy,0.6002747252747253,0.6007931349010809,0.5630624999999999,0.6426731635564961,1000,paired source-video group resample,,,,,C0,0.006868131868131844,0.008135626875330926,-0.02761848423022636,0.04010367181447156, +C6_pointmask,0.1/partial,macro_f1,0.544696783871215,0.5439467605392547,0.5089086239148519,0.5814982642934944,1000,paired source-video group resample,,,,,C0,-0.01293615413209026,-0.011779578246284006,-0.05431293234044063,0.027630435203406228, +C6_pointmask,0.1/partial,mae,0.693175733089447,0.6926285922527313,0.6401478931307792,0.7463719010353088,1000,paired source-video group resample,-0.0018445849418640137,-0.0015664398670196533,-0.011461019515991211,0.007130295038223266,C0,-0.042041659355163574,-0.042874813079833984,-0.08370510786771775,-0.0027707472443580686, +C6_pointmask,0.1/partial,rmse,0.9461266660752496,0.9440477892488843,0.8648078434519769,1.0277731710976254,1000,paired source-video group resample,,,,,C0,0.008683220668037617,0.006864912776235743,-0.04969772591948009,0.06339538721782129, +C6_pointmask,0.1/partial,pearson,0.5716928243637085,0.5715778470039368,0.5059064567089081,0.6332780212163925,1000,paired source-video group resample,,,,,C0,0.05111926794052124,0.053337424993515015,-0.004171659052371978,0.10273445844650268, +C6_pointmask,0.1/async,accuracy,0.6016483516483516,0.6021654844777032,0.56392221186715,0.6445398095482308,1000,paired source-video group resample,,,,,C0,0.009615384615384581,0.010575132014412403,-0.02589226577237476,0.04274426392950102, +C6_pointmask,0.1/async,macro_f1,0.5488062853082636,0.5479223658985704,0.5124883506749237,0.5843248536469298,1000,paired source-video group resample,,,,,C0,-0.010000736571143531,-0.008868418137046308,-0.04886048523104638,0.029927234072039056, +C6_pointmask,0.1/async,mae,0.6939353346824646,0.6937787234783173,0.6419263422489166,0.7447668194770813,1000,paired source-video group resample,-0.0010849833488464355,-0.0008711516857147217,-0.009207895398139954,0.006575669348239897,C0,-0.044958293437957764,-0.04573735594749451,-0.08504796177148818,-0.006269440054893503, +C6_pointmask,0.1/async,rmse,0.9510341286055842,0.9493304986625519,0.8685224252823964,1.0272326795207685,1000,paired source-video group resample,,,,,C0,0.007299487308059849,0.0066380675439655645,-0.052069503653949266,0.0629298176796837, +C6_pointmask,0.1/async,pearson,0.5664066672325134,0.5670377016067505,0.5009051352739334,0.6307253822684288,1000,paired source-video group resample,,,,,C0,0.0523906946182251,0.054596155881881714,0.0015720844268798837,0.10600960329174995, +C6_pointmask,0.3/single,accuracy,0.6085164835164835,0.6091713082003343,0.5698897656068694,0.6505732619852097,1000,paired source-video group resample,,,,,C0,0.0027472527472527375,0.004149377593361037,-0.035542788494700335,0.03921901189240958, +C6_pointmask,0.3/single,macro_f1,0.555096385893966,0.554489717285058,0.5198315151748155,0.5949621716839366,1000,paired source-video group resample,,,,,C0,-0.014202863514482189,-0.012358139395286571,-0.05887162451520476,0.028895419061518445, +C6_pointmask,0.3/single,mae,0.6857606172561646,0.6846841871738434,0.6362528070807457,0.7346968680620193,1000,paired source-video group resample,-0.009259700775146484,-0.009020835161209106,-0.02003478556871414,0.0006440982222557065,C0,-0.045370519161224365,-0.0459991991519928,-0.08675079196691513,-0.006359878182411194, +C6_pointmask,0.3/single,rmse,0.9395617384589352,0.9377096261268998,0.8584115494353276,1.0164619979952112,1000,paired source-video group resample,,,,,C0,-0.00020583627460968312,-0.0010681415864332022,-0.061352135062551105,0.05621695346322351, +C6_pointmask,0.3/single,pearson,0.5771206021308899,0.5777075588703156,0.5111358761787415,0.6419055715203286,1000,paired source-video group resample,,,,,C0,0.05570501089096069,0.057478561997413635,0.0036911964416503915,0.11029875874519347, +C6_pointmask,0.3/sync,accuracy,0.6002747252747253,0.6005476055367339,0.5609747652185664,0.6426515904961784,1000,paired source-video group resample,,,,,C0,0.02060439560439553,0.020862308762169657,-0.013335570469798635,0.053795187820019096, +C6_pointmask,0.3/sync,macro_f1,0.5399010980406329,0.5396635127890399,0.5060751826925692,0.5739263142351034,1000,paired source-video group resample,,,,,C0,-0.00019989139885490115,0.0002572864643724526,-0.03781308283264138,0.0379732199421443, +C6_pointmask,0.3/sync,mae,0.6910622119903564,0.6894395053386688,0.6389559552073478,0.7405360177159309,1000,paired source-video group resample,-0.00395810604095459,-0.0034271180629730225,-0.023400647938251494,0.01545789688825606,C0,-0.061841487884521484,-0.06243368983268738,-0.10199430882930756,-0.023792923986911782, +C6_pointmask,0.3/sync,rmse,0.9306507730085556,0.927690086648518,0.8532507678450593,1.009419591282034,1000,paired source-video group resample,,,,,C0,-0.03164194275572174,-0.033522865638082655,-0.08574471239764825,0.019783919588613825, +C6_pointmask,0.3/sync,pearson,0.5799417495727539,0.5803853273391724,0.5161906823515892,0.6394748032093048,1000,paired source-video group resample,,,,,C0,0.08170682191848755,0.08340579271316528,0.0345303013920784,0.13060271069407464, +C6_pointmask,0.3/partial,accuracy,0.6043956043956044,0.6039745000141039,0.5661626051057076,0.645806359350652,1000,paired source-video group resample,,,,,C0,0.009615384615384581,0.010649695202219644,-0.02711699740137019,0.04638018200202216, +C6_pointmask,0.3/partial,macro_f1,0.5510943198336964,0.5503848738578934,0.513464629296891,0.589569587233513,1000,paired source-video group resample,,,,,C0,-0.01214132780977295,-0.01129713090570067,-0.05468919374970795,0.0306400250799174, +C6_pointmask,0.3/partial,mae,0.6999186277389526,0.7002473473548889,0.6490382969379425,0.7505115464329719,1000,paired source-video group resample,0.0048983097076416016,0.005020022392272949,-0.011551772058010102,0.0224002406001091,C0,-0.04663306474685669,-0.04657819867134094,-0.0918493315577507,0.0013939559459686267, +C6_pointmask,0.3/partial,rmse,0.9515581541165736,0.9499019889087494,0.876558583639446,1.0270363874360628,1000,paired source-video group resample,,,,,C0,-0.0012400391474024497,-0.001853519859808972,-0.05929410704493347,0.059542359865242804, +C6_pointmask,0.3/partial,pearson,0.561883270740509,0.5618424117565155,0.49631733894348146,0.6225027784705162,1000,paired source-video group resample,,,,,C0,0.05316948890686035,0.054749175906181335,-0.006178301572799682,0.10759720206260681, +C6_pointmask,0.3/async,accuracy,0.6016483516483516,0.6013245614035088,0.5620009466454511,0.642561708214912,1000,paired source-video group resample,,,,,C0,0.0219780219780219,0.022270695430958054,-0.01243143661405447,0.061123223828462366, +C6_pointmask,0.3/async,macro_f1,0.5447870467292425,0.5436377881126042,0.5078289174579713,0.5811333875178181,1000,paired source-video group resample,,,,,C0,-0.001363423819432441,-0.0005541707011463837,-0.04295942055786604,0.04215905034376713, +C6_pointmask,0.3/async,mae,0.6930806636810303,0.692762941122055,0.6423661634325981,0.7435825631022454,1000,paired source-video group resample,-0.0019396543502807617,-0.0014485716819763184,-0.01607563942670822,0.011684443056583402,C0,-0.07550275325775146,-0.07798051834106445,-0.12258071005344391,-0.030785471200942997, +C6_pointmask,0.3/async,rmse,0.9379518691486342,0.93555776641264,0.859659130933973,1.0137255223006747,1000,paired source-video group resample,,,,,C0,-0.045152925407295874,-0.04714384094313662,-0.10625048037537069,0.012518385702311178, +C6_pointmask,0.3/async,pearson,0.5710340142250061,0.5715279281139374,0.5036475837230683,0.6337088122963905,1000,paired source-video group resample,,,,,C0,0.0841880738735199,0.08442080020904541,0.026561045646667482,0.1462169863283634, +C6_pointmask,0.5/single,accuracy,0.6016483516483516,0.6021799376683354,0.5624208613177343,0.6422686116700201,1000,paired source-video group resample,,,,,C0,0.015109890109890056,0.015547710945428672,-0.024306465284734537,0.0511425395256917, +C6_pointmask,0.5/single,macro_f1,0.5418015535912448,0.5413664154152495,0.505613736128241,0.5784316147944879,1000,paired source-video group resample,,,,,C0,-0.01321572857063813,-0.012592454337252978,-0.05755610867405414,0.029674701295784905, +C6_pointmask,0.5/single,mae,0.7026358246803284,0.7016992270946503,0.6510074272751808,0.7541944876313209,1000,paired source-video group resample,0.007615506649017334,0.00760987401008606,-0.005605097115039826,0.022174088656902312,C0,-0.04639250040054321,-0.0474848747253418,-0.08685398995876312,-0.006096380949020387, +C6_pointmask,0.5/single,rmse,0.9598123119086038,0.9589607084083542,0.8766735865749995,1.03757988736814,1000,paired source-video group resample,,,,,C0,0.00016147439607028247,-0.0017079977537143853,-0.0591556589328888,0.0576863302548184, +C6_pointmask,0.5/single,pearson,0.560593843460083,0.5613481402397156,0.49366522431373594,0.6243108525872231,1000,paired source-video group resample,,,,,C0,0.052360594272613525,0.05439314246177673,-0.0024774730205535857,0.10601662695407865, +C6_pointmask,0.5/sync,accuracy,0.6126373626373627,0.6126919863761969,0.5742170227465987,0.6548332808714777,1000,paired source-video group resample,,,,,C0,0.019230769230769273,0.01911698165744319,-0.018478248418223025,0.05595973111086041, +C6_pointmask,0.5/sync,macro_f1,0.543369000980704,0.5426709095577735,0.5069337870118644,0.5797726159659737,1000,paired source-video group resample,,,,,C0,-0.02013453841547952,-0.01951400477815518,-0.061522768407284656,0.021051440311493398, +C6_pointmask,0.5/sync,mae,0.693103551864624,0.6925141215324402,0.6413091629743576,0.7463256224989891,1000,paired source-video group resample,-0.0019167661666870117,-0.0018243789672851562,-0.029096144437789916,0.02500400394201278,C0,-0.09419071674346924,-0.09582075476646423,-0.13641897290945054,-0.053270539641380316, +C6_pointmask,0.5/sync,rmse,0.9252728704116687,0.9229968002986991,0.8454150791278694,1.0034509723090106,1000,paired source-video group resample,,,,,C0,-0.07709866851451974,-0.0795426633247453,-0.13138739290171475,-0.023738553192653458, +C6_pointmask,0.5/sync,pearson,0.5836662650108337,0.584229588508606,0.5204382821917534,0.6463545903563499,1000,paired source-video group resample,,,,,C0,0.10400798916816711,0.10503944754600525,0.05150414332747459,0.15574623718857764, +C6_pointmask,0.5/partial,accuracy,0.5961538461538461,0.5960028041916143,0.5567752418525268,0.6349904476482293,1000,paired source-video group resample,,,,,C0,0.01098901098901095,0.011436746372368745,-0.025247688760782875,0.04734322469643636, +C6_pointmask,0.5/partial,macro_f1,0.5316122097513486,0.5300904428377364,0.49438746538999834,0.5705327664800096,1000,paired source-video group resample,,,,,C0,-0.019984020988082496,-0.019023171681039452,-0.06230552967868049,0.023531299311041986, +C6_pointmask,0.5/partial,mae,0.7047833204269409,0.7037711143493652,0.6526267632842064,0.756676821410656,1000,paired source-video group resample,0.009763002395629883,0.010309100151062012,-0.012522093951702118,0.03322380632162094,C0,-0.08067578077316284,-0.08135303854942322,-0.12467101514339447,-0.036541725695133226, +C6_pointmask,0.5/partial,rmse,0.9520360948848486,0.9519727965390552,0.8736296754160296,1.0301349576472032,1000,paired source-video group resample,,,,,C0,-0.04757470045160017,-0.04918472781790523,-0.10262612324969853,0.01086449291896387, +C6_pointmask,0.5/partial,pearson,0.5570197105407715,0.557467132806778,0.4942507028579712,0.6182721480727196,1000,paired source-video group resample,,,,,C0,0.0756140947341919,0.0767388790845871,0.018928460776805878,0.13008690327405928, +C6_pointmask,0.5/async,accuracy,0.603021978021978,0.6036988110964333,0.5662945112894227,0.6453997333178735,1000,paired source-video group resample,,,,,C0,0.030219780219780223,0.03223502028813835,-0.0037967729784028066,0.06507815958388673, +C6_pointmask,0.5/async,macro_f1,0.5400993224504118,0.5400157821506983,0.5042029753144784,0.5789026432575445,1000,paired source-video group resample,,,,,C0,-0.0005486739841149557,0.0012120769908333107,-0.03987176053492404,0.03889874436616362, +C6_pointmask,0.5/async,mae,0.7044049501419067,0.7043474018573761,0.6524737298488616,0.7565036445856095,1000,paired source-video group resample,0.009384632110595703,0.009787708520889282,-0.015299296379089356,0.03389809727668761,C0,-0.08885973691940308,-0.08944764733314514,-0.13636554926633834,-0.04731642603874207, +C6_pointmask,0.5/async,rmse,0.9436266976453797,0.9423439604882453,0.8651686268784589,1.0222103813846197,1000,paired source-video group resample,,,,,C0,-0.059701035998791174,-0.0603731615096173,-0.11967664252853598,-0.001597708056048421, +C6_pointmask,0.5/async,pearson,0.5614078640937805,0.5621177852153778,0.49717149436473845,0.6244024559855461,1000,paired source-video group resample,,,,,C0,0.08691316843032837,0.0874689519405365,0.02637929990887642,0.14887942671775817, +C6_pointmask,0.7/single,accuracy,0.5975274725274725,0.5978036803804743,0.5609359074026087,0.6401762518117428,1000,paired source-video group resample,,,,,C0,0.012362637362637319,0.013243278003608916,-0.022449725094523754,0.050601562678965546, +C6_pointmask,0.7/single,macro_f1,0.5304580723935562,0.5301537086197196,0.49238287829563643,0.5676185085240876,1000,paired source-video group resample,,,,,C0,-0.02085290010894081,-0.0199367693130309,-0.061125036050355436,0.02241631439103953, +C6_pointmask,0.7/single,mae,0.7102105021476746,0.7092974781990051,0.6551469162106514,0.7649620309472084,1000,paired source-video group resample,0.015190184116363525,0.015467584133148193,-0.006708987057209014,0.03686230629682541,C0,-0.07773810625076294,-0.07814809679985046,-0.12616467475891113,-0.03213116079568863, +C6_pointmask,0.7/single,rmse,0.9528492075154,0.9505311503010232,0.8698138023836874,1.0365502524437855,1000,paired source-video group resample,,,,,C0,-0.057474787908528446,-0.05868448118724551,-0.12046037924517376,0.00532712409599778, +C6_pointmask,0.7/single,pearson,0.5674605965614319,0.5659830868244171,0.4990686535835266,0.6326514631509781,1000,paired source-video group resample,,,,,C0,0.09482038021087646,0.09704670310020447,0.035297489166259764,0.15601155310869216, +C6_pointmask,0.7/sync,accuracy,0.6002747252747253,0.5991271477953668,0.5590598739495799,0.6430865805500047,1000,paired source-video group resample,,,,,C0,0.017857142857142794,0.01855540799763905,-0.02011677959808785,0.0555597389558232, +C6_pointmask,0.7/sync,macro_f1,0.5075952276478822,0.506535984041667,0.4697303520957974,0.5424529542754238,1000,paired source-video group resample,,,,,C0,-0.041344272452481845,-0.0414646412542618,-0.08493760807715367,0.001769016689699407, +C6_pointmask,0.7/sync,mae,0.7427775859832764,0.742916077375412,0.6880170270800591,0.7978169530630111,1000,paired source-video group resample,0.04775726795196533,0.04970759153366089,0.014106623828411102,0.07975848317146302,C0,-0.04059404134750366,-0.040467411279678345,-0.09221168011426925,0.008583718538284277, +C6_pointmask,0.7/sync,rmse,0.9817732685305128,0.9798627241506089,0.9033151481865669,1.0637631003157186,1000,paired source-video group resample,,,,,C0,-0.038382173026784705,-0.03818558696257335,-0.09762579141704833,0.022419960079185397, +C6_pointmask,0.7/sync,pearson,0.534336268901825,0.5342632532119751,0.4681879736483097,0.5940205320715904,1000,paired source-video group resample,,,,,C0,0.055891215801239014,0.056050628423690796,9.258091449737592e-05,0.11355040594935416, +C6_pointmask,0.7/partial,accuracy,0.5906593406593407,0.5909090909090909,0.5529197303921569,0.6304701808250478,1000,paired source-video group resample,,,,,C0,-0.0027472527472527375,-0.0028089943050796373,-0.04023325251436782,0.03313961290707391, +C6_pointmask,0.7/partial,macro_f1,0.50333371491949,0.5031817296360865,0.4673583943576801,0.53973829649513,1000,paired source-video group resample,,,,,C0,-0.060679722297120486,-0.060276451925224184,-0.10059347780941565,-0.020978316785639873, +C6_pointmask,0.7/partial,mae,0.7443259358406067,0.7433881759643555,0.6853507414460183,0.8017901226878166,1000,paired source-video group resample,0.049305617809295654,0.04945972561836243,0.01861548572778702,0.07984105795621871,C0,-0.053265392780303955,-0.054376959800720215,-0.10075561255216599,-0.008872286975383769, +C6_pointmask,0.7/partial,rmse,0.9882875223676942,0.9863965001268096,0.8973441335821261,1.0706166935457841,1000,paired source-video group resample,,,,,C0,-0.02916916939922165,-0.03008090806019159,-0.09538672268257854,0.033328583498594404, +C6_pointmask,0.7/partial,pearson,0.5188366770744324,0.5181098282337189,0.4477321095764637,0.5916991859674454,1000,paired source-video group resample,,,,,C0,0.026359856128692627,0.02831055223941803,-0.03388632982969284,0.09075368642807005, +C6_pointmask,0.7/async,accuracy,0.5989010989010989,0.5994493563191383,0.5585916722074468,0.6383145399733318,1000,paired source-video group resample,,,,,C0,0.02060439560439553,0.021202449253292455,-0.01626349460215911,0.059768945117150106, +C6_pointmask,0.7/async,macro_f1,0.5139080177103549,0.5132008387867678,0.4777222997557826,0.5488112701947282,1000,paired source-video group resample,,,,,C0,-0.039890045297548915,-0.03904081006139101,-0.08206324925695943,0.00391852864953673, +C6_pointmask,0.7/async,mae,0.7435755729675293,0.7436866760253906,0.689701721072197,0.7940841242671013,1000,paired source-video group resample,0.04855525493621826,0.049806296825408936,0.015564166009426117,0.08036084920167923,C0,-0.07288402318954468,-0.07420375943183899,-0.12422399371862411,-0.02280445694923401, +C6_pointmask,0.7/async,rmse,0.9725638349514236,0.9715652906830945,0.8953905509291746,1.0498514604575777,1000,paired source-video group resample,,,,,C0,-0.06823104382293055,-0.06973899399260941,-0.13374624847784325,0.0022941200762928915, +C6_pointmask,0.7/async,pearson,0.5331299901008606,0.5324560105800629,0.46402418687939645,0.5925682932138442,1000,paired source-video group resample,,,,,C0,0.05393382906913757,0.055239319801330566,-0.010735903680324553,0.11546913310885429, +C6_pointmask,0.3/modality_T,accuracy,0.6112637362637363,0.6111859948445275,0.5752333169422419,0.652574200913242,1000,paired source-video group resample,,,,,C0,0.02472527472527475,0.024793388429752095,-0.006056891097842692,0.057914567109482354, +C6_pointmask,0.3/modality_T,macro_f1,0.555862265331295,0.554503426161798,0.5209373730342759,0.5924242640905888,1000,paired source-video group resample,,,,,C0,0.009098951887588247,0.009274239683901675,-0.026799914226445308,0.04772417363209459, +C6_pointmask,0.3/modality_T,mae,0.6778489947319031,0.6779740750789642,0.6268625065684319,0.7274748876690864,1000,paired source-video group resample,-0.01717132329940796,-0.01594129204750061,-0.04061823785305023,0.00435636788606643,C0,-0.07227474451065063,-0.07342803478240967,-0.1136921688914299,-0.031392878293991094, +C6_pointmask,0.3/modality_T,rmse,0.918229962783327,0.9176041223847116,0.8379846253218148,0.994596377468075,1000,paired source-video group resample,,,,,C0,-0.04443936887079358,-0.046027284852774075,-0.10144380933501022,0.011306040997301574, +C6_pointmask,0.3/modality_T,pearson,0.5903373956680298,0.5904963612556458,0.529854702949524,0.6514475166797637,1000,paired source-video group resample,,,,,C0,0.08857500553131104,0.09026402235031128,0.033960819244384766,0.14587471038103103, +C6_pointmask,0.3/modality_A,accuracy,0.6016483516483516,0.602333172147002,0.5632507288629738,0.6440715189716355,1000,paired source-video group resample,,,,,C0,0.015109890109890056,0.016286476027245922,-0.022947292253789317,0.050832962853191103, +C6_pointmask,0.3/modality_A,macro_f1,0.5467703563480085,0.5453744856077811,0.5108900902198011,0.5833259925378091,1000,paired source-video group resample,,,,,C0,-0.004711412311888763,-0.0023125846173803755,-0.0473277416539942,0.03581744808442675, +C6_pointmask,0.3/modality_A,mae,0.6935770511627197,0.6929322779178619,0.6425409078598022,0.744278459250927,1000,paired source-video group resample,-0.0014432668685913086,-0.001325160264968872,-0.007997545599937438,0.004182083904743194,C0,-0.036589980125427246,-0.03809398412704468,-0.07789844870567321,0.00402521938085555, +C6_pointmask,0.3/modality_A,rmse,0.9539659886005456,0.9523925465385905,0.872424558416111,1.0300382686873577,1000,paired source-video group resample,,,,,C0,0.019653628284465707,0.018006444398533883,-0.04187262445742458,0.07781886654378943, +C6_pointmask,0.3/modality_A,pearson,0.567615270614624,0.5684468150138855,0.501320993900299,0.6312942996621131,1000,paired source-video group resample,,,,,C0,0.044878244400024414,0.046950459480285645,-0.008145147562026977,0.0979297563433647, +C6_pointmask,0.3/modality_V,accuracy,0.6002747252747253,0.6005609541330565,0.5621353555835018,0.6426652814469412,1000,paired source-video group resample,,,,,C0,0.012362637362637319,0.013586956521739135,-0.02322404371584697,0.046706065391045826, +C6_pointmask,0.3/modality_V,macro_f1,0.5488310915272337,0.5483089398284616,0.5138682296996717,0.5853128705640047,1000,paired source-video group resample,,,,,C0,-0.0022622544556150093,-0.0010638107773842664,-0.04235864091253178,0.03702057479691105, +C6_pointmask,0.3/modality_V,mae,0.6953630447387695,0.694441556930542,0.6438161283731461,0.7457552090287208,1000,paired source-video group resample,0.0003427267074584961,0.00025281310081481934,-0.002153430879116058,0.003397803008556366,C0,-0.03797006607055664,-0.039034098386764526,-0.0791372999548912,0.0010042354464530922, +C6_pointmask,0.3/modality_V,rmse,0.9555057746157773,0.9535792153074463,0.8742013743866228,1.0323031465753147,1000,paired source-video group resample,,,,,C0,0.01771304230315096,0.016012392473416515,-0.04334222100187403,0.07222389275276658, +C6_pointmask,0.3/modality_V,pearson,0.562436044216156,0.5631886720657349,0.4970131374895573,0.625827445089817,1000,paired source-video group resample,,,,,C0,0.04299020767211914,0.044849544763565063,-0.008891762793064117,0.09801353067159652, +C6_pointmask,0.3/modality_TA,accuracy,0.603021978021978,0.6028271728271728,0.5646350465154674,0.6443044924967951,1000,paired source-video group resample,,,,,C0,0.016483516483516425,0.01702691575317794,-0.018815954159658956,0.05256748071979438, +C6_pointmask,0.3/modality_TA,macro_f1,0.5422529370291316,0.5412210346036445,0.5058004190525903,0.5761685915948341,1000,paired source-video group resample,,,,,C0,-0.01194535013116127,-0.01106503447392515,-0.051023689028138766,0.0287633776750925, +C6_pointmask,0.3/modality_TA,mae,0.6956610083580017,0.695913165807724,0.6450333803892135,0.7436297476291657,1000,paired source-video group resample,0.0006406903266906738,0.0011178851127624512,-0.017576898634433746,0.019702526926994323,C0,-0.07992452383041382,-0.08052858710289001,-0.12106852233409882,-0.035326716303825396, +C6_pointmask,0.3/modality_TA,rmse,0.9474221011828642,0.9463680773560343,0.8674770987592768,1.020346827242377,1000,paired source-video group resample,,,,,C0,-0.023198985170572617,-0.025564608661565347,-0.08219909861300749,0.03226378937547566, +C6_pointmask,0.3/modality_TA,pearson,0.5648590326309204,0.5650847554206848,0.5007694303989411,0.6259085059165954,1000,paired source-video group resample,,,,,C0,0.06641906499862671,0.06867723166942596,0.012819366157054904,0.1201735109090805, +C6_pointmask,0.3/modality_TV,accuracy,0.6181318681318682,0.6183938243730706,0.5777603456116416,0.6607761272743254,1000,paired source-video group resample,,,,,C0,0.0357142857142857,0.036425906394946694,-0.001520754680072729,0.07355394240910465, +C6_pointmask,0.3/modality_TV,macro_f1,0.5627039734047946,0.5614361235892782,0.5242965141325213,0.6000520847157513,1000,paired source-video group resample,,,,,C0,0.017859385415936346,0.0187039060183814,-0.024527255702510718,0.06062265372143306, +C6_pointmask,0.3/modality_TV,mae,0.6722285747528076,0.6714872419834137,0.6243312388658524,0.7223836719989777,1000,paired source-video group resample,-0.022791743278503418,-0.02238568663597107,-0.04117102473974228,-0.005352796614170077,C0,-0.08844518661499023,-0.0895097553730011,-0.12922194451093674,-0.04965069442987442, +C6_pointmask,0.3/modality_TV,rmse,0.9065285287545518,0.9043098926500186,0.8330183495750819,0.9817024589353218,1000,paired source-video group resample,,,,,C0,-0.061038562051337064,-0.06379651003833642,-0.1169761806600579,-0.009457914594281766, +C6_pointmask,0.3/modality_TV,pearson,0.5989774465560913,0.5996994078159332,0.5360727697610855,0.6578229635953903,1000,paired source-video group resample,,,,,C0,0.09999063611030579,0.1020708680152893,0.052635271847248075,0.1508306458592415, +C6_pointmask,0.3/modality_AV,accuracy,0.6043956043956044,0.6045450008895601,0.5676711229946524,0.6459954037181862,1000,paired source-video group resample,,,,,C0,0.009615384615384581,0.010473224429035866,-0.026101736566186123,0.04477665861444226, +C6_pointmask,0.3/modality_AV,macro_f1,0.5528134565846227,0.5518406559956284,0.5166758991541032,0.5902925377112541,1000,paired source-video group resample,,,,,C0,-0.006884749654489486,-0.00538771369594343,-0.04752301842436557,0.032819749457897326, +C6_pointmask,0.3/modality_AV,mae,0.6906806826591492,0.6897684633731842,0.639446347951889,0.7413535580039025,1000,paired source-video group resample,-0.004339635372161865,-0.004150509834289551,-0.011204150319099427,0.001197709143161773,C0,-0.04730015993118286,-0.048596203327178955,-0.0887989953160286,-0.008449725806713106, +C6_pointmask,0.3/modality_AV,rmse,0.9513902041541396,0.9494588569602249,0.867549472452964,1.0283251869927108,1000,paired source-video group resample,,,,,C0,0.00935497665254903,0.007922094179669326,-0.05090175569903549,0.06428663912709698, +C6_pointmask,0.3/modality_AV,pearson,0.5676571130752563,0.5684264898300171,0.5023043200373649,0.6322275698184967,1000,paired source-video group resample,,,,,C0,0.052123188972473145,0.054068177938461304,-5.927234888076778e-05,0.10632999241352081, +C6_pointmask,0.3/modality_TAV,accuracy,0.592032967032967,0.5918230897807835,0.553553281068525,0.6315931831123404,1000,paired source-video group resample,,,,,C0,0.01098901098901095,0.012203440312996416,-0.026662903567216765,0.04951376547911194, +C6_pointmask,0.3/modality_TAV,macro_f1,0.5314440033432027,0.5308339432489675,0.49494099974957684,0.5661205064248293,1000,paired source-video group resample,,,,,C0,-0.013033895261079453,-0.011331121346755624,-0.05627480211058864,0.029877131625863352, +C6_pointmask,0.3/modality_TAV,mae,0.6981375217437744,0.6982000768184662,0.6474638357758522,0.7463450416922569,1000,paired source-video group resample,0.003117203712463379,0.003822922706604004,-0.017892751097679137,0.022460737824439997,C0,-0.07279419898986816,-0.073780357837677,-0.11720914244651795,-0.03275971859693527, +C6_pointmask,0.3/modality_TAV,rmse,0.936876375682144,0.934712379508879,0.8623868073634283,1.0108758506988396,1000,paired source-video group resample,,,,,C0,-0.04316138597922514,-0.04475188116777634,-0.10114152143000053,0.012346904176857708, +C6_pointmask,0.3/modality_TAV,pearson,0.5727233290672302,0.573556512594223,0.5098162889480591,0.633763799071312,1000,paired source-video group resample,,,,,C0,0.08241382241249084,0.08346384763717651,0.028023096919059756,0.13745290860533713, +C6_pointmask,0.3/location_start_T,accuracy,0.6098901098901099,0.6091799113920129,0.5744651824330209,0.6520195656158357,1000,paired source-video group resample,,,,,C0,0.017857142857142905,0.018632331902718235,-0.015393081761006235,0.054134629880898524, +C6_pointmask,0.3/location_start_T,macro_f1,0.5570531675489921,0.5558407055194694,0.5207707968645533,0.5931394949394647,1000,paired source-video group resample,,,,,C0,-0.004138006019330676,-0.0029498136690324084,-0.04296800053538461,0.037451228712206845, +C6_pointmask,0.3/location_start_T,mae,0.6985827684402466,0.6979420781135559,0.6484092146158218,0.7491375163197518,1000,paired source-video group resample,0.003562450408935547,0.003703892230987549,-0.007008551061153412,0.015200443565845486,C0,-0.07067841291427612,-0.07106393575668335,-0.11848504841327667,-0.027518576383590728, +C6_pointmask,0.3/location_start_T,rmse,0.9531597068596116,0.9517556030391389,0.870100425788532,1.0280985630922794,1000,paired source-video group resample,,,,,C0,-0.022154222752448494,-0.02321584571040408,-0.08326373283846086,0.0327793803389312, +C6_pointmask,0.3/location_start_T,pearson,0.5620554089546204,0.5624253749847412,0.4988629467785358,0.6217599168419838,1000,paired source-video group resample,,,,,C0,0.07950595021247864,0.08114592730998993,0.028745900839567184,0.13425668850541114, +C6_pointmask,0.3/location_middle_T,accuracy,0.6126373626373627,0.6125008685984296,0.5725063912395587,0.6535757584463342,1000,paired source-video group resample,,,,,C0,0.02335164835164838,0.02415440054911533,-0.012311901504788003,0.058743169398907114, +C6_pointmask,0.3/location_middle_T,macro_f1,0.5492766165977948,0.5488249376412258,0.5112811585730503,0.5852123177790386,1000,paired source-video group resample,,,,,C0,-0.0015248870885220533,-0.000771839448976519,-0.04273534684016378,0.038125279743362536, +C6_pointmask,0.3/location_middle_T,mae,0.6794397830963135,0.6791399419307709,0.626835897564888,0.7313366398215294,1000,paired source-video group resample,-0.015580534934997559,-0.015089929103851318,-0.037267939746379854,0.0065434902906417805,C0,-0.06932759284973145,-0.06933671236038208,-0.11544043719768524,-0.026269946992397313, +C6_pointmask,0.3/location_middle_T,rmse,0.920680613964801,0.9178589288464928,0.8354292754006615,1.0006964227007575,1000,paired source-video group resample,,,,,C0,-0.04077666078601416,-0.04194305296823031,-0.10253055467131456,0.01950164842956546, +C6_pointmask,0.3/location_middle_T,pearson,0.5943151116371155,0.594251960515976,0.5318232417106629,0.6547245353460311,1000,paired source-video group resample,,,,,C0,0.08736079931259155,0.08900883793830872,0.027635814249515535,0.1452571354806423, +C6_pointmask,0.3/location_end_T,accuracy,0.6057692307692307,0.6053877551020408,0.5649059323500797,0.6468004280898989,1000,paired source-video group resample,,,,,C0,0.03159340659340659,0.03189209833363482,-0.0027980351779226444,0.06817722263827965, +C6_pointmask,0.3/location_end_T,macro_f1,0.54414156059075,0.543123341453358,0.5060669266056153,0.5789939122039922,1000,paired source-video group resample,,,,,C0,0.006173386660856983,0.006405776258204932,-0.03678149155629211,0.046102769280527, +C6_pointmask,0.3/location_end_T,mae,0.6850674152374268,0.683788537979126,0.6303961679339409,0.7348836287856102,1000,paired source-video group resample,-0.009952902793884277,-0.009608983993530273,-0.035670427978038786,0.0122157871723175,C0,-0.08408546447753906,-0.08453139662742615,-0.12724442631006241,-0.040673166513443, +C6_pointmask,0.3/location_end_T,rmse,0.9160607820942281,0.9132638460259972,0.8396289962525901,0.9886631074345931,1000,paired source-video group resample,,,,,C0,-0.061471786633812586,-0.06256072775682292,-0.11861372177764644,-0.008103940169597744, +C6_pointmask,0.3/location_end_T,pearson,0.5844565629959106,0.5858763456344604,0.5164260193705559,0.6470767498016358,1000,paired source-video group resample,,,,,C0,0.07777196168899536,0.07894709706306458,0.02317879572510719,0.13302590325474736, +C6_pointmask,0.3/span_long_T,accuracy,0.6002747252747253,0.600126103404792,0.5620494375471569,0.6418611209544058,1000,paired source-video group resample,,,,,C0,0.0219780219780219,0.022727272727272707,-0.0126100586070601,0.056522577400245896, +C6_pointmask,0.3/span_long_T,macro_f1,0.5403724083196012,0.5397298334759677,0.5044321436183303,0.5766375381422463,1000,paired source-video group resample,,,,,C0,0.0002679332496000608,0.0009496149188704672,-0.040033136325805345,0.03939106313469639, +C6_pointmask,0.3/span_long_T,mae,0.6921499371528625,0.691986471414566,0.6409514173865318,0.7426679819822312,1000,paired source-video group resample,-0.0028703808784484863,-0.0021632909774780273,-0.023025025427341462,0.016976788640022274,C0,-0.056971609592437744,-0.05769532918930054,-0.09811717122793198,-0.015598067641258258, +C6_pointmask,0.3/span_long_T,rmse,0.9225705642383922,0.9211757867607087,0.846538967373409,0.9981102860962389,1000,paired source-video group resample,,,,,C0,-0.04132735678647792,-0.04324941815620553,-0.09468843216590105,0.011846920424560184, +C6_pointmask,0.3/span_long_T,pearson,0.5862105488777161,0.5873236656188965,0.5227968186140061,0.6438746139407158,1000,paired source-video group resample,,,,,C0,0.08623144030570984,0.08905147016048431,0.03620288074016571,0.1368336610496044, +C6_pointmask,0.3/span_multi_short_T,accuracy,0.603021978021978,0.6034960447198772,0.5646431373587629,0.6447567987874956,1000,paired source-video group resample,,,,,C0,0.015109890109890056,0.01554789731295575,-0.021904804169183008,0.05143477563325255, +C6_pointmask,0.3/span_multi_short_T,macro_f1,0.5447757324345346,0.5442931208032411,0.5091987713232128,0.5802735789367983,1000,paired source-video group resample,,,,,C0,-0.006768722852083742,-0.006466372342798676,-0.046837222403877776,0.0351830743529725, +C6_pointmask,0.3/span_multi_short_T,mae,0.6793760657310486,0.6788385510444641,0.6273041680455208,0.7274966672062874,1000,paired source-video group resample,-0.01564425230026245,-0.014816910028457642,-0.03868539929389954,0.004434801638126372,C0,-0.07207947969436646,-0.07257494330406189,-0.11680605560541153,-0.030116857588291194, +C6_pointmask,0.3/span_multi_short_T,rmse,0.915084039810177,0.9128336669758572,0.8336324751360688,0.9918070961221047,1000,paired source-video group resample,,,,,C0,-0.045614065870204445,-0.046301450047113724,-0.10358057443247574,0.012339418538363407, +C6_pointmask,0.3/span_multi_short_T,pearson,0.5947513580322266,0.5959398448467255,0.5272472143173218,0.6552484497427941,1000,paired source-video group resample,,,,,C0,0.0931428074836731,0.09531685709953308,0.03815106898546219,0.14621270596981045, +C6_pointmask,0.3/location_start_A,accuracy,0.6016483516483516,0.6021100525639104,0.5622341057635175,0.6438234691088026,1000,paired source-video group resample,,,,,C0,0.017857142857142794,0.019385213339345952,-0.01892033936481724,0.05458420785671799, +C6_pointmask,0.3/location_start_A,macro_f1,0.5439144910500137,0.5429197858138524,0.506486222417306,0.5814248482928334,1000,paired source-video group resample,,,,,C0,-0.01286566934721356,-0.011142814859433137,-0.054420667123947275,0.027891707317075805, +C6_pointmask,0.3/location_start_A,mae,0.6969431638717651,0.696684718132019,0.6432713806629181,0.7487318724393844,1000,paired source-video group resample,0.0019228458404541016,0.0020678341388702393,-0.007965198159217835,0.011624263226985931,C0,-0.0380551815032959,-0.03945505619049072,-0.08209546506404877,0.003337767720222473, +C6_pointmask,0.3/location_start_A,rmse,0.953441973650404,0.9511637128990373,0.8716128261039647,1.036008844877235,1000,paired source-video group resample,,,,,C0,0.012644625955736344,0.010982845073907122,-0.05054630347570132,0.06979080889853397, +C6_pointmask,0.3/location_start_A,pearson,0.5705196261405945,0.5697512626647949,0.5037169218063354,0.6320768401026725,1000,paired source-video group resample,,,,,C0,0.05277597904205322,0.055363550782203674,-0.00025951266288757284,0.10698444023728369, +C6_pointmask,0.3/location_middle_A,accuracy,0.6071428571428571,0.6073464954500534,0.5700643476387917,0.6478377838639735,1000,paired source-video group resample,,,,,C0,0.02060439560439553,0.021468846263164754,-0.015732181028122353,0.05459978514287304, +C6_pointmask,0.3/location_middle_A,macro_f1,0.5559292666952514,0.5549349393531735,0.5209478728195114,0.5921335777568303,1000,paired source-video group resample,,,,,C0,0.002166443367210724,0.00393303470489309,-0.03927890247097192,0.042160455006727555, +C6_pointmask,0.3/location_middle_A,mae,0.690590500831604,0.6896293759346008,0.6397590562701225,0.741885232925415,1000,paired source-video group resample,-0.004429817199707031,-0.0041387975215911865,-0.011167745292186736,0.0009089663624763486,C0,-0.043432772159576416,-0.04467207193374634,-0.08476034253835678,-0.0038663536310195954, +C6_pointmask,0.3/location_middle_A,rmse,0.9515805786119219,0.9499595291754397,0.8710755977083804,1.0281663227441518,1000,paired source-video group resample,,,,,C0,0.0148016429582839,0.013647922384676048,-0.046869818308675835,0.07358619893768582, +C6_pointmask,0.3/location_middle_A,pearson,0.5681990385055542,0.569073498249054,0.5015531405806541,0.6325946554541588,1000,paired source-video group resample,,,,,C0,0.047837793827056885,0.049496620893478394,-0.004922600090503692,0.10156538113951682, +C6_pointmask,0.3/location_end_A,accuracy,0.6016483516483516,0.6016788353006703,0.5636251248751248,0.6442648298257356,1000,paired source-video group resample,,,,,C0,0.012362637362637319,0.013377932406989812,-0.025045595135964927,0.04781411078848454, +C6_pointmask,0.3/location_end_A,macro_f1,0.5503906638455444,0.5497219652185199,0.5147627713580437,0.5871354956899648,1000,paired source-video group resample,,,,,C0,-0.0030084974195143666,-0.0020256979754788573,-0.04379551959783558,0.038668646059804926, +C6_pointmask,0.3/location_end_A,mae,0.6944974064826965,0.6934072375297546,0.6433093786239624,0.7457962140440941,1000,paired source-video group resample,-0.000522911548614502,-0.0004850625991821289,-0.0018607720732688904,0.0004578426480293274,C0,-0.040249526500701904,-0.04177737236022949,-0.08185546398162842,-0.0011861428618431143, +C6_pointmask,0.3/location_end_A,rmse,0.9552055851110918,0.9534602590058483,0.8732184037957761,1.0316526492554998,1000,paired source-video group resample,,,,,C0,0.01753616428269933,0.01579896306241152,-0.04320089433336374,0.07281582780516768, +C6_pointmask,0.3/location_end_A,pearson,0.564346969127655,0.5650760531425476,0.49835103675723075,0.6271291807293892,1000,paired source-video group resample,,,,,C0,0.045395612716674805,0.0473383367061615,-0.007334172725677489,0.09927184358239173, +C6_pointmask,0.3/span_long_A,accuracy,0.6016483516483516,0.6022023660656769,0.5634350916283607,0.643700071014212,1000,paired source-video group resample,,,,,C0,0.013736263736263687,0.015277777777777724,-0.02291572058478848,0.04801126456022871, +C6_pointmask,0.3/span_long_A,macro_f1,0.5462197365220147,0.5455045973776849,0.5108514720698594,0.5827582054326824,1000,paired source-video group resample,,,,,C0,-0.008117544131055365,-0.007011312555888771,-0.0489021789173504,0.03207346719938194, +C6_pointmask,0.3/span_long_A,mae,0.6992484331130981,0.6985288560390472,0.6465888023376465,0.7515897482633591,1000,paired source-video group resample,0.004228115081787109,0.003926664590835571,-0.0014061644673347474,0.01081658899784088,C0,-0.0374104380607605,-0.03827393054962158,-0.07788493037223816,0.0009130999445915193, +C6_pointmask,0.3/span_long_A,rmse,0.9612616945802931,0.9589790449576119,0.8742321269142215,1.0409629047478839,1000,paired source-video group resample,,,,,C0,0.023308618026930517,0.022638289378610954,-0.040142792288891616,0.07946822734857045, +C6_pointmask,0.3/span_long_A,pearson,0.5624366998672485,0.5631444752216339,0.4957756258547306,0.6280930042266846,1000,paired source-video group resample,,,,,C0,0.044906795024871826,0.04717329144477844,-0.008622105419635772,0.10285621732473373, +C6_pointmask,0.3/span_multi_short_A,accuracy,0.6016483516483516,0.6024548192771084,0.5645206451131187,0.6432718568030837,1000,paired source-video group resample,,,,,C0,0.006868131868131844,0.008462623413258097,-0.029430074782206467,0.04149933065595712, +C6_pointmask,0.3/span_multi_short_A,macro_f1,0.5463784845228145,0.5455522798317727,0.510333132408673,0.5829527413640531,1000,paired source-video group resample,,,,,C0,-0.013899351061193888,-0.012349225277495768,-0.054345722547506116,0.027400407091212577, +C6_pointmask,0.3/span_multi_short_A,mae,0.6968013048171997,0.6963781714439392,0.6436375260353089,0.749733780324459,1000,paired source-video group resample,0.0017809867858886719,0.0016259849071502686,-0.006315675377845764,0.009869176149368285,C0,-0.039322733879089355,-0.040506333112716675,-0.07981782108545303,-0.0007038399577140998, +C6_pointmask,0.3/span_multi_short_A,rmse,0.9583898126848838,0.9569607143695358,0.8731387997006173,1.036996414939298,1000,paired source-video group resample,,,,,C0,0.016743663039585632,0.015614542994463021,-0.043979444256433166,0.07569070638606212, +C6_pointmask,0.3/span_multi_short_A,pearson,0.5654610991477966,0.5659667551517487,0.4980952501296997,0.6303692385554314,1000,paired source-video group resample,,,,,C0,0.04916071891784668,0.05197605490684509,-0.004863770306110382,0.10524919927120208, +C6_pointmask,0.3/location_start_V,accuracy,0.6002747252747253,0.6010783629810488,0.5626538394441208,0.6430618278141673,1000,paired source-video group resample,,,,,C0,0.004120879120879106,0.005355097827314248,-0.03265699146991184,0.03919151218438854, +C6_pointmask,0.3/location_start_V,macro_f1,0.5516622598671251,0.5511884680033229,0.5149511074201316,0.5879581047761735,1000,paired source-video group resample,,,,,C0,-0.012148413902835165,-0.01069522516933058,-0.05231452793027118,0.027603336757125497, +C6_pointmask,0.3/location_start_V,mae,0.6914190649986267,0.6904871165752411,0.6380360126495361,0.7438201397657395,1000,paired source-video group resample,-0.003601253032684326,-0.0034728646278381348,-0.011944980919361114,0.004765328764915464,C0,-0.04202735424041748,-0.04277357459068298,-0.08387649357318878,-0.002878487110137947, +C6_pointmask,0.3/location_start_V,rmse,0.9518271818817775,0.9496486275111005,0.8663189284615335,1.0325527340399498,1000,paired source-video group resample,,,,,C0,0.014985861810567491,0.014189333138358073,-0.047821709741387275,0.07185169145432878, +C6_pointmask,0.3/location_start_V,pearson,0.5607166886329651,0.5608433783054352,0.49345619305968286,0.6261209636926651,1000,paired source-video group resample,,,,,C0,0.0396762490272522,0.04140837490558624,-0.015185047686100005,0.09355425015091895, +C6_pointmask,0.3/location_middle_V,accuracy,0.6043956043956044,0.6050033458499325,0.5654645622708881,0.64636907261451,1000,paired source-video group resample,,,,,C0,0.012362637362637319,0.01277774149541383,-0.022947292253789317,0.04621484911608546, +C6_pointmask,0.3/location_middle_V,macro_f1,0.5536520888926612,0.5530325502016398,0.5167325120548559,0.5901323798989483,1000,paired source-video group resample,,,,,C0,-0.002056890143754986,-0.0011041068758760875,-0.04473486189395508,0.03734852343759201, +C6_pointmask,0.3/location_middle_V,mae,0.6901042461395264,0.6894992291927338,0.6381408199667931,0.7399939253926276,1000,paired source-video group resample,-0.004916071891784668,-0.00458642840385437,-0.011003811657428742,-0.00022081583738327093,C0,-0.04370582103729248,-0.04476484656333923,-0.08527854532003402,-0.005416716635227206, +C6_pointmask,0.3/location_middle_V,rmse,0.9506046867833734,0.9483751072177515,0.8689621453728072,1.0267626671506762,1000,paired source-video group resample,,,,,C0,0.011723480474780446,0.00966193315389191,-0.04703977682450198,0.06577874464673138, +C6_pointmask,0.3/location_middle_V,pearson,0.5658414363861084,0.5667000412940979,0.49936513155698775,0.630885374546051,1000,paired source-video group resample,,,,,C0,0.04681795835494995,0.04931275546550751,-0.004278098046779632,0.10057054609060287, +C6_pointmask,0.3/location_end_V,accuracy,0.603021978021978,0.6036172329667036,0.5650924572626682,0.6437381509873936,1000,paired source-video group resample,,,,,C0,0.013736263736263687,0.014647552683138776,-0.023134811616954458,0.04881732073896261, +C6_pointmask,0.3/location_end_V,macro_f1,0.5500960042243276,0.5498161293825383,0.5137698579120599,0.5855645938233142,1000,paired source-video group resample,,,,,C0,-0.0031803906463442333,-0.0015037663755963493,-0.0442224825346778,0.03884056253138071, +C6_pointmask,0.3/location_end_V,mae,0.6936039328575134,0.6924462020397186,0.6424853354692459,0.7435732528567314,1000,paired source-video group resample,-0.0014163851737976074,-0.0014500021934509277,-0.004108509421348572,0.0010508775711059568,C0,-0.03961443901062012,-0.040475040674209595,-0.08067871630191803,0.0005410447716712909, +C6_pointmask,0.3/location_end_V,rmse,0.9541128386316292,0.9519985196234356,0.8718618001130589,1.0308039495265957,1000,paired source-video group resample,,,,,C0,0.01666834411996898,0.014680205388290068,-0.04482256025544193,0.07228009156597483, +C6_pointmask,0.3/location_end_V,pearson,0.5651412010192871,0.5658327341079712,0.49867853671312334,0.6283614918589592,1000,paired source-video group resample,,,,,C0,0.04599279165267944,0.04825875163078308,-0.00619165301322937,0.09975276589393615, +C6_pointmask,0.3/span_long_V,accuracy,0.6043956043956044,0.6046523887580368,0.5664216634429401,0.6469835572024085,1000,paired source-video group resample,,,,,C0,0.019230769230769162,0.020273000955554732,-0.017493398976841445,0.05484032210727121, +C6_pointmask,0.3/span_long_V,macro_f1,0.5531799596422858,0.5525375756182636,0.5163979430661898,0.5889902707513847,1000,paired source-video group resample,,,,,C0,0.004566442874169185,0.005787080353624241,-0.03626843594736828,0.04684280959109683, +C6_pointmask,0.3/span_long_V,mae,0.6895143985748291,0.6891641020774841,0.6376197174191475,0.7407252207398415,1000,paired source-video group resample,-0.005505919456481934,-0.005198359489440918,-0.011812308430671692,-0.000697121024131778,C0,-0.04484391212463379,-0.045880019664764404,-0.08575425893068314,-0.00652456134557726, +C6_pointmask,0.3/span_long_V,rmse,0.9510594483656432,0.9494248456597412,0.8689687723273753,1.0287075360581701,1000,paired source-video group resample,,,,,C0,0.013227310647009216,0.011638357727878634,-0.04632569767434509,0.06824444346780281, +C6_pointmask,0.3/span_long_V,pearson,0.5662582516670227,0.5669298768043518,0.49996894150972365,0.631060916185379,1000,paired source-video group resample,,,,,C0,0.04637765884399414,0.04855886101722717,-0.00490484982728958,0.0996202401816845, +C6_pointmask,0.3/span_multi_short_V,accuracy,0.6043956043956044,0.6045901153983861,0.5667860669719006,0.6456727955806278,1000,paired source-video group resample,,,,,C0,0.016483516483516425,0.01748042523394233,-0.01916256110510559,0.0504676381180481, +C6_pointmask,0.3/span_multi_short_V,macro_f1,0.5546102693857252,0.5539935740094462,0.5193922734078181,0.5910374725182149,1000,paired source-video group resample,,,,,C0,0.0031509515548170386,0.003968917178940434,-0.03777429489783279,0.04330180621392243, +C6_pointmask,0.3/span_multi_short_V,mae,0.6897972226142883,0.6890001893043518,0.6380852669477463,0.7404617846012116,1000,paired source-video group resample,-0.005223095417022705,-0.004951059818267822,-0.011416913568973541,0.0003529012203216552,C0,-0.043805718421936035,-0.04520031809806824,-0.08452776223421096,-0.005263006687164307, +C6_pointmask,0.3/span_multi_short_V,rmse,0.9514552326846539,0.9497034985547252,0.8693016374240704,1.028882473370174,1000,paired source-video group resample,,,,,C0,0.013522396252750313,0.011725885709846062,-0.04680773315384069,0.06931395001588342, +C6_pointmask,0.3/span_multi_short_V,pearson,0.5660951137542725,0.5667392909526825,0.5000628605484962,0.6310354635119438,1000,paired source-video group resample,,,,,C0,0.04657912254333496,0.048823803663253784,-0.0052022248506546015,0.0996913433074951, +C6_pointmask,0.3/synchrony_sync,accuracy,0.6057692307692307,0.6052268609427323,0.5685655325729752,0.646307261458202,1000,paired source-video group resample,,,,,C0,0.017857142857142794,0.019019842883746807,-0.015664208784509543,0.05325597679303796, +C6_pointmask,0.3/synchrony_sync,macro_f1,0.5436364625897864,0.5425473195164426,0.5099321626577266,0.5795046377731128,1000,paired source-video group resample,,,,,C0,-0.005315768423975742,-0.003878093131097382,-0.047665971274700285,0.035812569726765, +C6_pointmask,0.3/synchrony_sync,mae,0.6870747804641724,0.6871552467346191,0.6350949317216873,0.735992631316185,1000,paired source-video group resample,-0.007945537567138672,-0.007394760847091675,-0.028346365690231322,0.01092119663953781,C0,-0.0558658242225647,-0.05626922845840454,-0.10193280428647995,-0.014969353377819062, +C6_pointmask,0.3/synchrony_sync,rmse,0.9179080050234815,0.9152907884263055,0.8412570904948169,0.9921347766474151,1000,paired source-video group resample,,,,,C0,-0.03348520632835161,-0.0347544874434893,-0.092868030282131,0.017344580007605952, +C6_pointmask,0.3/synchrony_sync,pearson,0.5908973217010498,0.5918853282928467,0.5304584309458733,0.6530683562159538,1000,paired source-video group resample,,,,,C0,0.0759727954864502,0.07634967565536499,0.028817947208881377,0.1318745106458664, +C6_pointmask,0.3/synchrony_partial,accuracy,0.6167582417582418,0.6164578144458281,0.5794940149214076,0.6584255345846811,1000,paired source-video group resample,,,,,C0,0.02472527472527475,0.025126265752271504,-0.011801860127271859,0.05831941636635321, +C6_pointmask,0.3/synchrony_partial,macro_f1,0.5582995865367456,0.5570306116396377,0.523074519726983,0.5926088477981656,1000,paired source-video group resample,,,,,C0,0.0014506592604447421,0.0027923624845579975,-0.041782634587571414,0.04386865854348471, +C6_pointmask,0.3/synchrony_partial,mae,0.6806420087814331,0.6797354817390442,0.6312681376934052,0.7275946140289307,1000,paired source-video group resample,-0.01437830924987793,-0.013723403215408325,-0.031244562566280366,0.0026252105832099883,C0,-0.07431304454803467,-0.07537218928337097,-0.1123827189207077,-0.03433569967746735, +C6_pointmask,0.3/synchrony_partial,rmse,0.9121626648457606,0.9099690977278234,0.8378509718825168,0.9892087654508799,1000,paired source-video group resample,,,,,C0,-0.04158533426093125,-0.0428101353180812,-0.09537502485734078,0.01082573772739296, +C6_pointmask,0.3/synchrony_partial,pearson,0.5947660207748413,0.5946125686168671,0.5317644238471985,0.6524033784866333,1000,paired source-video group resample,,,,,C0,0.08702176809310913,0.08818311989307404,0.0384174108505249,0.13524738773703573, +C6_pointmask,0.3/synchrony_async,accuracy,0.6098901098901099,0.6098746324098436,0.5708455105086432,0.6512360541577152,1000,paired source-video group resample,,,,,C0,0.015109890109890167,0.015488414357110403,-0.014921121361472705,0.047625379939209664, +C6_pointmask,0.3/synchrony_async,macro_f1,0.5506538840736852,0.5492575185061305,0.5135688105562647,0.5888746737236363,1000,paired source-video group resample,,,,,C0,-0.006695861062101072,-0.005685506186554334,-0.04496948191654089,0.031689952792675065, +C6_pointmask,0.3/synchrony_async,mae,0.6900760531425476,0.6904626786708832,0.6345339208841324,0.7408803030848503,1000,paired source-video group resample,-0.004944264888763428,-0.004418879747390747,-0.030534060299396516,0.018902981281280515,C0,-0.06714671850204468,-0.06691622734069824,-0.11382345408201218,-0.023844332993030553, +C6_pointmask,0.3/synchrony_async,rmse,0.9243771169869076,0.9217691848409774,0.8460670770981964,1.0017979714145664,1000,paired source-video group resample,,,,,C0,-0.042713267900648666,-0.04288230790857239,-0.10302705993938528,0.013026196062723944, +C6_pointmask,0.3/synchrony_async,pearson,0.5824931859970093,0.5834273099899292,0.5173869788646698,0.6449479550123215,1000,paired source-video group resample,,,,,C0,0.08477595448493958,0.08519834280014038,0.03100570365786553,0.1441313438117504, +C7_distill,0.0/none,accuracy,0.5906593406593407,0.5916723959022798,0.553447914120231,0.6288825324180016,1000,paired source-video group resample,,,,,C0,-0.0013736263736263687,0.0,-0.03894469453492523,0.03352984050763153, +C7_distill,0.0/none,macro_f1,0.5243846543289639,0.5248703696127459,0.49188047642875204,0.5568265232084257,1000,paired source-video group resample,,,,,C0,-0.03154995832206664,-0.030150126457411164,-0.07225104908462827,0.008833054675009593, +C7_distill,0.0/none,mae,0.6742965579032898,0.6742668449878693,0.629886557161808,0.7254724353551865,1000,paired source-video group resample,,,,,C0,-0.05911737680435181,-0.060005784034729004,-0.09469406455755233,-0.023747466504573825, +C7_distill,0.0/none,rmse,0.8981109357355169,0.8962383682096454,0.8222706022011207,0.9785181395085336,1000,paired source-video group resample,,,,,C0,-0.039062723692673273,-0.03992031111126981,-0.09111710881261266,0.014632626683510192, +C7_distill,0.0/none,pearson,0.6013434529304504,0.6019341051578522,0.5350904121994973,0.6629965081810951,1000,paired source-video group resample,,,,,C0,0.08210086822509766,0.0818755179643631,0.033297739923000336,0.1299555145204067, +C7_distill,0.1/single,accuracy,0.592032967032967,0.5928766588602654,0.554635831381733,0.6300464169946639,1000,paired source-video group resample,,,,,C0,0.004120879120879106,0.00552870379214826,-0.03390274785081193,0.04354823638661545, +C7_distill,0.1/single,macro_f1,0.524562777336849,0.5244349524138001,0.4894664681343343,0.559230644274933,1000,paired source-video group resample,,,,,C0,-0.025322020100057352,-0.023388022233669647,-0.06753679756197666,0.019170021121372033, +C7_distill,0.1/single,mae,0.6799377799034119,0.6800381243228912,0.6341777756810189,0.7305812194943428,1000,paired source-video group resample,0.00564122200012207,0.005505651235580444,-0.0004839852452278136,0.013470596075057984,C0,-0.05582141876220703,-0.056827813386917114,-0.09239424914121627,-0.01779282242059708, +C7_distill,0.1/single,rmse,0.904535052116391,0.9038386162128019,0.828333872934039,0.9823346839727639,1000,paired source-video group resample,,,,,C0,-0.03478752344485625,-0.035769339765258534,-0.08820437185142868,0.019677597971321417, +C7_distill,0.1/single,pearson,0.595530092716217,0.596304178237915,0.5266641959547996,0.6574144348502159,1000,paired source-video group resample,,,,,C0,0.07895457744598389,0.07944852113723755,0.029664094746112823,0.12777776792645454, +C7_distill,0.1/sync,accuracy,0.5906593406593407,0.5906589000281154,0.5538808689572553,0.627949883758571,1000,paired source-video group resample,,,,,C0,0.004120879120879106,0.0050827234226685225,-0.032290539077722426,0.038676711406314575, +C7_distill,0.1/sync,macro_f1,0.5217284909062792,0.5205023596494257,0.4887479682182141,0.553601319395147,1000,paired source-video group resample,,,,,C0,-0.028599572188474087,-0.027673410118786934,-0.07053674471351505,0.012542237499921453, +C7_distill,0.1/sync,mae,0.6786344647407532,0.6787534058094025,0.6341310605406761,0.7293811351060867,1000,paired source-video group resample,0.004337906837463379,0.004495412111282349,-0.0023304194211959837,0.011148813366889953,C0,-0.05640840530395508,-0.05735942721366882,-0.09091978669166564,-0.02013298571109772, +C7_distill,0.1/sync,rmse,0.902233265639928,0.9017355373405826,0.8263205515179572,0.9820499455934453,1000,paired source-video group resample,,,,,C0,-0.04294999871535865,-0.04403210437874161,-0.09592551382571787,0.012391067538161668, +C7_distill,0.1/sync,pearson,0.5993814468383789,0.5998030304908752,0.535095539689064,0.6597509667277336,1000,paired source-video group resample,,,,,C0,0.08598160743713379,0.08662542700767517,0.04019933864474297,0.13425687253475188, +C7_distill,0.1/partial,accuracy,0.5906593406593407,0.5913183738723307,0.553592031844713,0.6292622660178013,1000,paired source-video group resample,,,,,C0,-0.0027472527472527375,-0.0014204545454545303,-0.03943640406074339,0.030515652863086967, +C7_distill,0.1/partial,macro_f1,0.5215462508144882,0.5211321549876939,0.4879594761375852,0.5533897566385245,1000,paired source-video group resample,,,,,C0,-0.036086687188817024,-0.035246860179669826,-0.079362462244649,0.004783731624338183, +C7_distill,0.1/partial,mae,0.6799012422561646,0.6799030303955078,0.6330803230404853,0.7329964339733124,1000,paired source-video group resample,0.005604684352874756,0.0055574774742126465,-0.002307206392288208,0.014659589529037472,C0,-0.055316150188446045,-0.05572989583015442,-0.09019165486097336,-0.01984638571739197, +C7_distill,0.1/partial,rmse,0.9074751366606286,0.9051735493742175,0.8263383710254786,0.9954466405940079,1000,paired source-video group resample,,,,,C0,-0.029968308746583405,-0.031036363775667763,-0.08333913569399017,0.022399081878080627, +C7_distill,0.1/partial,pearson,0.5955010652542114,0.5966799557209015,0.5244080767035484,0.6579386636614799,1000,paired source-video group resample,,,,,C0,0.07492750883102417,0.07642436027526855,0.02775789499282837,0.12452706024050711, +C7_distill,0.1/async,accuracy,0.5865384615384616,0.587153988720381,0.549711138907734,0.6256663337045043,1000,paired source-video group resample,,,,,C0,-0.005494505494505475,-0.00421941762937178,-0.04166947439353096,0.03267877882860464, +C7_distill,0.1/async,macro_f1,0.5152940636105828,0.5148820815905515,0.48387252637744294,0.5477683519129181,1000,paired source-video group resample,,,,,C0,-0.04351295826882429,-0.042560489744826624,-0.08508928966869675,3.697734032503426e-05, +C7_distill,0.1/async,mae,0.6802725195884705,0.6806835234165192,0.6358393430709839,0.7315587997436523,1000,paired source-video group resample,0.005975961685180664,0.005972504615783691,-0.0007409319281578064,0.014324903488159178,C0,-0.058621108531951904,-0.05997735261917114,-0.09358619898557663,-0.02243833392858507, +C7_distill,0.1/async,rmse,0.9020681579640761,0.9007323874687941,0.8266705428839465,0.9805286186755808,1000,paired source-video group resample,,,,,C0,-0.041666483333448245,-0.04195527135732985,-0.09366844352072541,0.010930697295516751, +C7_distill,0.1/async,pearson,0.5975505113601685,0.5982727110385895,0.5289166390895843,0.6595890849828719,1000,paired source-video group resample,,,,,C0,0.08353453874588013,0.08378037810325623,0.036269666999578475,0.1328396163880825, +C7_distill,0.3/single,accuracy,0.5975274725274725,0.5987774057875055,0.5610705709535831,0.6360970608339029,1000,paired source-video group resample,,,,,C0,-0.008241758241758212,-0.0073640258120492574,-0.045347056186491284,0.02710914894312665, +C7_distill,0.3/single,macro_f1,0.5284759249629695,0.5281568065061097,0.4930141212353739,0.5617418203073343,1000,paired source-video group resample,,,,,C0,-0.04082332444547876,-0.03929726366822356,-0.08524532698265545,0.004542035403162435, +C7_distill,0.3/single,mae,0.6799160242080688,0.680206686258316,0.6340243518352509,0.7306894436478615,1000,paired source-video group resample,0.005619466304779053,0.005791068077087402,-0.0024451375007629394,0.014441864192485807,C0,-0.05121511220932007,-0.051268309354782104,-0.0883388176560402,-0.013406579196453097, +C7_distill,0.3/single,rmse,0.9019475620341081,0.900803229394959,0.8266521625061063,0.9799625564786216,1000,paired source-video group resample,,,,,C0,-0.0378200126994368,-0.038375185133595724,-0.09150950419943438,0.019418270917744458, +C7_distill,0.3/single,pearson,0.6005235910415649,0.6008141934871674,0.5361549779772758,0.65957121104002,1000,paired source-video group resample,,,,,C0,0.07910799980163574,0.07932674884796143,0.030028903484344484,0.12890586853027342, +C7_distill,0.3/sync,accuracy,0.5865384615384616,0.5868719342436697,0.5476470666359725,0.6262238209477897,1000,paired source-video group resample,,,,,C0,0.006868131868131844,0.007347807623654057,-0.02884814049586778,0.042683346771484276, +C7_distill,0.3/sync,macro_f1,0.5119109142364956,0.5114682269672112,0.4786564454290651,0.5462147950704253,1000,paired source-video group resample,,,,,C0,-0.028190075202992215,-0.027536225916375667,-0.06829728090128494,0.012456419312624582, +C7_distill,0.3/sync,mae,0.6936126947402954,0.694351464509964,0.6471006318926811,0.7441665232181549,1000,paired source-video group resample,0.019316136837005615,0.019649386405944824,0.0030773296952247625,0.0377119779586792,C0,-0.05929100513458252,-0.06008824706077576,-0.0978402242064476,-0.02148469537496567, +C7_distill,0.3/sync,rmse,0.9144702882064513,0.9140826164969317,0.8385064134345628,0.9913607183514589,1000,paired source-video group resample,,,,,C0,-0.047822427557826064,-0.04810726142685845,-0.10200999885395733,0.005519154150034301, +C7_distill,0.3/sync,pearson,0.5927407145500183,0.5939752459526062,0.5254461258649826,0.6521680951118469,1000,paired source-video group resample,,,,,C0,0.09450578689575195,0.09509703516960144,0.04629639685153961,0.1450526289641857, +C7_distill,0.3/partial,accuracy,0.6002747252747253,0.6010824182057034,0.5636114911080712,0.6415591471801925,1000,paired source-video group resample,,,,,C0,0.005494505494505475,0.006116222250797887,-0.03286471574076273,0.04426156021195154, +C7_distill,0.3/partial,macro_f1,0.5253127418657062,0.5247904344196486,0.49188189977924435,0.5630112473756641,1000,paired source-video group resample,,,,,C0,-0.03792290577776314,-0.036140961788113435,-0.07972253876973338,0.007831449185021981, +C7_distill,0.3/partial,mae,0.692629873752594,0.6926842331886292,0.6442794695496559,0.745668026804924,1000,paired source-video group resample,0.0183333158493042,0.01845291256904602,0.0025889217853546143,0.03673176914453506,C0,-0.05392181873321533,-0.05370810627937317,-0.09342772513628006,-0.013534392416477204, +C7_distill,0.3/partial,rmse,0.9282297197341056,0.9269254143736151,0.8507239590354974,1.0099492993283177,1000,paired source-video group resample,,,,,C0,-0.02456847352987046,-0.024019665823341918,-0.08137981185752903,0.035309425715503696, +C7_distill,0.3/partial,pearson,0.5833005905151367,0.5832979381084442,0.5169854000210762,0.6404252901673316,1000,paired source-video group resample,,,,,C0,0.07458680868148804,0.07506300508975983,0.023819160461425782,0.12535839974880217, +C7_distill,0.3/async,accuracy,0.5851648351648352,0.585068433764786,0.5473139329749115,0.6250090057636888,1000,paired source-video group resample,,,,,C0,0.005494505494505475,0.005673770280710755,-0.02834497845109055,0.039377401820242006, +C7_distill,0.3/async,macro_f1,0.504594820384294,0.503374712874282,0.47276101033952306,0.5388380961805379,1000,paired source-video group resample,,,,,C0,-0.0415556501643809,-0.04122438675282292,-0.07899203316148525,-0.0025754124620571057, +C7_distill,0.3/async,mae,0.6937493085861206,0.6931886374950409,0.6470826134085655,0.7439159378409386,1000,paired source-video group resample,0.01945275068283081,0.020140647888183594,0.0003947705030441285,0.03711736500263214,C0,-0.07483410835266113,-0.07546576857566833,-0.11442503929138184,-0.03493272960186005, +C7_distill,0.3/async,rmse,0.9149900767304183,0.9124268463157823,0.8347037329002499,0.9998985738556048,1000,paired source-video group resample,,,,,C0,-0.0681147178255117,-0.06817808054212143,-0.1233047671091311,-0.015861568351451024, +C7_distill,0.3/async,pearson,0.5920988321304321,0.5931415855884552,0.5206591591238976,0.6590887486934662,1000,paired source-video group resample,,,,,C0,0.10525289177894592,0.10588687658309937,0.06052371859550476,0.15354588329792024, +C7_distill,0.5/single,accuracy,0.5879120879120879,0.5885195021890213,0.5491795221623016,0.6261299072795423,1000,paired source-video group resample,,,,,C0,0.0013736263736263687,0.0025873394418643447,-0.03795898301824283,0.03945661191305797, +C7_distill,0.5/single,macro_f1,0.5207954930594249,0.5202102197602209,0.4864703326283057,0.5527614064129052,1000,paired source-video group resample,,,,,C0,-0.0342217891024581,-0.03333434979363731,-0.0755927913481755,0.008319700917812055, +C7_distill,0.5/single,mae,0.6808550357818604,0.6807239651679993,0.6380749017000198,0.7271762043237686,1000,paired source-video group resample,0.006558477878570557,0.006895184516906738,-0.004497899115085602,0.01837608367204666,C0,-0.06817328929901123,-0.06814870238304138,-0.10387099981307983,-0.03384900838136674, +C7_distill,0.5/single,rmse,0.9004912082321309,0.8988817171995955,0.8237200382040629,0.9790149725642592,1000,paired source-video group resample,,,,,C0,-0.05915962928040264,-0.059512800136264477,-0.10958068857278287,-0.008694333116152192, +C7_distill,0.5/single,pearson,0.6040370464324951,0.6043434739112854,0.5344610929489135,0.6628813415765762,1000,paired source-video group resample,,,,,C0,0.09580379724502563,0.09711867570877075,0.0477598674595356,0.14403697103261948, +C7_distill,0.5/sync,accuracy,0.5989010989010989,0.6,0.5621546961325967,0.6391686602870814,1000,paired source-video group resample,,,,,C0,0.005494505494505475,0.006139765863730717,-0.030921160233506086,0.043001835742624714, +C7_distill,0.5/sync,macro_f1,0.5206919745351754,0.5198818617496872,0.48734441259290995,0.5579681633436328,1000,paired source-video group resample,,,,,C0,-0.04281156486100812,-0.04238838697078476,-0.08735579543738434,0.0009866233465022065, +C7_distill,0.5/sync,mae,0.7106931209564209,0.7103723287582397,0.6632233887910843,0.7595076695084572,1000,paired source-video group resample,0.036396563053131104,0.03593260049819946,0.017176438868045808,0.05653678029775619,C0,-0.07660114765167236,-0.07702341675758362,-0.11865423172712326,-0.03449341654777527, +C7_distill,0.5/sync,rmse,0.936733027485394,0.9343210364230987,0.8581365023662553,1.015163983879711,1000,paired source-video group resample,,,,,C0,-0.06563851144079447,-0.06749942571842976,-0.12301863358299772,-0.012477522113665707, +C7_distill,0.5/sync,pearson,0.5825034976005554,0.5846393406391144,0.5140529364347458,0.6441381052136421,1000,paired source-video group resample,,,,,C0,0.1028452217578888,0.10464495420455933,0.052237183600664136,0.1561154969036579, +C7_distill,0.5/partial,accuracy,0.6002747252747253,0.6016655301147724,0.5633164918262396,0.6381642122690834,1000,paired source-video group resample,,,,,C0,0.015109890109890056,0.016457454381304637,-0.023068694810384344,0.05449429457475726, +C7_distill,0.5/partial,macro_f1,0.523034287265772,0.5224586845436237,0.49029361658892995,0.5567438656809204,1000,paired source-video group resample,,,,,C0,-0.028561943473659146,-0.02652153253376366,-0.07266201214044957,0.01892683603052193, +C7_distill,0.5/partial,mae,0.7164063453674316,0.7164032757282257,0.6678135842084885,0.7664204359054565,1000,paired source-video group resample,0.042109787464141846,0.041626423597335815,0.019549334049224855,0.0677413135766983,C0,-0.06905275583267212,-0.07052019238471985,-0.11103559136390687,-0.030912864208221442, +C7_distill,0.5/partial,rmse,0.9644542942835725,0.9646912711233642,0.8845374994636416,1.0461536899581285,1000,paired source-video group resample,,,,,C0,-0.035156501052876266,-0.03762870598402701,-0.09452634667840905,0.024884047018688814, +C7_distill,0.5/partial,pearson,0.5545317530632019,0.5539657771587372,0.4830300033092499,0.6198525220155716,1000,paired source-video group resample,,,,,C0,0.07312613725662231,0.07422494888305664,0.015472187846899032,0.12934360504150388, +C7_distill,0.5/async,accuracy,0.5906593406593407,0.5911257816374396,0.5506843280429666,0.6307988370893222,1000,paired source-video group resample,,,,,C0,0.017857142857142905,0.01881626300943484,-0.019352099499202063,0.058173762203157356, +C7_distill,0.5/async,macro_f1,0.5076204822568879,0.5075891464484084,0.4712054272952846,0.5432624388281764,1000,paired source-video group resample,,,,,C0,-0.03302751417763883,-0.03227282642533205,-0.07758113712095108,0.008820623348970099, +C7_distill,0.5/async,mae,0.7036042213439941,0.7035881578922272,0.6573852702975274,0.7517104104161263,1000,paired source-video group resample,0.029307663440704346,0.02998185157775879,0.010553285479545593,0.04835334569215774,C0,-0.08966046571731567,-0.08931323885917664,-0.12998494654893875,-0.05132149904966356, +C7_distill,0.5/async,rmse,0.9248570202821017,0.9235980034185514,0.8577800881501684,1.0014184036330092,1000,paired source-video group resample,,,,,C0,-0.07847071336206912,-0.07881725271277695,-0.12554097337905942,-0.02635931238066445, +C7_distill,0.5/async,pearson,0.5872247815132141,0.5876753032207489,0.5228972285985947,0.6455265328288078,1000,paired source-video group resample,,,,,C0,0.11273008584976196,0.11231574416160583,0.0643603965640068,0.1583224631845951, +C7_distill,0.7/single,accuracy,0.5865384615384616,0.5868828503917423,0.5497096423796791,0.6276372381417562,1000,paired source-video group resample,,,,,C0,0.0013736263736263687,0.002756720813147151,-0.03385971289318476,0.039278596694602035, +C7_distill,0.7/single,macro_f1,0.5153735153735154,0.5148647230498828,0.4836920153488018,0.5481545609005491,1000,paired source-video group resample,,,,,C0,-0.035937457128981665,-0.035227423215297926,-0.07847508350925866,0.0071011739404850385, +C7_distill,0.7/single,mae,0.7121081352233887,0.7119297683238983,0.6669688060879707,0.7624439388513564,1000,paired source-video group resample,0.03781157732009888,0.0380876362323761,0.02412579655647278,0.05218825191259384,C0,-0.07584047317504883,-0.07575514912605286,-0.11472276896238327,-0.035507234930992136, +C7_distill,0.7/single,rmse,0.9321715243764459,0.9296760699694333,0.8580058497506042,1.0109194232519376,1000,paired source-video group resample,,,,,C0,-0.07815247104748257,-0.07844172611344508,-0.1329360406261115,-0.021197291243518584, +C7_distill,0.7/single,pearson,0.5826635360717773,0.5834218859672546,0.5148316353559494,0.6421331897377968,1000,paired source-video group resample,,,,,C0,0.11002331972122192,0.11061714589595795,0.06005273535847664,0.15870301946997642, +C7_distill,0.7/sync,accuracy,0.5865384615384616,0.5870476131355143,0.5477130564243297,0.6278845783056505,1000,paired source-video group resample,,,,,C0,0.004120879120879106,0.0053086184910419165,-0.033143604970765024,0.04097067748253093, +C7_distill,0.7/sync,macro_f1,0.4850243746615983,0.48489593312190615,0.45421659857783314,0.5179704221662473,1000,paired source-video group resample,,,,,C0,-0.06391512543876576,-0.0630280492103896,-0.10617655870170274,-0.021559936177854774, +C7_distill,0.7/sync,mae,0.7548737525939941,0.7546645104885101,0.7039392650127411,0.8045631185173988,1000,paired source-video group resample,0.08057719469070435,0.08026045560836792,0.05458658188581467,0.10640192776918411,C0,-0.02849787473678589,-0.02868911623954773,-0.07710551917552948,0.01653991639614102, +C7_distill,0.7/sync,rmse,0.9805789596807174,0.9793579222510591,0.9056661508458368,1.058255524350755,1000,paired source-video group resample,,,,,C0,-0.03957648187658014,-0.040467968468266835,-0.09584319629286771,0.015264535847759431, +C7_distill,0.7/sync,pearson,0.5589423775672913,0.5600906610488892,0.49219213575124743,0.6233824744820595,1000,paired source-video group resample,,,,,C0,0.08049732446670532,0.08094128966331482,0.033012958616018294,0.13404306843876837, +C7_distill,0.7/partial,accuracy,0.5892857142857143,0.5900214147120328,0.5495948880138517,0.6290103252800648,1000,paired source-video group resample,,,,,C0,-0.004120879120879106,-0.0041637771613499686,-0.04245612030033529,0.0338661815987124, +C7_distill,0.7/partial,macro_f1,0.48734234269197635,0.48666363786972394,0.4545290704937692,0.5198897707812714,1000,paired source-video group resample,,,,,C0,-0.07667109452463411,-0.07755519218618467,-0.11988173366588986,-0.03680028249365032, +C7_distill,0.7/partial,mae,0.7626818418502808,0.762523740530014,0.7157208919525146,0.8131907925009727,1000,paired source-video group resample,0.08838528394699097,0.08925360441207886,0.05977867692708969,0.11462043672800064,C0,-0.03490948677062988,-0.03451251983642578,-0.07843362987041473,0.007879516482353195, +C7_distill,0.7/partial,rmse,0.9909259555592903,0.9907483893181938,0.9188254769849737,1.0636869086081981,1000,paired source-video group resample,,,,,C0,-0.026530736207625583,-0.02658144361573611,-0.0792827404242091,0.026276626332940346, +C7_distill,0.7/partial,pearson,0.5498490929603577,0.550658792257309,0.4826948933303356,0.609789402782917,1000,paired source-video group resample,,,,,C0,0.05737227201461792,0.058413177728652954,0.00563354715704918,0.10715115815401076, +C7_distill,0.7/async,accuracy,0.5810439560439561,0.5816782527359083,0.5438664499872183,0.6210302703246804,1000,paired source-video group resample,,,,,C0,0.0027472527472527375,0.002857148688058586,-0.03616523106371347,0.041321345036290424, +C7_distill,0.7/async,macro_f1,0.48348889101970594,0.4830793856105735,0.45182589140920437,0.515556313730908,1000,paired source-video group resample,,,,,C0,-0.07030917198819786,-0.07010676664612217,-0.11148036540392178,-0.02834788087955662, +C7_distill,0.7/async,mae,0.7557876110076904,0.7558473944664001,0.70846586227417,0.805910274386406,1000,paired source-video group resample,0.08149105310440063,0.08190485835075378,0.050260809063911435,0.11501872986555099,C0,-0.060671985149383545,-0.06021204590797424,-0.10679725110530854,-0.011679726839065563, +C7_distill,0.7/async,rmse,0.9806256415691429,0.9807333382940753,0.9072710913578375,1.0592110288768282,1000,paired source-video group resample,,,,,C0,-0.06016923720521128,-0.060490041295422625,-0.12395601742896555,0.007752015404125323, +C7_distill,0.7/async,pearson,0.5574042201042175,0.558440774679184,0.49193322062492373,0.6169944375753402,1000,paired source-video group resample,,,,,C0,0.0782080590724945,0.07976986467838287,0.01790475696325302,0.13008299469947812, +C7_distill,0.3/modality_T,accuracy,0.5947802197802198,0.5960764550652398,0.5586785998134006,0.634122744228814,1000,paired source-video group resample,,,,,C0,0.008241758241758212,0.009222725434273549,-0.028449646694190988,0.046484483826033055, +C7_distill,0.3/modality_T,macro_f1,0.5192083738317917,0.519234006608307,0.484730760058751,0.5543438517311922,1000,paired source-video group resample,,,,,C0,-0.02755493961191502,-0.026613968273849153,-0.06935872222674329,0.019855188645475193, +C7_distill,0.3/modality_T,mae,0.6946868300437927,0.6947642266750336,0.6473287269473076,0.7446799203753471,1000,paired source-video group resample,0.02039027214050293,0.020387232303619385,0.004560258984565735,0.03989474475383758,C0,-0.055436909198760986,-0.05494081974029541,-0.09478776752948762,-0.01647791713476181, 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resample,,,,,C0,0.0027472527472527375,0.004231311706629104,-0.03371042211539864,0.03674303568371357, +C7_distill,0.3/modality_V,macro_f1,0.5245944271283881,0.5249685599141538,0.4924328779103849,0.5570136678101528,1000,paired source-video group resample,,,,,C0,-0.02649891885446065,-0.025262592265043737,-0.0667718076953686,0.013910528206883745, +C7_distill,0.3/modality_V,mae,0.6733604073524475,0.673448383808136,0.628836740553379,0.7251293703913688,1000,paired source-video group resample,-0.0009361505508422852,-0.0008414089679718018,-0.0027210935950279236,0.0001557081937789916,C0,-0.05997270345687866,-0.06058821082115173,-0.0965325728058815,-0.02464079558849335, +C7_distill,0.3/modality_V,rmse,0.8973722694271473,0.8960951599791587,0.8214713856938973,0.9774405933478599,1000,paired source-video group resample,,,,,C0,-0.04042046288547907,-0.041783229044351444,-0.09324790011839273,0.013094681007560428, +C7_distill,0.3/modality_V,pearson,0.6015283465385437,0.602138489484787,0.5355728521943093,0.6630158677697182,1000,paired source-video group resample,,,,,C0,0.08208250999450684,0.08272205293178558,0.034135088324546814,0.12946362793445584, +C7_distill,0.3/modality_TA,accuracy,0.5947802197802198,0.595743824520803,0.5579032718280388,0.6327320917057814,1000,paired source-video group resample,,,,,C0,0.008241758241758212,0.008834821909763646,-0.028856760594145884,0.04414098345018358, +C7_distill,0.3/modality_TA,macro_f1,0.5199177365844032,0.5196072359307294,0.48717070015171804,0.5537822282155913,1000,paired source-video group resample,,,,,C0,-0.034280550575889635,-0.032877504250569956,-0.07673652961375414,0.006536458230003424, +C7_distill,0.3/modality_TA,mae,0.7061866521835327,0.7062560021877289,0.6602426931262017,0.7566446036100387,1000,paired source-video group resample,0.03189009428024292,0.03202393651008606,0.011731351912021636,0.05590074360370636,C0,-0.06939888000488281,-0.06991466879844666,-0.10567143708467483,-0.030653555691242222, +C7_distill,0.3/modality_TA,rmse,0.9429765323295655,0.9417200950357927,0.8599773082280091,1.0208415260606627,1000,paired source-video group resample,,,,,C0,-0.027644554023871337,-0.028716967345126077,-0.0856525572179196,0.026825081104459778, +C7_distill,0.3/modality_TA,pearson,0.5715773105621338,0.5718263387680054,0.5027128353714942,0.6334102675318718,1000,paired source-video group resample,,,,,C0,0.07313734292984009,0.07376320660114288,0.021099844574928285,0.127231627702713, +C7_distill,0.3/modality_TV,accuracy,0.5906593406593407,0.5915006490208251,0.5550873837594086,0.6270703102207528,1000,paired source-video group resample,,,,,C0,0.008241758241758212,0.00898593856340335,-0.029038212178147164,0.045865384615384565, +C7_distill,0.3/modality_TV,macro_f1,0.5183560679594418,0.5178348165630169,0.48569165906760975,0.5500030951554687,1000,paired source-video group resample,,,,,C0,-0.026488520029416485,-0.025607245808237727,-0.06840885557154246,0.016455201759250797, +C7_distill,0.3/modality_TV,mae,0.6997418403625488,0.6993273198604584,0.6541124239563942,0.7494101867079734,1000,paired source-video group resample,0.025445282459259033,0.025557249784469604,0.009362910687923432,0.04262477606534957,C0,-0.06093192100524902,-0.061533212661743164,-0.10083538591861725,-0.022665432095527648, +C7_distill,0.3/modality_TV,rmse,0.9291589019576403,0.9273285468364504,0.8531211069554229,1.0079735592633159,1000,paired source-video group resample,,,,,C0,-0.03840818884824859,-0.03932879004374873,-0.09588107211240526,0.017934636385611203, +C7_distill,0.3/modality_TV,pearson,0.5814394354820251,0.5822694301605225,0.5133730962872505,0.6435210302472114,1000,paired source-video group resample,,,,,C0,0.08245262503623962,0.08332760632038116,0.032814668118953706,0.13317600786685943, +C7_distill,0.3/modality_AV,accuracy,0.5906593406593407,0.591781614376728,0.5526269782848731,0.6288689675780667,1000,paired source-video group resample,,,,,C0,-0.004120879120879106,-0.002756720813147151,-0.04071251418021658,0.03271113392257356, +C7_distill,0.3/modality_AV,macro_f1,0.5245652929925231,0.5248410536761747,0.49113665465826695,0.5563664435581267,1000,paired source-video group resample,,,,,C0,-0.03513291324658907,-0.03291014530848102,-0.07581260638852363,0.006850160218064814, +C7_distill,0.3/modality_AV,mae,0.6713489890098572,0.6712960600852966,0.6268315866589547,0.7211116388440132,1000,paired source-video group resample,-0.002947568893432617,-0.00260201096534729,-0.011015002429485322,0.003166012465953826,C0,-0.06663185358047485,-0.06764599680900574,-0.10248487740755081,-0.031331712007522584, +C7_distill,0.3/modality_AV,rmse,0.8932219005470832,0.8916710960688377,0.8165255680437399,0.9744122982446838,1000,paired source-video group resample,,,,,C0,-0.04881332695450735,-0.04939332734791668,-0.10097040135245595,0.006628042245999296, +C7_distill,0.3/modality_AV,pearson,0.6044967770576477,0.6051116287708282,0.5364830702543258,0.6646781876683235,1000,paired source-video group resample,,,,,C0,0.0889628529548645,0.08943906426429749,0.04099344909191131,0.1359222002327442, +C7_distill,0.3/modality_TAV,accuracy,0.5879120879120879,0.5890603085553997,0.5498593863833745,0.627877532763268,1000,paired source-video group resample,,,,,C0,0.006868131868131844,0.008310249307479256,-0.032582591084098445,0.04309518629035604, +C7_distill,0.3/modality_TAV,macro_f1,0.5147849485115562,0.5144073493852948,0.4808208044060947,0.5501043723866026,1000,paired source-video group resample,,,,,C0,-0.02969295009272599,-0.027641470662437356,-0.07734384926280714,0.0150883558125438, +C7_distill,0.3/modality_TAV,mae,0.6974321007728577,0.6968929469585419,0.6521423399448395,0.7461807280778885,1000,paired source-video group resample,0.02313554286956787,0.022753745317459106,0.007589377462863922,0.04113237261772155,C0,-0.07349961996078491,-0.07392251491546631,-0.11290178447961807,-0.03587398529052735, +C7_distill,0.3/modality_TAV,rmse,0.9251677657397854,0.92396339493315,0.8476599028484353,1.0018461583149718,1000,paired source-video group resample,,,,,C0,-0.0548699959215837,-0.05477892453396682,-0.11073174448259623,-0.0003495624331930777, +C7_distill,0.3/modality_TAV,pearson,0.5849357843399048,0.5851230621337891,0.5171891763806343,0.6454131096601486,1000,paired source-video group resample,,,,,C0,0.0946262776851654,0.09553119540214539,0.042677213251590726,0.14371188804507254, +C7_distill,0.3/location_start_T,accuracy,0.5865384615384616,0.5868967957853,0.5496330468093058,0.6270155756827226,1000,paired source-video group resample,,,,,C0,-0.005494505494505475,-0.00431727073946464,-0.04447620496768402,0.03222479928078213, +C7_distill,0.3/location_start_T,macro_f1,0.511511062493729,0.5109431765691871,0.4786242676989837,0.5464299612959141,1000,paired source-video group resample,,,,,C0,-0.0496801110745938,-0.04908354181329372,-0.09257846351853782,-0.006570791773460525, +C7_distill,0.3/location_start_T,mae,0.6997548937797546,0.7004909813404083,0.650605072081089,0.7498735457658767,1000,paired source-video group resample,0.025458335876464844,0.02501848340034485,0.008404280245304107,0.047305004298686976,C0,-0.06950628757476807,-0.06951457262039185,-0.11113393753767013,-0.025582835078239448, +C7_distill,0.3/location_start_T,rmse,0.9341963096382427,0.9345761002384726,0.8581421110366263,1.0108052004308965,1000,paired source-video group resample,,,,,C0,-0.041117619973817354,-0.040763975147070586,-0.10209571268660057,0.021783315828817346, +C7_distill,0.3/location_start_T,pearson,0.573676586151123,0.5727472901344299,0.5030914038419724,0.6352327063679695,1000,paired source-video group resample,,,,,C0,0.09112712740898132,0.09068268537521362,0.032665193825960157,0.15082657411694528, +C7_distill,0.3/location_middle_T,accuracy,0.5892857142857143,0.5907756768371294,0.551099396912974,0.6293146785425701,1000,paired source-video group resample,,,,,C0,0.0,0.0,-0.03435062920950017,0.03618347999161951, +C7_distill,0.3/location_middle_T,macro_f1,0.5171666262881364,0.5174655523559671,0.4835411400619016,0.5524796110315187,1000,paired source-video group resample,,,,,C0,-0.033634877398180496,-0.03349010671538216,-0.07267598545165946,0.008824815204031009, +C7_distill,0.3/location_middle_T,mae,0.6943658590316772,0.6948316991329193,0.6479435369372368,0.7462911918759346,1000,paired source-video group resample,0.02006930112838745,0.020093142986297607,0.006144402921199799,0.03583133518695831,C0,-0.054401516914367676,-0.05493214726448059,-0.09163549393415452,-0.016085788607597365, +C7_distill,0.3/location_middle_T,rmse,0.9291662469928518,0.9280852569939539,0.8493172425603451,1.0113184883340545,1000,paired source-video group resample,,,,,C0,-0.03229102775796344,-0.033685807258413414,-0.09039575870584145,0.026720466978381877, +C7_distill,0.3/location_middle_T,pearson,0.5807386040687561,0.5809126496315002,0.5066337808966637,0.6427140384912491,1000,paired source-video group resample,,,,,C0,0.07378429174423218,0.07456320524215698,0.019672539830207825,0.12626676633954048, +C7_distill,0.3/location_end_T,accuracy,0.592032967032967,0.592148892077156,0.555237324391513,0.6325663232979746,1000,paired source-video group resample,,,,,C0,0.017857142857142905,0.017985820367824368,-0.01849789069798925,0.05387206958339555, +C7_distill,0.3/location_end_T,macro_f1,0.508251376876906,0.507541153043402,0.4767374366699536,0.5418498900456253,1000,paired source-video group resample,,,,,C0,-0.02971679705298702,-0.02920279668669512,-0.07104017690971683,0.012464339621292963, +C7_distill,0.3/location_end_T,mae,0.7089433073997498,0.707521378993988,0.6602432638406753,0.7607051759958268,1000,paired source-video group resample,0.03464674949645996,0.03412443399429321,0.01472640484571457,0.05503742396831512,C0,-0.060209572315216064,-0.06058397889137268,-0.09522953182458878,-0.023120445013046286, +C7_distill,0.3/location_end_T,rmse,0.9328048437369824,0.9305284181267538,0.8539690453504174,1.0146862391772464,1000,paired source-video group resample,,,,,C0,-0.04472772499105837,-0.04542460114788649,-0.09811680914187376,0.006692929092024299, +C7_distill,0.3/location_end_T,pearson,0.5851706862449646,0.5853226184844971,0.5163966983556747,0.6515783235430718,1000,paired source-video group resample,,,,,C0,0.07848608493804932,0.07891014218330383,0.03704736083745957,0.12466247826814651, +C7_distill,0.3/span_long_T,accuracy,0.592032967032967,0.592329157969395,0.5554015636804331,0.6306896114477496,1000,paired source-video group resample,,,,,C0,0.013736263736263687,0.014385802521395707,-0.022507969798657684,0.046035679173239995, +C7_distill,0.3/span_long_T,macro_f1,0.5125667684491214,0.5122729963240038,0.4799953601020151,0.5453390548139612,1000,paired source-video group resample,,,,,C0,-0.02753770662087973,-0.027322044853759553,-0.06878362451307288,0.011970820822642433, +C7_distill,0.3/span_long_T,mae,0.7017372250556946,0.7019736170768738,0.6543315097689628,0.7517513692378998,1000,paired source-video group resample,0.027440667152404785,0.027653217315673828,0.012463870644569396,0.044088572263717644,C0,-0.04738432168960571,-0.047442883253097534,-0.08745871335268021,-0.007580976188182831, +C7_distill,0.3/span_long_T,rmse,0.9262595570800953,0.9245742273361444,0.8521730298197545,1.0044313622147973,1000,paired source-video group resample,,,,,C0,-0.03763836394477482,-0.0380153758322499,-0.09647983677421768,0.021689746766816585, +C7_distill,0.3/span_long_T,pearson,0.5866219401359558,0.586455374956131,0.5215354666113854,0.643990334868431,1000,paired source-video group resample,,,,,C0,0.08664283156394958,0.08736924827098846,0.03461035862565041,0.1369426868855953, +C7_distill,0.3/span_multi_short_T,accuracy,0.592032967032967,0.5923573139274123,0.5541462478426754,0.6315162795314672,1000,paired source-video group resample,,,,,C0,0.004120879120879106,0.004249368513342955,-0.03369843687711892,0.04092023170570685, +C7_distill,0.3/span_multi_short_T,macro_f1,0.5111374501205009,0.5107062585872539,0.4787582337028978,0.5446505701432347,1000,paired source-video group resample,,,,,C0,-0.04040700516611739,-0.03929941135128373,-0.08392073244235776,0.004278286390313668, +C7_distill,0.3/span_multi_short_T,mae,0.6955581307411194,0.6953039467334747,0.6512055113911629,0.7451452136039733,1000,paired source-video group resample,0.02126157283782959,0.021413981914520264,0.004025085270404816,0.037314364314079286,C0,-0.055897414684295654,-0.056505173444747925,-0.09330360442399979,-0.019634070992469804, +C7_distill,0.3/span_multi_short_T,rmse,0.9115187307056035,0.9104712068526901,0.8389826764924737,0.985207433275808,1000,paired source-video group resample,,,,,C0,-0.04917937497477798,-0.05015032383667262,-0.10129238609458963,0.0020993996395528227, +C7_distill,0.3/span_multi_short_T,pearson,0.6000438332557678,0.5999613106250763,0.5350381031632423,0.6591213122010231,1000,paired source-video group resample,,,,,C0,0.09843528270721436,0.09802880883216858,0.05136843174695969,0.14649087488651275, +C7_distill,0.3/location_start_A,accuracy,0.5865384615384616,0.5871288373365134,0.5498578561760261,0.624685668222229,1000,paired source-video group resample,,,,,C0,0.0027472527472527375,0.003997379466092799,-0.03289654424522839,0.039017883490426813, +C7_distill,0.3/location_start_A,macro_f1,0.5217154051385475,0.5212550761879229,0.4887563437277566,0.5530180486476892,1000,paired source-video group resample,,,,,C0,-0.03506475525867969,-0.0339892397077311,-0.07310510187444608,0.004658557627561564, +C7_distill,0.3/location_start_A,mae,0.6686100959777832,0.6685260534286499,0.6231258988380433,0.7166235342621803,1000,paired source-video group resample,-0.005686461925506592,-0.005317807197570801,-0.013961179554462433,0.001260645687580108,C0,-0.06638824939727783,-0.06721547245979309,-0.10155064016580581,-0.030364280939102192, +C7_distill,0.3/location_start_A,rmse,0.8884693627643341,0.886744407691737,0.8110578371323305,0.9688228138956763,1000,paired source-video group resample,,,,,C0,-0.052327984930333526,-0.05295446018246386,-0.10222628583316139,-0.004227346957742673, +C7_distill,0.3/location_start_A,pearson,0.6051310896873474,0.6059047877788544,0.537954394519329,0.6658692792057991,1000,paired source-video group resample,,,,,C0,0.08738744258880615,0.08780506253242493,0.04146420285105705,0.13367339819669724, +C7_distill,0.3/location_middle_A,accuracy,0.5934065934065934,0.5942237514336357,0.5565453123967287,0.6321156451786636,1000,paired source-video group resample,,,,,C0,0.006868131868131844,0.007968253968253958,-0.02929075108991429,0.042893567841700564, +C7_distill,0.3/location_middle_A,macro_f1,0.5279880392243421,0.528415051551042,0.4948033715157356,0.5598527389201126,1000,paired source-video group resample,,,,,C0,-0.0257747841036986,-0.02504664272509327,-0.06704133658624092,0.015366412643930795, +C7_distill,0.3/location_middle_A,mae,0.6700723171234131,0.6692034006118774,0.624186922609806,0.7232516944408417,1000,paired source-video group resample,-0.004224240779876709,-0.004397839307785034,-0.01286969631910324,0.00425346791744232,C0,-0.06395095586776733,-0.06475692987442017,-0.09856860786676407,-0.029360660910606386, +C7_distill,0.3/location_middle_A,rmse,0.8987304541593942,0.8969724511803168,0.8160917799386241,0.9860678434899969,1000,paired source-video group resample,,,,,C0,-0.03804848149424378,-0.03920280113741237,-0.08856048734603063,0.013794573684570858, +C7_distill,0.3/location_middle_A,pearson,0.5992106199264526,0.6003622114658356,0.5264560267329216,0.6625092923641205,1000,paired source-video group resample,,,,,C0,0.07884937524795532,0.0796349048614502,0.03374694138765335,0.12462671250104904, +C7_distill,0.3/location_end_A,accuracy,0.592032967032967,0.593147622644591,0.5551238851418959,0.6300445474814678,1000,paired source-video group resample,,,,,C0,0.0027472527472527375,0.004279635406809534,-0.03338339408880978,0.0392170612985727, +C7_distill,0.3/location_end_A,macro_f1,0.5257562617604755,0.5259976558034957,0.49288454623091643,0.5586900173560612,1000,paired source-video group resample,,,,,C0,-0.027642899504583207,-0.026244345129251168,-0.06817249285481679,0.01389443990516225, +C7_distill,0.3/location_end_A,mae,0.6709986329078674,0.6706001460552216,0.6257254689931869,0.7219357162714004,1000,paired source-video group resample,-0.0032979249954223633,-0.003197789192199707,-0.009822201728820801,0.00024319440126419062,C0,-0.063748300075531,-0.06450355052947998,-0.09854289442300797,-0.02886051535606384, +C7_distill,0.3/location_end_A,rmse,0.8935063583561916,0.8919099439289079,0.8161194970846114,0.974210789049681,1000,paired source-video group resample,,,,,C0,-0.04416306247220081,-0.04483848616030933,-0.0968802526195867,0.007185956383896068, +C7_distill,0.3/location_end_A,pearson,0.6050497889518738,0.6057990789413452,0.5369323626160621,0.6657649844884872,1000,paired source-video group resample,,,,,C0,0.08609843254089355,0.08734464645385742,0.03716939836740494,0.13389579057693482, +C7_distill,0.3/span_long_A,accuracy,0.5892857142857143,0.5899231568423735,0.5530553338653897,0.6275790008433542,1000,paired source-video group resample,,,,,C0,0.0013736263736263687,0.002735983232277861,-0.03607818352968586,0.03677660155413324, +C7_distill,0.3/span_long_A,macro_f1,0.5250774567847739,0.525118953729115,0.49279417632716055,0.5570563649206148,1000,paired source-video group resample,,,,,C0,-0.029259823868296175,-0.027594737187199847,-0.07111901321233083,0.012257761630706094, +C7_distill,0.3/span_long_A,mae,0.6705284714698792,0.6703748106956482,0.6265886694192886,0.7200691744685173,1000,paired source-video group resample,-0.0037680864334106445,-0.0034088194370269775,-0.011933787167072296,0.0017926305532455443,C0,-0.06613039970397949,-0.06685546040534973,-0.10236429125070572,-0.03150907009840012, +C7_distill,0.3/span_long_A,rmse,0.8910990340256616,0.8893675041272173,0.8148084445926076,0.971022117500531,1000,paired source-video group resample,,,,,C0,-0.04685404252770098,-0.047866737611949595,-0.09816366797897082,0.005050692748724673, +C7_distill,0.3/span_long_A,pearson,0.6059636473655701,0.6067139804363251,0.5382882699370384,0.6663716614246368,1000,paired source-video group resample,,,,,C0,0.08843374252319336,0.08957453072071075,0.03986045867204666,0.1358846791088581, +C7_distill,0.3/span_multi_short_A,accuracy,0.592032967032967,0.5928734659331358,0.5555516098484848,0.6301839464882943,1000,paired source-video group resample,,,,,C0,-0.0027472527472527375,-0.0013633423541307144,-0.04016165541424612,0.03213175281772256, +C7_distill,0.3/span_multi_short_A,macro_f1,0.5270259629279203,0.5276013338929464,0.4946265398069199,0.5592635871576491,1000,paired source-video group resample,,,,,C0,-0.03325187265608809,-0.0313808484432016,-0.07478478345986984,0.009257381650864753, +C7_distill,0.3/span_multi_short_A,mae,0.6682427525520325,0.667974203824997,0.6238143503665924,0.7178728193044662,1000,paired source-video group resample,-0.006053805351257324,-0.005666643381118774,-0.013908930122852325,-0.0006822109222412111,C0,-0.06788128614425659,-0.06885984539985657,-0.10417300164699554,-0.03224437534809114, +C7_distill,0.3/span_multi_short_A,rmse,0.8897555943093743,0.8880420824203448,0.8125822806928462,0.9694787975682649,1000,paired source-video group resample,,,,,C0,-0.051890555335923794,-0.0526357041795652,-0.10422388333752365,-0.00041500408262782875, +C7_distill,0.3/span_multi_short_A,pearson,0.6068456768989563,0.607517421245575,0.5388862460851669,0.6679799452424049,1000,paired source-video group resample,,,,,C0,0.09054529666900635,0.09150362014770508,0.040971417725086216,0.13902794644236566, +C7_distill,0.3/location_start_V,accuracy,0.5851648351648352,0.5859869357004028,0.5483202475597913,0.6224138489155705,1000,paired source-video group resample,,,,,C0,-0.01098901098901095,-0.010379990379990378,-0.04803008758958031,0.024851350264422513, +C7_distill,0.3/location_start_V,macro_f1,0.5226160970625854,0.5228840973764317,0.49024829853994767,0.5553025680497399,1000,paired source-video group resample,,,,,C0,-0.04119457670737492,-0.04066911956922248,-0.08350382089934301,0.001207561886557944, +C7_distill,0.3/location_start_V,mae,0.6726104021072388,0.6727112829685211,0.62862678617239,0.7227315619587898,1000,paired source-video group resample,-0.0016861557960510254,-0.001611471176147461,-0.007016089558601379,0.003793840110301971,C0,-0.06083601713180542,-0.060983747243881226,-0.096743842959404,-0.024960075318813335, +C7_distill,0.3/location_start_V,rmse,0.8949409113190966,0.894028751433158,0.8191687469236911,0.9738784956392427,1000,paired source-video group resample,,,,,C0,-0.04190040875211343,-0.04294075197886266,-0.09468932476367944,0.011747525564280653, +C7_distill,0.3/location_start_V,pearson,0.6025909185409546,0.6028980910778046,0.5356074452400208,0.6632341027259827,1000,paired source-video group resample,,,,,C0,0.0815504789352417,0.08217790722846985,0.03459882363677025,0.12941626384854316, +C7_distill,0.3/location_middle_V,accuracy,0.5879120879120879,0.5886924383178503,0.5510802915387802,0.6269081555365381,1000,paired source-video group resample,,,,,C0,-0.004120879120879106,-0.002873563218390829,-0.042662128382990626,0.03251832340815395, +C7_distill,0.3/location_middle_V,macro_f1,0.5222388556015782,0.5222330889699146,0.48874724262055597,0.5550711524044112,1000,paired source-video group resample,,,,,C0,-0.033470123434837906,-0.03197739787166748,-0.07514134408986836,0.007612023496054784, +C7_distill,0.3/location_middle_V,mae,0.6742833256721497,0.6743028461933136,0.6302674368023873,0.7240989565849304,1000,paired source-video group resample,-1.3232231140136719e-05,0.00012862682342529297,-0.004249100387096405,0.004477374255657195,C0,-0.05952674150466919,-0.06025487184524536,-0.09509901106357574,-0.02402684837579727, +C7_distill,0.3/location_middle_V,rmse,0.8969830889814144,0.8960247481866479,0.8212611897326221,0.9769641132564781,1000,paired source-video group resample,,,,,C0,-0.04189811732717852,-0.04263185253662044,-0.09527946894600098,0.011915367146359237, +C7_distill,0.3/location_middle_V,pearson,0.6010740995407104,0.601414680480957,0.5349899351596832,0.662963704764843,1000,paired source-video group resample,,,,,C0,0.082050621509552,0.08214333653450012,0.03271427452564239,0.12993568852543827, +C7_distill,0.3/location_end_V,accuracy,0.5892857142857143,0.5900574229255579,0.5535174514868534,0.6275389403323726,1000,paired source-video group resample,,,,,C0,0.0,0.0014234882655934644,-0.036171074915980775,0.03566871977623364, +C7_distill,0.3/location_end_V,macro_f1,0.5217744545289903,0.521713360400419,0.48937275686464776,0.55401015911241,1000,paired source-video group resample,,,,,C0,-0.03150194034168152,-0.029725412413604407,-0.07168657286203942,0.010412322389242544, +C7_distill,0.3/location_end_V,mae,0.6765652894973755,0.6766910254955292,0.6315081119537354,0.7274621039628982,1000,paired source-video group resample,0.0022687315940856934,0.002120107412338257,-0.0005014717578887939,0.0065403372049331636,C0,-0.05665308237075806,-0.057062387466430664,-0.09234251528978348,-0.020261269807815552, +C7_distill,0.3/location_end_V,rmse,0.9007022012399275,0.8995318836314441,0.8249479137158253,0.9813251909020665,1000,paired source-video group resample,,,,,C0,-0.03674229327173273,-0.03788434234190541,-0.08924746663584238,0.02009111701950057, +C7_distill,0.3/location_end_V,pearson,0.5992234945297241,0.5997799336910248,0.532473674416542,0.659912383556366,1000,paired source-video group resample,,,,,C0,0.08007508516311646,0.08044786751270294,0.03173875361680985,0.126864992082119, +C7_distill,0.3/span_long_V,accuracy,0.5892857142857143,0.5905146560034275,0.5519125683060109,0.6269574760748047,1000,paired source-video group resample,,,,,C0,0.004120879120879106,0.005555598422827324,-0.03253552245980902,0.03950108048919333, +C7_distill,0.3/span_long_V,macro_f1,0.5263450347681772,0.5267274688536974,0.492837814942206,0.5593378709279828,1000,paired source-video group resample,,,,,C0,-0.02226848199993947,-0.020488124279846864,-0.0627092426793134,0.017648390836683715, +C7_distill,0.3/span_long_V,mae,0.673602283000946,0.6737315952777863,0.6286977872252464,0.7244439050555229,1000,paired source-video group resample,-0.00069427490234375,-0.0005064308643341064,-0.004475826025009155,0.002841418981552124,C0,-0.060756027698516846,-0.061134010553359985,-0.0976147323846817,-0.025608891248703008, +C7_distill,0.3/span_long_V,rmse,0.8982034461286371,0.8970906818369763,0.8217884522837688,0.9776390512642339,1000,paired source-video group resample,,,,,C0,-0.03962869158999682,-0.04036632295576298,-0.0902646795460408,0.014181832341889307, +C7_distill,0.3/span_long_V,pearson,0.6009500622749329,0.6016150414943695,0.5359371811151504,0.6612360388040542,1000,paired source-video group resample,,,,,C0,0.0810694694519043,0.08149009943008423,0.03391572535037994,0.12862801775336266, +C7_distill,0.3/span_multi_short_V,accuracy,0.5892857142857143,0.5902300597952772,0.5511241883116883,0.6272399284426952,1000,paired source-video group resample,,,,,C0,0.0013736263736263687,0.002737913638595435,-0.03381181543923652,0.03689543519608728, +C7_distill,0.3/span_multi_short_V,macro_f1,0.5265223800406479,0.5267093067519125,0.49305027239517607,0.5589544428042464,1000,paired source-video group resample,,,,,C0,-0.024936937790260294,-0.02338690026239476,-0.06457080906487152,0.015380651404821352, +C7_distill,0.3/span_multi_short_V,mae,0.6738946437835693,0.6741203963756561,0.6279231205582618,0.7255858913064003,1000,paired source-video group resample,-0.000401914119720459,-0.0003624558448791504,-0.004348385334014893,0.003275589644908904,C0,-0.05970829725265503,-0.060562342405319214,-0.0964906558394432,-0.024494048953056336, +C7_distill,0.3/span_multi_short_V,rmse,0.8984012430587518,0.8974059694332637,0.822382501361274,0.9774610899207122,1000,paired source-video group resample,,,,,C0,-0.03953159337315182,-0.04085857481532279,-0.09272813584170177,0.014276347280963721, +C7_distill,0.3/span_multi_short_V,pearson,0.6009039282798767,0.6017521023750305,0.5356794282793998,0.6621970519423485,1000,paired source-video group resample,,,,,C0,0.08138793706893921,0.08122289180755615,0.03273535370826721,0.12928597107529638, +C7_distill,0.3/synchrony_sync,accuracy,0.5892857142857143,0.5912806539509536,0.5526543651287154,0.628326892069861,1000,paired source-video group resample,,,,,C0,0.0013736263736263687,0.0026666856297644648,-0.03314140939704176,0.03727809070775977, +C7_distill,0.3/synchrony_sync,macro_f1,0.5107037624967199,0.5112160640457266,0.4801103418385947,0.5421913080604649,1000,paired source-video group resample,,,,,C0,-0.03824846851704222,-0.036246734041671,-0.07899812418812388,0.007226316313026784, +C7_distill,0.3/synchrony_sync,mae,0.6894748210906982,0.6890571415424347,0.6434470936655998,0.7394608318805694,1000,paired source-video group resample,0.015178263187408447,0.015277504920959473,0.0034982457756996153,0.02800145447254181,C0,-0.05346578359603882,-0.054451435804367065,-0.09364304393529892,-0.017422701418399814, +C7_distill,0.3/synchrony_sync,rmse,0.9127572676767112,0.9108539739099674,0.834995148772472,0.992656360577949,1000,paired source-video group resample,,,,,C0,-0.03863594367512191,-0.040228594322089306,-0.09493620665174633,0.017938166895502525, +C7_distill,0.3/synchrony_sync,pearson,0.5965097546577454,0.597542017698288,0.5316047444939613,0.6544020518660545,1000,paired source-video group resample,,,,,C0,0.08158522844314575,0.08256110548973083,0.0320400357246399,0.13234525099396705, +C7_distill,0.3/synchrony_partial,accuracy,0.5989010989010989,0.6002739422939901,0.5633579226167698,0.6392240739212935,1000,paired source-video group resample,,,,,C0,0.006868131868131844,0.008185599821323886,-0.031774592560673394,0.04435300228124479, +C7_distill,0.3/synchrony_partial,macro_f1,0.5196887636246904,0.5196613250026905,0.4876246569541499,0.5550952181741832,1000,paired source-video group resample,,,,,C0,-0.037160163651610456,-0.03558440809398411,-0.08386127779740199,0.00843292362558079, +C7_distill,0.3/synchrony_partial,mae,0.6934294104576111,0.6935299634933472,0.6486360847949981,0.7421420931816101,1000,paired source-video group resample,0.01913285255432129,0.019563734531402588,0.004574090242385864,0.033177582919597624,C0,-0.06152564287185669,-0.06281894445419312,-0.09907691925764084,-0.023076990246772768, +C7_distill,0.3/synchrony_partial,rmse,0.9126398802368259,0.9106624302975429,0.8383484375213571,0.9896236650921557,1000,paired source-video group resample,,,,,C0,-0.041108118869865984,-0.04277741611114838,-0.09635216332870689,0.020299393070330452, +C7_distill,0.3/synchrony_partial,pearson,0.5965877175331116,0.597480058670044,0.5305576860904694,0.6550495982170105,1000,paired source-video group resample,,,,,C0,0.0888434648513794,0.09023524820804596,0.039508777856826785,0.1366257794201374, +C7_distill,0.3/synchrony_async,accuracy,0.6016483516483516,0.6027877610490529,0.5651489777815776,0.6412223771453792,1000,paired source-video group resample,,,,,C0,0.006868131868131844,0.008321791320406335,-0.0262167554831866,0.038518432671920455, +C7_distill,0.3/synchrony_async,macro_f1,0.5241910459760358,0.524762006177373,0.4924334760294677,0.556449578674676,1000,paired source-video group resample,,,,,C0,-0.03315869915975045,-0.031876670669527485,-0.07265219122753162,0.0061678345953532976, +C7_distill,0.3/synchrony_async,mae,0.6821228861808777,0.6809988617897034,0.636540025472641,0.7304542064666748,1000,paired source-video group resample,0.00782632827758789,0.0077956318855285645,-0.010133339464664458,0.026425035297870634,C0,-0.0750998854637146,-0.07518711686134338,-0.11704703867435455,-0.03412115573883057, +C7_distill,0.3/synchrony_async,rmse,0.8991478143812776,0.8975776812693217,0.8216590667414341,0.9723952234039503,1000,paired source-video group resample,,,,,C0,-0.06794257050627872,-0.06884218064310288,-0.12292084701267827,-0.01673158240522675, +C7_distill,0.3/synchrony_async,pearson,0.6061596274375916,0.6058736443519592,0.5411302834749222,0.6672436848282813,1000,paired source-video group resample,,,,,C0,0.10844239592552185,0.10905477404594421,0.06067015379667282,0.16110027655959128, +C7_group,0.0/none,accuracy,0.6085164835164835,0.6083242533456262,0.569454949056182,0.6485508689140357,1000,paired source-video group resample,,,,,C0,0.016483516483516425,0.017731325476033122,-0.01846174142480207,0.04820088981261968, +C7_group,0.0/none,macro_f1,0.5116842947005743,0.510751229486049,0.47576602324031747,0.5451703583579719,1000,paired source-video group resample,,,,,C0,-0.0442503179504562,-0.04329673265612338,-0.08230913052278561,-0.007325194741830743, +C7_group,0.0/none,mae,0.6860519051551819,0.684800535440445,0.6337327554821968,0.7382403776049614,1000,paired source-video group resample,,,,,C0,-0.04736202955245972,-0.048021793365478516,-0.0856263816356659,-0.010593000054359437, +C7_group,0.0/none,rmse,0.9252575709031406,0.922528402723495,0.832944793088755,1.0152631820171787,1000,paired source-video group resample,,,,,C0,-0.01191608852504955,-0.01324818189621807,-0.06669098526357216,0.039001968440413454, +C7_group,0.0/none,pearson,0.5912197232246399,0.5943423211574554,0.5139355167746544,0.6582809448242187,1000,paired source-video group resample,,,,,C0,0.07197713851928711,0.072964608669281,0.0264721542596817,0.11937765926122665, +C7_group,0.1/single,accuracy,0.6085164835164835,0.608183277013995,0.5704267917001703,0.6478496588592759,1000,paired source-video group resample,,,,,C0,0.02060439560439553,0.021425277934320364,-0.014830374887998182,0.05390360700182704, +C7_group,0.1/single,macro_f1,0.5099890852385828,0.5089246968677967,0.4745980199921492,0.5425061277681338,1000,paired source-video group resample,,,,,C0,-0.03989571219832355,-0.03935438393708812,-0.07791421847495066,-0.0010681133932258467, +C7_group,0.1/single,mae,0.6862916946411133,0.6857656240463257,0.6339869767427444,0.7391699716448784,1000,paired source-video group resample,0.00023978948593139648,0.00042769312858581543,-0.0046255171298980715,0.004134218394756315,C0,-0.049467504024505615,-0.04994818568229675,-0.08776924163103103,-0.01154087483882904, +C7_group,0.1/single,rmse,0.9258597296434946,0.924023548950769,0.8342655685889487,1.0157228078465157,1000,paired source-video group resample,,,,,C0,-0.013462845917752597,-0.014771752945598349,-0.06855526313365609,0.03902677863393973, +C7_group,0.1/single,pearson,0.5910477042198181,0.5942170917987823,0.5131706088781357,0.6595304697751999,1000,paired source-video group resample,,,,,C0,0.07447218894958496,0.07571744918823242,0.029638907313346865,0.1216272547841072, +C7_group,0.1/sync,accuracy,0.5989010989010989,0.5980662061123607,0.5597864838430294,0.6401311630847029,1000,paired source-video group resample,,,,,C0,0.012362637362637319,0.01288475964435476,-0.0232445741646765,0.045727307039063955, +C7_group,0.1/sync,macro_f1,0.4895275318081212,0.48852041295979,0.4560694346315746,0.5227426884491202,1000,paired source-video group resample,,,,,C0,-0.06080053128663204,-0.06015022397957012,-0.10012231012474501,-0.023841207546297757, +C7_group,0.1/sync,mae,0.6929094791412354,0.6926961839199066,0.6395886182785034,0.7453372076153755,1000,paired source-video group resample,0.006857573986053467,0.00708615779876709,-0.004605121910572052,0.016555604338645932,C0,-0.0421333909034729,-0.0431266725063324,-0.08354423791170121,-0.0039006412029266384, +C7_group,0.1/sync,rmse,0.9213454455100748,0.9188594525004044,0.8303166302832988,1.0087877941467878,1000,paired source-video group resample,,,,,C0,-0.023837818845211856,-0.025057290009635358,-0.08025875668143286,0.03008911141660977, +C7_group,0.1/sync,pearson,0.5956986546516418,0.5973629355430603,0.5185720145702362,0.6634164810180664,1000,paired source-video group resample,,,,,C0,0.08229881525039673,0.08420537412166595,0.036534512788057326,0.1291866451501846, +C7_group,0.1/partial,accuracy,0.5975274725274725,0.5971929478971733,0.5591085059082496,0.637477362013988,1000,paired source-video group resample,,,,,C0,0.004120879120879106,0.0053263827938686,-0.03008703900876859,0.03679232041800166, +C7_group,0.1/partial,macro_f1,0.4907362260992237,0.4906311201601038,0.45570992756875467,0.523750018504948,1000,paired source-video group resample,,,,,C0,-0.06689671190408158,-0.06551934618311195,-0.10644044436053014,-0.030893257951465924, +C7_group,0.1/partial,mae,0.7017626166343689,0.7014385461807251,0.6487693458795547,0.7566681370139122,1000,paired source-video group resample,0.01571071147918701,0.015195608139038086,0.005768081545829773,0.028187198936939238,C0,-0.0334547758102417,-0.034307271242141724,-0.07364025563001633,0.006632977724075303, +C7_group,0.1/partial,rmse,0.9438621176506266,0.9406735558988117,0.8548484778796263,1.0331044106640472,1000,paired source-video group resample,,,,,C0,0.006418672243414525,0.003957857919987096,-0.05071482361107679,0.05840532576458552, +C7_group,0.1/partial,pearson,0.5769387483596802,0.5785171687602997,0.5030557230114937,0.645741319656372,1000,paired source-video group resample,,,,,C0,0.05636519193649292,0.05733323097229004,0.010741358995437622,0.1069808505475521, +C7_group,0.1/async,accuracy,0.5975274725274725,0.5974929146322301,0.5590190730441775,0.6378132144888177,1000,paired source-video group resample,,,,,C0,0.005494505494505475,0.006460336538461564,-0.028460898901904567,0.03920165615361097, +C7_group,0.1/async,macro_f1,0.48669941770158065,0.4865397768004045,0.4527395557750672,0.5197085040244708,1000,paired source-video group resample,,,,,C0,-0.07210760417782647,-0.0704093484531993,-0.11087190155411204,-0.036828192178290566, +C7_group,0.1/async,mae,0.69637531042099,0.6949160397052765,0.6419589802622795,0.7494164377450943,1000,paired source-video group resample,0.010323405265808105,0.010097026824951172,0.004392054677009582,0.016430382430553437,C0,-0.04251831769943237,-0.04278901219367981,-0.0822735995054245,-0.006479357182979598, +C7_group,0.1/async,rmse,0.9296973412257324,0.9271327736896322,0.8396439405305468,1.0200035914122978,1000,paired source-video group resample,,,,,C0,-0.014037300071791936,-0.014047485572649288,-0.07000724531419292,0.03410016614863068, +C7_group,0.1/async,pearson,0.5881722569465637,0.5909530520439148,0.5126119643449784,0.6564499899744988,1000,paired source-video group resample,,,,,C0,0.07415628433227539,0.0744219720363617,0.03066881224513054,0.12217312827706336, +C7_group,0.3/single,accuracy,0.5989010989010989,0.599232573530843,0.5592943795380524,0.6403394006018871,1000,paired source-video group resample,,,,,C0,-0.006868131868131844,-0.006863421215273058,-0.041921634259570746,0.026501713700703294, +C7_group,0.3/single,macro_f1,0.49015574781208127,0.48942848264115746,0.4564787973275808,0.52613464457757,1000,paired source-video group resample,,,,,C0,-0.07914350159636696,-0.07864945837030782,-0.11897048928119999,-0.04203983178587609, +C7_group,0.3/single,mae,0.7045457363128662,0.7039429247379303,0.6492564126849174,0.7560493767261505,1000,paired source-video group resample,0.018493831157684326,0.01837712526321411,0.010083113610744477,0.027966195344924925,C0,-0.026585400104522705,-0.027148723602294922,-0.06657329052686692,0.012126609683036797, +C7_group,0.3/single,rmse,0.9380842295815184,0.9355696831045297,0.8487357231612165,1.028743010070304,1000,paired source-video group resample,,,,,C0,-0.0016833451520265053,-0.002428781203724917,-0.05559074187338048,0.050892243139862535, +C7_group,0.3/single,pearson,0.583071768283844,0.5860426425933838,0.5064176127314568,0.6499664142727851,1000,paired source-video group resample,,,,,C0,0.061656177043914795,0.0625891387462616,0.018101969361305238,0.10707512795925139, +C7_group,0.3/sync,accuracy,0.6002747252747253,0.6002747382344672,0.5608353322139602,0.6425393282976465,1000,paired source-video group resample,,,,,C0,0.02060439560439553,0.02097902097902099,-0.014231976992652218,0.05428979320811988, +C7_group,0.3/sync,macro_f1,0.4816221864596062,0.4810139059799227,0.45158697949449433,0.5111143220890877,1000,paired source-video group resample,,,,,C0,-0.05847880297988162,-0.05775090608453154,-0.0953086278492621,-0.021289687623903028, +C7_group,0.3/sync,mae,0.7177635431289673,0.7167164981365204,0.6640314280986785,0.7696645364165307,1000,paired source-video group resample,0.0317116379737854,0.031256020069122314,0.014292730391025544,0.051820693910121916,C0,-0.035140156745910645,-0.03501024842262268,-0.07657383978366852,0.0031887888908386213, +C7_group,0.3/sync,rmse,0.9573691569537374,0.9543010087978056,0.8700483791568935,1.0442505207144717,1000,paired source-video group resample,,,,,C0,-0.004923558810539963,-0.0066834431875265055,-0.06129972071846617,0.04719944064293848, +C7_group,0.3/sync,pearson,0.5661795139312744,0.5677832663059235,0.4906572952866554,0.6323844596743584,1000,paired source-video group resample,,,,,C0,0.06794458627700806,0.06824645400047302,0.020695407688617707,0.11651158481836318, +C7_group,0.3/partial,accuracy,0.603021978021978,0.6025712344863039,0.5626527255639098,0.64592459924577,1000,paired source-video group resample,,,,,C0,0.008241758241758212,0.008547893253540273,-0.031418502136366405,0.04626729505361473, +C7_group,0.3/partial,macro_f1,0.47998237537414346,0.4790153479216104,0.4488000146674266,0.5137230779406255,1000,paired source-video group resample,,,,,C0,-0.08325327226932588,-0.08215069984094639,-0.12411700928817966,-0.045918239307025585, +C7_group,0.3/partial,mae,0.7138437032699585,0.7144801616668701,0.6593333855271339,0.7632610887289046,1000,paired source-video group resample,0.02779179811477661,0.0280190110206604,0.010899688303470613,0.04618170708417892,C0,-0.03270798921585083,-0.03244656324386597,-0.0764581874012947,0.005067117512226097, +C7_group,0.3/partial,rmse,0.9509089300331054,0.9496689815672592,0.8646191436283235,1.0363301818872406,1000,paired source-video group resample,,,,,C0,-0.0018892632308706858,-0.0013998155259672407,-0.060529708120096365,0.04879714289318567, +C7_group,0.3/partial,pearson,0.573399543762207,0.5752836167812347,0.5022111840546131,0.6391937345266342,1000,paired source-video group resample,,,,,C0,0.06468576192855835,0.0650576502084732,0.01784028857946396,0.1135256879031658, +C7_group,0.3/async,accuracy,0.6016483516483516,0.6017935923162941,0.5621325480154679,0.6423512913701656,1000,paired source-video group resample,,,,,C0,0.0219780219780219,0.022742485091882647,-0.013798015813171922,0.05671012402156299, +C7_group,0.3/async,macro_f1,0.48286727898702897,0.4817223181368106,0.45120059490002073,0.5142462002268223,1000,paired source-video group resample,,,,,C0,-0.06328319156164597,-0.06234551417279652,-0.09700303242821263,-0.031484309411540005, +C7_group,0.3/async,mae,0.7180367112159729,0.7182070016860962,0.6669908866286278,0.7686963617801666,1000,paired source-video group resample,0.031984806060791016,0.03217405080795288,0.009766502678394318,0.05403653383255005,C0,-0.05054670572280884,-0.05135536193847656,-0.0972189888358116,-0.007448063790798188, +C7_group,0.3/async,rmse,0.9444572741596972,0.9432099028452439,0.863106133289423,1.0216479098498616,1000,paired source-video group resample,,,,,C0,-0.03864752039623287,-0.039358775175661054,-0.09146778645620889,0.010581146922635686, +C7_group,0.3/async,pearson,0.5806990265846252,0.5815438032150269,0.5142472520470619,0.6402795448899269,1000,paired source-video group resample,,,,,C0,0.09385308623313904,0.09406563639640808,0.043500132858753204,0.14612659141421316, +C7_group,0.5/single,accuracy,0.6043956043956044,0.6046785225718194,0.5663899333399882,0.6445142893487109,1000,paired source-video group resample,,,,,C0,0.017857142857142794,0.01839888772467163,-0.01809627680331395,0.05184529219537054, +C7_group,0.5/single,macro_f1,0.5059109153432723,0.5048205184258692,0.47121112523886477,0.5397993435283696,1000,paired source-video group resample,,,,,C0,-0.04910636681861069,-0.049557496989864336,-0.08988228203040809,-0.009388886619115038, +C7_group,0.5/single,mae,0.7071334719657898,0.7058885991573334,0.6523032411932945,0.7625810816884041,1000,paired source-video group resample,0.02108156681060791,0.021070003509521484,0.007856132090091705,0.035209295153617856,C0,-0.04189485311508179,-0.041741132736206055,-0.08446573466062546,-0.0020165383815765403, +C7_group,0.5/single,rmse,0.9482637475624074,0.9450885243923428,0.8543069946149734,1.043949587387703,1000,paired source-video group resample,,,,,C0,-0.011387089950126161,-0.01271331761740463,-0.07495378617933682,0.04105355175957654, +C7_group,0.5/single,pearson,0.5768412351608276,0.579289436340332,0.49930155500769613,0.6462177187204361,1000,paired source-video group resample,,,,,C0,0.06860798597335815,0.0697365403175354,0.018930031359195708,0.12296758592128754, +C7_group,0.5/sync,accuracy,0.6016483516483516,0.6019592122034456,0.559832120204799,0.6455086338728176,1000,paired source-video group resample,,,,,C0,0.008241758241758212,0.00877222982216147,-0.029814665837812743,0.04532967032967028, +C7_group,0.5/sync,macro_f1,0.47004685552268155,0.47032265056721334,0.4386042616095749,0.5036338293399266,1000,paired source-video group resample,,,,,C0,-0.09345668387350192,-0.09337520471732047,-0.13447886101176557,-0.056499898750760384, +C7_group,0.5/sync,mae,0.7520185112953186,0.7519309818744659,0.6928148433566094,0.8041859239339828,1000,paired source-video group resample,0.06596660614013672,0.0655607283115387,0.03685808628797531,0.09711194932460784,C0,-0.03527575731277466,-0.035380005836486816,-0.08271855115890503,0.01239862442016601, +C7_group,0.5/sync,rmse,0.9922188881542421,0.9916224334217529,0.9012124595210816,1.081227444805345,1000,paired source-video group resample,,,,,C0,-0.010152650771946381,-0.010427334620798923,-0.08086587063842833,0.04924413341555223, +C7_group,0.5/sync,pearson,0.5440298914909363,0.5463204383850098,0.4655355863273144,0.6178763553500175,1000,paired source-video group resample,,,,,C0,0.06437161564826965,0.06642888486385345,0.01106880605220795,0.12240330129861832, +C7_group,0.5/partial,accuracy,0.5961538461538461,0.5965909090909091,0.5573144322198437,0.6410758933314445,1000,paired source-video group resample,,,,,C0,0.01098901098901095,0.011444921316165924,-0.02857609710550888,0.051063179985741586, +C7_group,0.5/partial,macro_f1,0.46481200148766727,0.46411517028737814,0.43489425505552326,0.4969926353254376,1000,paired source-video group resample,,,,,C0,-0.08678422925176382,-0.08580199772739505,-0.12736266412925318,-0.041790901809630125, +C7_group,0.5/partial,mae,0.7419087886810303,0.7413413524627686,0.6848594218492507,0.7939592704176902,1000,paired source-video group resample,0.05585688352584839,0.05517280101776123,0.02769041657447815,0.08575219064950942,C0,-0.043550312519073486,-0.04498600959777832,-0.08956382870674133,0.004074579477310165, +C7_group,0.5/partial,rmse,0.9808695304584909,0.9787028138630931,0.8929347235889388,1.0627253057287929,1000,paired source-video group resample,,,,,C0,-0.01874126487795791,-0.02297432544791822,-0.08257364586079306,0.0432259610387295, +C7_group,0.5/partial,pearson,0.5512108206748962,0.5529791116714478,0.4762364991009235,0.6202911004424095,1000,paired source-video group resample,,,,,C0,0.06980520486831665,0.07299093902111053,0.00906449556350708,0.12657228335738183, 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resample,0.048776984214782715,0.049059152603149414,0.030527539551258087,0.06745060086250305,C0,-0.0531197190284729,-0.0536763072013855,-0.09502255618572235,-0.012048342823982252, +C7_group,0.7/single,rmse,0.966793699933628,0.964734459374206,0.8903810367309036,1.0401501030821374,1000,paired source-video group resample,,,,,C0,-0.04353029549030052,-0.044077064290466095,-0.09892049777619516,0.006959458627602598, +C7_group,0.7/single,pearson,0.5657607913017273,0.5689146518707275,0.49802195802330973,0.6244936257600784,1000,paired source-video group resample,,,,,C0,0.09312057495117188,0.09518420696258545,0.04590837582945824,0.1394055664539337, +C7_group,0.7/sync,accuracy,0.5879120879120879,0.5871573378935045,0.545189050252945,0.6333018931653522,1000,paired source-video group resample,,,,,C0,0.005494505494505475,0.00621582262744752,-0.03344038760485132,0.04367692322677413, +C7_group,0.7/sync,macro_f1,0.4564096574254754,0.45522158808853275,0.4238437601818207,0.48805998900702413,1000,paired source-video group resample,,,,,C0,-0.09252984267488867,-0.09176855803608158,-0.13070572742981793,-0.0516232420391475, +C7_group,0.7/sync,mae,0.8039528727531433,0.8046007454395294,0.7443829879164696,0.8606285274028778,1000,paired source-video group resample,0.11790096759796143,0.11739319562911987,0.07925511449575424,0.1575057551264763,C0,0.02058124542236328,0.019414424896240234,-0.03301009386777878,0.0758665919303894, +C7_group,0.7/sync,rmse,1.0435931447657478,1.0445217879190998,0.949361275519446,1.1331523105484402,1000,paired source-video group resample,,,,,C0,0.02343770320845029,0.021788589260728464,-0.04792672851787537,0.09292243454756437, +C7_group,0.7/sync,pearson,0.5142754316329956,0.5150603950023651,0.4355708032846451,0.5912602826952934,1000,paired source-video group resample,,,,,C0,0.03583037853240967,0.03619791567325592,-0.0307204008102417,0.09921582490205764, +C7_group,0.7/partial,accuracy,0.5659340659340659,0.5663889657079646,0.5228766698299145,0.6085247988754084,1000,paired source-video group resample,,,,,C0,-0.027472527472527486,-0.027160450687601367,-0.07196338730816389,0.011990960281840317, +C7_group,0.7/partial,macro_f1,0.4234608837213146,0.4237064292040325,0.39384129230035264,0.452017486530949,1000,paired source-video group resample,,,,,C0,-0.14055255349529588,-0.13979987856568457,-0.18344215784332527,-0.10161032790717602, +C7_group,0.7/partial,mae,0.8193768262863159,0.8193906545639038,0.759796553850174,0.8788376525044441,1000,paired source-video group resample,0.13332492113113403,0.13347500562667847,0.09413699805736542,0.1753141090273857,C0,0.021785497665405273,0.02182254195213318,-0.031166325509548187,0.07596058696508408, +C7_group,0.7/partial,rmse,1.0717310728195293,1.0711497032588193,0.9800146690157256,1.1613304303785814,1000,paired source-video group resample,,,,,C0,0.054274381052613396,0.053048580547842894,-0.017348824101403898,0.12112801500008892, +C7_group,0.7/partial,pearson,0.4812347888946533,0.4828123152256012,0.3936352275311947,0.5623029381036758,1000,paired source-video group resample,,,,,C0,-0.011242032051086426,-0.00954844057559967,-0.07898450791835784,0.05625333338975906, +C7_group,0.7/async,accuracy,0.5879120879120879,0.588034148507159,0.547573734258626,0.6302797102675404,1000,paired source-video group resample,,,,,C0,0.009615384615384581,0.010589055639845968,-0.0339296045970361,0.05057652518750538, +C7_group,0.7/async,macro_f1,0.4536387142978671,0.4535221542737615,0.4230957968049892,0.48372689053048784,1000,paired source-video group resample,,,,,C0,-0.10015934871003668,-0.09905847812609875,-0.1433916731002128,-0.05928829262671808, +C7_group,0.7/async,mae,0.8060576319694519,0.8061514794826508,0.750188672542572,0.8615006133913994,1000,paired source-video group resample,0.12000572681427002,0.11886698007583618,0.0839049831032753,0.160108482837677,C0,-0.01040196418762207,-0.010959148406982422,-0.06384879499673843,0.040199828147888174, +C7_group,0.7/async,rmse,1.051301338221365,1.0484573012096496,0.9656442783968624,1.1397373116625125,1000,paired source-video group resample,,,,,C0,0.010506459447010785,0.010389698251437818,-0.05855420233041195,0.07499585258700953, +C7_group,0.7/async,pearson,0.5125513672828674,0.5130863785743713,0.43655402585864067,0.5781601086258888,1000,paired source-video group resample,,,,,C0,0.03335520625114441,0.033406466245651245,-0.022792015224695206,0.093896596878767, +C7_group,0.3/modality_T,accuracy,0.5892857142857143,0.5893434727503168,0.5504421317446212,0.6316625589881737,1000,paired source-video group resample,,,,,C0,0.0027472527472527375,0.002789400278940035,-0.03222154286580971,0.03734748088820267, +C7_group,0.3/modality_T,macro_f1,0.46066025455894294,0.4600113899361167,0.43033917421076945,0.49043722353363733,1000,paired source-video group resample,,,,,C0,-0.08610305888476383,-0.08539080933283752,-0.12265175629753775,-0.04758255885791414, +C7_group,0.3/modality_T,mae,0.7292237877845764,0.7282831966876984,0.6755094662308693,0.7796218737959861,1000,paired source-video group resample,0.04317188262939453,0.043055564165115356,0.025857359170913696,0.061185854673385616,C0,-0.020899951457977295,-0.021260827779769897,-0.06387106031179428,0.02153597772121427, +C7_group,0.3/modality_T,rmse,0.9676148316401383,0.9651067734316205,0.8777614640067795,1.058743534154567,1000,paired source-video group resample,,,,,C0,0.004945499986017676,0.003996237757376064,-0.05336403147492346,0.05813220228633293, +C7_group,0.3/modality_T,pearson,0.5572686791419983,0.5594981014728546,0.4779651552438736,0.6257893815636635,1000,paired source-video group resample,,,,,C0,0.05550628900527954,0.0570492297410965,0.003790242969989777,0.10591353774070739, +C7_group,0.3/modality_A,accuracy,0.6057692307692307,0.6058823529411764,0.5667896771825115,0.6463100975953466,1000,paired source-video group resample,,,,,C0,0.019230769230769162,0.019959138920083774,-0.01776508967643921,0.05193119131201692, +C7_group,0.3/modality_A,macro_f1,0.5073677008935622,0.5062297969685512,0.47253556053673484,0.5393387496973532,1000,paired source-video group resample,,,,,C0,-0.044114067766335086,-0.0429513620618652,-0.08383140170346581,-0.006870069688872819, +C7_group,0.3/modality_A,mae,0.6910558342933655,0.6899496912956238,0.6384876042604446,0.7447717800736428,1000,paired source-video group resample,0.005003929138183594,0.0046791136264801025,0.00035733580589294436,0.01188187450170517,C0,-0.039111196994781494,-0.04018726944923401,-0.07657862305641175,-0.0019119247794151307, +C7_group,0.3/modality_A,rmse,0.9309747583591642,0.9287529414845044,0.8420446705286735,1.021056159394493,1000,paired source-video group resample,,,,,C0,-0.003337601956915681,-0.0043476623074239495,-0.0573164227478214,0.046676991878440786, +C7_group,0.3/modality_A,pearson,0.5880905985832214,0.5909413397312164,0.5111345633864403,0.6549915328621864,1000,paired source-video group resample,,,,,C0,0.06535357236862183,0.06677067279815674,0.020453604310750963,0.11167013198137284, +C7_group,0.3/modality_V,accuracy,0.6016483516483516,0.6014909212060636,0.5625686083950466,0.6423460745528501,1000,paired source-video group resample,,,,,C0,0.013736263736263687,0.01433323248056717,-0.022736013986013968,0.04645977796670981, +C7_group,0.3/modality_V,macro_f1,0.5042605037712021,0.5039001310177891,0.46886307303623304,0.536246825104109,1000,paired source-video group resample,,,,,C0,-0.04683284221164663,-0.045941858044219935,-0.08689869828435491,-0.007470620676598002, +C7_group,0.3/modality_V,mae,0.6932002305984497,0.6924245655536652,0.6404030665755271,0.7482657566666603,1000,paired source-video group resample,0.007148325443267822,0.00687563419342041,0.0004152879118919375,0.015437993407249448,C0,-0.040132880210876465,-0.040841490030288696,-0.07836406379938125,-0.003349767625331892, +C7_group,0.3/modality_V,rmse,0.9339126616818396,0.9320180001501639,0.844016065765724,1.0249541590077424,1000,paired source-video group resample,,,,,C0,-0.0038800706307867694,-0.00536721994146494,-0.0585365609402429,0.048184775536719224, +C7_group,0.3/modality_V,pearson,0.5855700373649597,0.588498443365097,0.5098373278975487,0.6539814904332161,1000,paired source-video group resample,,,,,C0,0.06612420082092285,0.06721392273902893,0.021739719808101656,0.11098119094967841, +C7_group,0.3/modality_TA,accuracy,0.5906593406593407,0.59120448354025,0.5511593999364975,0.6333130919804453,1000,paired source-video group resample,,,,,C0,0.004120879120879106,0.004451665741988298,-0.03081448871683505,0.04210670136629797, +C7_group,0.3/modality_TA,macro_f1,0.46317457221395236,0.4630552042539716,0.4339678834858907,0.49206199892275965,1000,paired source-video group resample,,,,,C0,-0.09102371494634048,-0.09035504992793197,-0.12595569834543818,-0.0551292419010805, +C7_group,0.3/modality_TA,mae,0.7336435914039612,0.7332816421985626,0.6785556629300118,0.7896636739373207,1000,paired source-video group resample,0.0475916862487793,0.04723703861236572,0.026482421159744262,0.07328382730484008,C0,-0.041941940784454346,-0.041837722063064575,-0.08258803188800812,-0.001128076016902925, +C7_group,0.3/modality_TA,rmse,0.9797297576600326,0.9772623971448311,0.8876842972277956,1.0728776946761909,1000,paired source-video group resample,,,,,C0,0.009108671306595761,0.0075845213540833845,-0.054254439993119644,0.06569069732162246, +C7_group,0.3/modality_TA,pearson,0.5473980903625488,0.5486486256122589,0.4695810295641422,0.6186028108000755,1000,paired source-video group resample,,,,,C0,0.04895812273025513,0.049222514033317566,-0.005497568845748901,0.10490406304597855, +C7_group,0.3/modality_TV,accuracy,0.5906593406593407,0.590429156662784,0.549719730038819,0.6328395910492116,1000,paired source-video group resample,,,,,C0,0.008241758241758212,0.008602154958006702,-0.03097509345180508,0.04573203082989781, +C7_group,0.3/modality_TV,macro_f1,0.46563316006625427,0.46514670793268104,0.43509215089259135,0.4974954219082138,1000,paired source-video group resample,,,,,C0,-0.079211427922604,-0.07851454052434159,-0.11919121190806538,-0.04093159940385588, +C7_group,0.3/modality_TV,mae,0.726919412612915,0.7261656224727631,0.6727929949760437,0.7789764523506164,1000,paired source-video group resample,0.040867507457733154,0.04069584608078003,0.018878936767578125,0.0642868623137474,C0,-0.03375434875488281,-0.03427055478096008,-0.07504022121429443,0.008166038990020752, +C7_group,0.3/modality_TV,rmse,0.9626812504124249,0.9601822952694966,0.8783041143323448,1.05140160043637,1000,paired source-video group resample,,,,,C0,-0.004885840393463958,-0.006166470173130989,-0.061254476452822004,0.04655568345338331, +C7_group,0.3/modality_TV,pearson,0.5615667700767517,0.5636012852191925,0.48310779184103014,0.6317740187048911,1000,paired source-video group resample,,,,,C0,0.06257995963096619,0.0644153356552124,0.01632179543375969,0.11162173748016357, +C7_group,0.3/modality_AV,accuracy,0.603021978021978,0.6027591456162885,0.5642820197044335,0.6438384742888715,1000,paired source-video group resample,,,,,C0,0.008241758241758212,0.008869223205506371,-0.026293547578601483,0.04194184355059336, 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resample,,,,,C0,0.07980585098266602,0.08148002624511719,0.03474466428160668,0.12580302506685256, +C7_group,0.3/modality_TAV,accuracy,0.5961538461538461,0.5965902211028504,0.5558770711617661,0.6385346214853307,1000,paired source-video group resample,,,,,C0,0.015109890109890056,0.015723429915324993,-0.01931302310010043,0.05068631382204883, +C7_group,0.3/modality_TAV,macro_f1,0.46873768874017346,0.4682075488518098,0.4374233772119188,0.5022378075074532,1000,paired source-video group resample,,,,,C0,-0.07574020986410873,-0.07432299935323128,-0.11299533842338498,-0.03668875184932924, +C7_group,0.3/modality_TAV,mae,0.7291298508644104,0.7284508943557739,0.6730370745062828,0.7797390848398209,1000,paired source-video group resample,0.043077945709228516,0.043251633644104004,0.02186216413974762,0.06418509036302567,C0,-0.04180186986923218,-0.04180136322975159,-0.08636517226696014,-0.0023385971784591684, +C7_group,0.3/modality_TAV,rmse,0.9704205045928558,0.9687631974264804,0.8816116821511114,1.0540610890359918,1000,paired source-video group resample,,,,,C0,-0.009617257068513352,-0.010563648477918297,-0.06997317123649333,0.043841983795165185, +C7_group,0.3/modality_TAV,pearson,0.5579834580421448,0.5597214996814728,0.4815408937633038,0.6282888576388359,1000,paired source-video group resample,,,,,C0,0.0676739513874054,0.07014256715774536,0.016293787211179734,0.12119294106960295, +C7_group,0.3/location_start_T,accuracy,0.5961538461538461,0.5969945355191257,0.5554087396892242,0.6404187182550087,1000,paired source-video group resample,,,,,C0,0.004120879120879106,0.005376431501986301,-0.03269978112297319,0.043665654455537585, +C7_group,0.3/location_start_T,macro_f1,0.47262698070360143,0.47251546601157157,0.4429835924013925,0.5033600501998062,1000,paired source-video group resample,,,,,C0,-0.08856419286472139,-0.08766401344133778,-0.1221130562233436,-0.050102834357125765, +C7_group,0.3/location_start_T,mae,0.7224045395851135,0.7222899794578552,0.6718727767467498,0.7701337039470673,1000,paired source-video group resample,0.03635263442993164,0.03613665699958801,0.013279877603054047,0.06090753972530365,C0,-0.04685664176940918,-0.04688364267349243,-0.08917828500270844,-0.0033470422029495293, +C7_group,0.3/location_start_T,rmse,0.9631772494887949,0.9624951151932025,0.8831272626911627,1.0396204116642147,1000,paired source-video group resample,,,,,C0,-0.012136680123265187,-0.013683773619329653,-0.07229353977274094,0.04586729645068204, +C7_group,0.3/location_start_T,pearson,0.556897759437561,0.558743417263031,0.48377165496349334,0.6191786393523216,1000,paired source-video group resample,,,,,C0,0.07434830069541931,0.07555115222930908,0.01728082224726677,0.131556086987257, +C7_group,0.3/location_middle_T,accuracy,0.5975274725274725,0.5973322662398293,0.5564286445769424,0.6385915992056274,1000,paired source-video group resample,,,,,C0,0.008241758241758212,0.008236105458327647,-0.02727338035527697,0.044994973708629794, +C7_group,0.3/location_middle_T,macro_f1,0.4751968524789027,0.4741112506061816,0.4433658683352644,0.5046379535602776,1000,paired source-video group resample,,,,,C0,-0.07560465120741416,-0.0755642237204823,-0.11529131112138272,-0.03883480855557657, +C7_group,0.3/location_middle_T,mae,0.7193560600280762,0.7192937135696411,0.661778561770916,0.7750683888792992,1000,paired source-video group resample,0.03330415487289429,0.033409565687179565,0.015634021162986754,0.053634367883205414,C0,-0.02941131591796875,-0.029114216566085815,-0.07120628356933593,0.009299091994762414, +C7_group,0.3/location_middle_T,rmse,0.9584024065805034,0.957599548779662,0.8704139012751794,1.0480951412395183,1000,paired source-video group resample,,,,,C0,-0.003054868170311864,-0.00271359483263639,-0.05969099070162674,0.04846729330998784, +C7_group,0.3/location_middle_T,pearson,0.5655500888824463,0.5666459202766418,0.48999896347522737,0.6324332222342491,1000,paired source-video group resample,,,,,C0,0.05859577655792236,0.05925174057483673,0.008410555869340896,0.10845646336674689, +C7_group,0.3/location_end_T,accuracy,0.6016483516483516,0.6021042270335657,0.5628062185929649,0.6429720513632484,1000,paired source-video group resample,,,,,C0,0.027472527472527486,0.028263795423956906,-0.009955407041728821,0.06413204028610613, +C7_group,0.3/location_end_T,macro_f1,0.4666669027543165,0.46603716230772196,0.4390060685288203,0.4943261786373241,1000,paired source-video group resample,,,,,C0,-0.07130127117557655,-0.07098309177850917,-0.10968703296538501,-0.035606352430585644, +C7_group,0.3/location_end_T,mae,0.7316970229148865,0.7325846552848816,0.6833887442946434,0.7789612531661987,1000,paired source-video group resample,0.04564511775970459,0.04642370343208313,0.018900859355926513,0.0708037793636322,C0,-0.037455856800079346,-0.03733012080192566,-0.07947451323270797,0.0018030047416686956, +C7_group,0.3/location_end_T,rmse,0.9480264970359934,0.9467671312414018,0.8772320078327416,1.0137446554621827,1000,paired source-video group resample,,,,,C0,-0.02950607169204733,-0.03127199947533493,-0.07768349425802835,0.016438934001400184, +C7_group,0.3/location_end_T,pearson,0.5912908315658569,0.5918858349323273,0.5263505771756172,0.6428087785840034,1000,paired source-video group resample,,,,,C0,0.08460623025894165,0.0857420265674591,0.0386107936501503,0.1274881273508072, +C7_group,0.3/span_long_T,accuracy,0.6002747252747253,0.6008174766256258,0.5607731773213722,0.6428619174942705,1000,paired source-video group resample,,,,,C0,0.0219780219780219,0.02241914233499087,-0.015178797697925194,0.05648559458218544, +C7_group,0.3/span_long_T,macro_f1,0.4755757240008096,0.4745496073219051,0.4427027597667749,0.5065173524180118,1000,paired source-video group resample,,,,,C0,-0.06452875106919154,-0.06415132202475063,-0.10610795766826425,-0.026365841445787675, +C7_group,0.3/span_long_T,mae,0.7145537734031677,0.7145043611526489,0.6603974938392639,0.7671259507536888,1000,paired source-video group resample,0.02850186824798584,0.02813151478767395,0.004441951215267182,0.05590957999229431,C0,-0.03456777334213257,-0.034973204135894775,-0.07574861347675324,0.006727883219718918, +C7_group,0.3/span_long_T,rmse,0.9429056407223688,0.9412117436164881,0.8574635418275296,1.0274286088450502,1000,paired source-video group resample,,,,,C0,-0.02099228030250133,-0.02243845286318691,-0.07499820161731346,0.028962587615615622, +C7_group,0.3/span_long_T,pearson,0.5793851613998413,0.5797049403190613,0.5037647068500519,0.6455590516328812,1000,paired source-video group resample,,,,,C0,0.07940605282783508,0.08108420670032501,0.03395476192235947,0.12526206150650976, +C7_group,0.3/span_multi_short_T,accuracy,0.603021978021978,0.6036697688870476,0.5624893417462483,0.6465065350389321,1000,paired source-video group resample,,,,,C0,0.015109890109890056,0.015635185788787476,-0.01906846940263442,0.048532293377121, +C7_group,0.3/span_multi_short_T,macro_f1,0.4891074372355046,0.4885601410728204,0.4552566051817674,0.5242050024633489,1000,paired source-video group resample,,,,,C0,-0.062437018051113735,-0.061197568202733255,-0.09988956713339382,-0.025232982786495047, +C7_group,0.3/span_multi_short_T,mae,0.7114484310150146,0.7095970511436462,0.6585747987031937,0.7637076959013939,1000,paired source-video group resample,0.025396525859832764,0.025131016969680786,0.010550369322299958,0.04240324646234512,C0,-0.04000711441040039,-0.040573954582214355,-0.07968470305204392,0.001816718280315393, +C7_group,0.3/span_multi_short_T,rmse,0.9468978325133636,0.9437488356264936,0.8613468351960237,1.0341650193495087,1000,paired source-video group resample,,,,,C0,-0.013800273167017929,-0.01581830978162857,-0.07094616859741316,0.0405856531508613, +C7_group,0.3/span_multi_short_T,pearson,0.5756534934043884,0.5770930349826813,0.4986491225659847,0.6436078429222107,1000,paired source-video group resample,,,,,C0,0.07404494285583496,0.07451304793357849,0.02321499288082123,0.124639243632555, +C7_group,0.3/location_start_A,accuracy,0.6043956043956044,0.6045197740112994,0.5658020762689759,0.6445825142322618,1000,paired source-video group resample,,,,,C0,0.02060439560439553,0.020397751700390487,-0.015069528074665054,0.05593802195560434, +C7_group,0.3/location_start_A,macro_f1,0.5083245857893746,0.5075971872268353,0.4712909963182215,0.5434651800243028,1000,paired source-video group resample,,,,,C0,-0.04845557460785266,-0.04784674418370988,-0.08741818188549413,-0.008033340727148869, +C7_group,0.3/location_start_A,mae,0.6949326395988464,0.6935119032859802,0.6415462285280228,0.7502418980002403,1000,paired source-video group resample,0.00888073444366455,0.00861242413520813,0.0031053304672241213,0.016396258771419522,C0,-0.0400657057762146,-0.040070801973342896,-0.07955849319696426,-0.0009965687990188604, +C7_group,0.3/location_start_A,rmse,0.9365760064511505,0.9339186126848742,0.8467727987088715,1.0259080219905532,1000,paired source-video group resample,,,,,C0,-0.0042213412435171405,-0.005959079537395995,-0.058846739821863836,0.04624117846264511, +C7_group,0.3/location_start_A,pearson,0.5869316458702087,0.5899096727371216,0.5112563237547875,0.6549770668148994,1000,paired source-video group resample,,,,,C0,0.06918799877166748,0.07017868757247925,0.02557338625192642,0.11577562764286993, +C7_group,0.3/location_middle_A,accuracy,0.603021978021978,0.6027877610490529,0.5647012573513184,0.6438076001560149,1000,paired source-video group resample,,,,,C0,0.016483516483516425,0.017322933097372317,-0.018798338127197185,0.04987189653578365, +C7_group,0.3/location_middle_A,macro_f1,0.5057193445940249,0.5047041752567877,0.47101476900233147,0.5394634667792424,1000,paired source-video group resample,,,,,C0,-0.04804347873401582,-0.0470698427163429,-0.08736180727061606,-0.011950374005455715, +C7_group,0.3/location_middle_A,mae,0.6911180019378662,0.690529853105545,0.6387819975614548,0.7443797573447227,1000,paired source-video group resample,0.005066096782684326,0.004743456840515137,0.0012642189860343934,0.01084505170583725,C0,-0.04290527105331421,-0.04346945881843567,-0.079578797519207,-0.005292391777038595, +C7_group,0.3/location_middle_A,rmse,0.9319875139333276,0.9300559903180319,0.8385600857677044,1.0232034862383683,1000,paired source-video group resample,,,,,C0,-0.00479142172031044,-0.006495524296335875,-0.05925017733911012,0.04757395238206395, +C7_group,0.3/location_middle_A,pearson,0.586514949798584,0.5898366868495941,0.509792722761631,0.6544850900769233,1000,paired source-video group resample,,,,,C0,0.06615370512008667,0.06728065013885498,0.019641071557998657,0.1123711958527565, +C7_group,0.3/location_end_A,accuracy,0.6057692307692307,0.605789179699968,0.5661427130909307,0.6467339172572135,1000,paired source-video group resample,,,,,C0,0.016483516483516425,0.017608226646168956,-0.018309421329507348,0.04823318795308536, +C7_group,0.3/location_end_A,macro_f1,0.5077628257349466,0.5070184092113246,0.4721906571167216,0.541269492379204,1000,paired source-video group resample,,,,,C0,-0.04563633553011215,-0.04471484269847151,-0.08362928122131594,-0.008408440203816286, +C7_group,0.3/location_end_A,mae,0.6869874000549316,0.685932993888855,0.63434067517519,0.7396346464753151,1000,paired source-video group resample,0.0009354948997497559,0.0008226335048675537,-0.00027511864900588986,0.002726134657859802,C0,-0.0477595329284668,-0.0482867956161499,-0.08620034456253052,-0.010855448246002226, +C7_group,0.3/location_end_A,rmse,0.9255946812374676,0.9229684854608333,0.8334361066407099,1.0150791655599896,1000,paired source-video group resample,,,,,C0,-0.012074739590924866,-0.013526033870595311,-0.06678472937049604,0.03901859946327399, +C7_group,0.3/location_end_A,pearson,0.591266930103302,0.5941897034645081,0.5146970078349113,0.6579983353614807,1000,paired source-video group resample,,,,,C0,0.07231557369232178,0.07329747080802917,0.027654385566711424,0.11946969851851462, +C7_group,0.3/span_long_A,accuracy,0.6085164835164835,0.6081663527740899,0.5698865406006675,0.6485795095671558,1000,paired source-video group resample,,,,,C0,0.02060439560439553,0.02128081128291387,-0.014957164931189905,0.05357985175202148, +C7_group,0.3/span_long_A,macro_f1,0.513416477702192,0.5128149269074056,0.47650842451395575,0.5469207142558546,1000,paired source-video group resample,,,,,C0,-0.04092080295087808,-0.04034315266942812,-0.08315185172448572,-0.00133366021043481, +C7_group,0.3/span_long_A,mae,0.690218448638916,0.6893383264541626,0.6376586422324181,0.7439599201083184,1000,paired source-video group resample,0.004166543483734131,0.004045635461807251,-0.00048741698265075684,0.010816051065921782,C0,-0.04644042253494263,-0.04666554927825928,-0.08369404822587967,-0.009376561641693138, +C7_group,0.3/span_long_A,rmse,0.9312123847891612,0.9290237397223662,0.842280247381335,1.0213596902366051,1000,paired source-video group resample,,,,,C0,-0.006740691764201334,-0.007727922311331403,-0.061041084422065246,0.0437681200259907, +C7_group,0.3/span_long_A,pearson,0.5882331132888794,0.5910170376300812,0.5114483550190926,0.6553556501865386,1000,paired source-video group resample,,,,,C0,0.07070320844650269,0.07261614501476288,0.02589186280965805,0.1180204652249813, +C7_group,0.3/span_multi_short_A,accuracy,0.6085164835164835,0.6081663527740899,0.5698865406006675,0.6485795095671558,1000,paired source-video group resample,,,,,C0,0.013736263736263687,0.014511898608159657,-0.021220287369914895,0.045841901154401093, +C7_group,0.3/span_multi_short_A,macro_f1,0.513416477702192,0.5128149269074056,0.47650842451395575,0.5469207142558546,1000,paired source-video group resample,,,,,C0,-0.046861357881816335,-0.04515455362148718,-0.08818853294465256,-0.007720800743397034, +C7_group,0.3/span_multi_short_A,mae,0.6897726655006409,0.6886664927005768,0.6370287507772445,0.7436355963349343,1000,paired source-video group resample,0.0037207603454589844,0.0035425126552581787,-0.0007709845900535584,0.010517084598541258,C0,-0.04635137319564819,-0.04727157950401306,-0.08529599756002426,-0.009116782248020172, +C7_group,0.3/span_multi_short_A,rmse,0.9304584544242402,0.9280176151949011,0.8412666811309628,1.0204655569359047,1000,paired source-video group resample,,,,,C0,-0.011187695221057892,-0.012460271180631144,-0.06531469716043009,0.03850238935919029, +C7_group,0.3/span_multi_short_A,pearson,0.5885758399963379,0.5913993418216705,0.5118785113096237,0.6556807458400725,1000,paired source-video group resample,,,,,C0,0.07227545976638794,0.07394620776176453,0.02792378291487694,0.11810202822089196, +C7_group,0.3/location_start_V,accuracy,0.6098901098901099,0.6093347336892572,0.5710057142239889,0.6505738185425685,1000,paired source-video group resample,,,,,C0,0.013736263736263798,0.014054876242024339,-0.023553973824270904,0.04782111554246759, +C7_group,0.3/location_start_V,macro_f1,0.5187012798980596,0.5174964554252738,0.47984887075564847,0.5527800238160573,1000,paired source-video group resample,,,,,C0,-0.045109393871900716,-0.04520712199433602,-0.0854779913330112,-0.0037023554845646966, +C7_group,0.3/location_start_V,mae,0.6823319792747498,0.6818513870239258,0.6292561709880828,0.7363006725907325,1000,paired source-video group resample,-0.003719925880432129,-0.0033937692642211914,-0.01443350464105606,0.0052869528532028184,C0,-0.051114439964294434,-0.050687938928604126,-0.09194203317165375,-0.012932048738002778, +C7_group,0.3/location_start_V,rmse,0.918480945298139,0.9166630317971287,0.8276545618562957,1.0106958753228585,1000,paired source-video group resample,,,,,C0,-0.018360374773071064,-0.020149459792562774,-0.07126362424243018,0.035215439214159504, +C7_group,0.3/location_start_V,pearson,0.5963819622993469,0.598353922367096,0.5210094019770622,0.664144916832447,1000,paired source-video group resample,,,,,C0,0.07534152269363403,0.07651364803314209,0.03019995763897896,0.12285140901803969, +C7_group,0.3/location_middle_V,accuracy,0.6057692307692307,0.6060194334650857,0.5689842483403587,0.6471570735090152,1000,paired source-video group resample,,,,,C0,0.013736263736263687,0.014579197920143339,-0.02103125786339369,0.04574752205403804, +C7_group,0.3/location_middle_V,macro_f1,0.5106059647561693,0.5094800055338836,0.47516523339809424,0.5434546445698406,1000,paired source-video group resample,,,,,C0,-0.04510301428024688,-0.04434782736068546,-0.08423736597626866,-0.008437225591865265, +C7_group,0.3/location_middle_V,mae,0.6863077282905579,0.6856467127799988,0.6330891966819763,0.741171646118164,1000,paired source-video group resample,0.00025582313537597656,0.00047722458839416504,-0.011251665651798248,0.01055476069450378,C0,-0.047502338886260986,-0.0483492910861969,-0.08763674795627593,-0.008321061730384837, +C7_group,0.3/location_middle_V,rmse,0.92303636103392,0.9219853444280242,0.8303119131053612,1.017721362362975,1000,paired source-video group resample,,,,,C0,-0.015844845274673003,-0.018218124370710242,-0.0718392137247464,0.03995936477558708, +C7_group,0.3/location_middle_V,pearson,0.5949817299842834,0.5965936779975891,0.5188797697424888,0.662843631207943,1000,paired source-video group resample,,,,,C0,0.075958251953125,0.07800674438476562,0.02888067066669464,0.12273337543010711, +C7_group,0.3/location_end_V,accuracy,0.603021978021978,0.6032074162977741,0.564256040049467,0.643468026966965,1000,paired source-video group resample,,,,,C0,0.013736263736263687,0.014705882352941124,-0.021100707176532254,0.0463483146067416, +C7_group,0.3/location_end_V,macro_f1,0.5057193445940249,0.504910855540647,0.4700638081625291,0.5378003520617832,1000,paired source-video group resample,,,,,C0,-0.04755705027664692,-0.046635130575995803,-0.08605103182496802,-0.011413217509615433, +C7_group,0.3/location_end_V,mae,0.6898821592330933,0.6891552805900574,0.6368652418255806,0.7440334171056747,1000,paired source-video group resample,0.003830254077911377,0.0033330321311950684,-0.00038148760795593263,0.010616298019886016,C0,-0.04333621263504028,-0.0440899133682251,-0.08210146725177765,-0.005598352849483495, +C7_group,0.3/location_end_V,rmse,0.9292504701897984,0.9268640390955489,0.8401160786933901,1.01803750257232,1000,paired source-video group resample,,,,,C0,-0.008194024321861781,-0.00954525427109626,-0.06192734440953445,0.04150690588439194, +C7_group,0.3/location_end_V,pearson,0.5878564119338989,0.5904313325881958,0.5117262721061706,0.654898963868618,1000,paired source-video group resample,,,,,C0,0.06870800256729126,0.07010430097579956,0.02507541626691818,0.11500400453805923, +C7_group,0.3/span_long_V,accuracy,0.6085164835164835,0.6082620320855615,0.5699352840214427,0.6495253824756607,1000,paired source-video group resample,,,,,C0,0.02335164835164827,0.024271283937925603,-0.011818901418320068,0.0545884061385663, +C7_group,0.3/span_long_V,macro_f1,0.5149962531743951,0.513712938117726,0.47712501496634263,0.5489692151645653,1000,paired source-video group resample,,,,,C0,-0.033617263593721525,-0.03326623587364694,-0.07499934418953431,0.003950498919590663, +C7_group,0.3/span_long_V,mae,0.6889601349830627,0.6882029175758362,0.6360716044902801,0.7430565327405929,1000,paired source-video group resample,0.0029082298278808594,0.0027546584606170654,-0.0026463568210601807,0.009671466052532194,C0,-0.045398175716400146,-0.04584428668022156,-0.08351956009864807,-0.00811291784048081, +C7_group,0.3/span_long_V,rmse,0.9301041382761019,0.9277487582924938,0.8409255841210532,1.0206465236506155,1000,paired source-video group resample,,,,,C0,-0.0077279994425319964,-0.008663198450277465,-0.06080744210101146,0.04140659331635294, +C7_group,0.3/span_long_V,pearson,0.5891196131706238,0.592041015625,0.5131404861807823,0.6559696748852729,1000,paired source-video group resample,,,,,C0,0.06923902034759521,0.07049581408500671,0.025566799938678744,0.11422253400087357, +C7_group,0.3/span_multi_short_V,accuracy,0.6071428571428571,0.6071666349629066,0.5671366995073892,0.6488622809680777,1000,paired source-video group resample,,,,,C0,0.019230769230769162,0.019649132483413934,-0.016099569304656752,0.049595373734826455, +C7_group,0.3/span_multi_short_V,macro_f1,0.5126163431119378,0.5113829708848834,0.47591144017926035,0.5463448270298319,1000,paired source-video group resample,,,,,C0,-0.03884297471897036,-0.03863319221271966,-0.07958347725431535,-0.0040804260638825545, +C7_group,0.3/span_multi_short_V,mae,0.6865583062171936,0.6860308349132538,0.6338073551654816,0.7400755748152733,1000,paired source-video group resample,0.0005064010620117188,0.0008484423160552979,-0.01043587625026703,0.00943379551172256,C0,-0.04704463481903076,-0.04769092798233032,-0.0874909982085228,-0.008551330864429486, +C7_group,0.3/span_multi_short_V,rmse,0.9224864419080372,0.920625887762243,0.8318357429931815,1.0142186614103157,1000,paired source-video group resample,,,,,C0,-0.015446394523866425,-0.017238558596106457,-0.06931443311172039,0.03901106286056806, +C7_group,0.3/span_multi_short_V,pearson,0.5963611006736755,0.5984741747379303,0.5210445567965507,0.6638940200209618,1000,paired source-video group resample,,,,,C0,0.07684510946273804,0.07845905423164368,0.031365607678890225,0.1237744741141796, +C7_group,0.3/synchrony_sync,accuracy,0.592032967032967,0.5918501258771225,0.5527607111446161,0.6364963503649635,1000,paired source-video group resample,,,,,C0,0.004120879120879106,0.004106778104679243,-0.03161413091164335,0.04048065198371421, +C7_group,0.3/synchrony_sync,macro_f1,0.4685336829264865,0.4679387332978472,0.4380630717830186,0.5001164246236789,1000,paired source-video group resample,,,,,C0,-0.08041854808727561,-0.08004060046994774,-0.1184606030873827,-0.04220680715380482, +C7_group,0.3/synchrony_sync,mae,0.725333571434021,0.725210577249527,0.6660918742418289,0.7813893914222717,1000,paired source-video group resample,0.03928166627883911,0.03935670852661133,0.023403826355934142,0.05534648001194,C0,-0.017607033252716064,-0.017640620470046997,-0.06260109841823577,0.02348676770925521, +C7_group,0.3/synchrony_sync,rmse,0.9638541702891106,0.9612273406770037,0.8683920542260918,1.0543128278072333,1000,paired source-video group resample,,,,,C0,0.0124609589372775,0.010760657398964035,-0.05119347920334558,0.0666490995757187, +C7_group,0.3/synchrony_sync,pearson,0.5632575750350952,0.566026121377945,0.4870730608701706,0.6372876569628716,1000,paired source-video group resample,,,,,C0,0.048333048820495605,0.04966150224208832,-0.003611412644386291,0.10477486252784729, +C7_group,0.3/synchrony_partial,accuracy,0.6016483516483516,0.6022575844182964,0.5596383599293266,0.6450808871971305,1000,paired source-video group resample,,,,,C0,0.009615384615384581,0.009873060648801224,-0.02450157598140667,0.046038756639779674, +C7_group,0.3/synchrony_partial,macro_f1,0.47805214573629956,0.47797666577377396,0.444947872783728,0.5106792125533456,1000,paired source-video group resample,,,,,C0,-0.0787967815400013,-0.0783418357640239,-0.11737687642539789,-0.03934741913146386, +C7_group,0.3/synchrony_partial,mae,0.7170849442481995,0.7157917022705078,0.6632735073566437,0.7696826204657554,1000,paired source-video group resample,0.031033039093017578,0.03098127245903015,0.013716180622577668,0.047965444624423974,C0,-0.03787010908126831,-0.038816243410110474,-0.07742033004760743,0.0031401425600051745, +C7_group,0.3/synchrony_partial,rmse,0.9463708485945721,0.9439078676801335,0.8568850387837252,1.0377907291297435,1000,paired source-video group resample,,,,,C0,-0.0073771505121197345,-0.009331080301995975,-0.06308611452203872,0.04692342558448613, +C7_group,0.3/synchrony_partial,pearson,0.5761823058128357,0.5785074830055237,0.5050644427537918,0.6459787786006927,1000,paired source-video group resample,,,,,C0,0.06843805313110352,0.07065100967884064,0.020321911573410036,0.11482193171977996, +C7_group,0.3/synchrony_async,accuracy,0.5975274725274725,0.5987083333333334,0.5575790891508564,0.6397083560346788,1000,paired source-video group resample,,,,,C0,0.0027472527472527375,0.002952031128133359,-0.031705691629505824,0.03776875216038712, +C7_group,0.3/synchrony_async,macro_f1,0.4684562423732539,0.46805606734324745,0.43830226332482053,0.499353231266051,1000,paired source-video group resample,,,,,C0,-0.08889350276253238,-0.08841309802994093,-0.12385036738835317,-0.0540712271355101, +C7_group,0.3/synchrony_async,mae,0.7251530885696411,0.7242251038551331,0.6690801605582237,0.7798114284873009,1000,paired source-video group resample,0.03910118341445923,0.038417309522628784,0.013453997671604156,0.06454516649246216,C0,-0.03206968307495117,-0.0311526358127594,-0.0788385033607483,0.01465134322643279, +C7_group,0.3/synchrony_async,rmse,0.9609705291282016,0.9588750217944743,0.8676080054886377,1.0558370001360478,1000,paired source-video group resample,,,,,C0,-0.006119855759354698,-0.007258652406674393,-0.06840664651101948,0.05229580025173998, +C7_group,0.3/synchrony_async,pearson,0.5695079565048218,0.5707384347915649,0.4914640188217163,0.6399292409420013,1000,paired source-video group resample,,,,,C0,0.07179072499275208,0.07291565835475922,0.016143745183944704,0.12624204456806182, +C0,MAE_rate_curve/single,AURC_MAE,0.7453589308840982,0.7446564405046148,0.6969916087386897,0.7962292057391175,1000,paired source-video group resample,,,,,,,,,,"[0.0, 0.033573082215659425, 0.10112225007737187, 0.16741076544018754, 0.23297094863937376]" +C0,MAE_rate_curve/sync,AURC_MAE,0.7647705734160003,0.7648819593037308,0.7153390746435726,0.8156598342768211,1000,paired source-video group resample,,,,,,,,,,"[0.0, 0.057485145950546455, 0.1839160913819273, 0.33038531757979195, 0.5056906444017303]" +C0,MAE_rate_curve/partial,AURC_MAE,0.7656618543442275,0.7649162362839388,0.7183335358681301,0.8161517081205042,1000,paired source-video group resample,,,,,,,,,,"[0.0, 0.05304705151915722, 0.14821818657736774, 0.23661207845883836, 0.3909052849857452]" +C0,MAE_rate_curve/async,AURC_MAE,0.7774590424930353,0.7768957737578126,0.7292928409925403,0.8259885935640745,1000,paired source-video group resample,,,,,,,,,,"[0.0, 0.05599840150124984, 0.1757341571118529, 0.31261571285017986, 0.4833601627210972]" +C1,MAE_rate_curve/single,AURC_MAE,0.695243378828104,0.6948812114858639,0.642774124441669,0.7450962653510277,1000,paired source-video group resample,,,,,C0,-0.05011555205599416,-0.05103176667718995,-0.08719601161191329,-0.01125741733418487,"[0.0, 0.033573082215659425, 0.10112225007737187, 0.16741076544018754, 0.23297094863937376]" +C1,MAE_rate_curve/sync,AURC_MAE,0.721752277081038,0.7216806642765553,0.6684463371103947,0.7737067871281762,1000,paired source-video group resample,,,,,C0,-0.04301829633496235,-0.04394933027202863,-0.08034404882229358,-0.007427778085490802,"[0.0, 0.057485145950546455, 0.1839160913819273, 0.33038531757979195, 0.5056906444017303]" +C1,MAE_rate_curve/partial,AURC_MAE,0.7197292896210654,0.7197746014726947,0.6711271955179811,0.7660743597322373,1000,paired source-video group resample,,,,,C0,-0.045932564723162095,-0.04698026269935429,-0.08229051792435531,-0.010232309930044474,"[0.0, 0.05304705151915722, 0.14821818657736774, 0.23661207845883836, 0.3909052849857452]" +C1,MAE_rate_curve/async,AURC_MAE,0.712679592667176,0.713065726385218,0.6593428180217015,0.7641808417255227,1000,paired source-video group resample,,,,,C0,-0.06477944982585937,-0.06579997568524881,-0.10155130296364798,-0.02737563440900534,"[0.0, 0.05599840150124984, 0.1757341571118529, 0.31261571285017986, 0.4833601627210972]" +C2,MAE_rate_curve/single,AURC_MAE,0.7238275263839922,0.7244260423541136,0.670794453336031,0.7742333858808916,1000,paired source-video group resample,,,,,C0,-0.021531404500106044,-0.020702895651532882,-0.058220958005113316,0.012705032594465355,"[0.0, 0.033573082215659425, 0.10112225007737187, 0.16741076544018754, 0.23297094863937376]" +C2,MAE_rate_curve/sync,AURC_MAE,0.7432642022706187,0.7417208279063694,0.6897636661158242,0.7959711168286566,1000,paired source-video group resample,,,,,C0,-0.021506371145381564,-0.022228618646347287,-0.05854129600265766,0.012053809193449628,"[0.0, 0.057485145950546455, 0.1839160913819273, 0.33038531757979195, 0.5056906444017303]" +C2,MAE_rate_curve/partial,AURC_MAE,0.74339676595525,0.7427149817400218,0.6915548080635051,0.7974200122264737,1000,paired source-video group resample,,,,,C0,-0.02226508838897756,-0.022423301455053557,-0.06080244026665085,0.013106271070073472,"[0.0, 0.05304705151915722, 0.14821818657736774, 0.23661207845883836, 0.3909052849857452]" +C2,MAE_rate_curve/async,AURC_MAE,0.7618199871485388,0.7612189554328166,0.7080780019422931,0.8156967171010984,1000,paired source-video group resample,,,,,C0,-0.0156390553444965,-0.015609522599685288,-0.05441699953068346,0.018589005151252426,"[0.0, 0.05599840150124984, 0.1757341571118529, 0.31261571285017986, 0.4833601627210972]" +C3,MAE_rate_curve/single,AURC_MAE,0.7256730161236258,0.7241067389670065,0.6735526298494073,0.7794375415774664,1000,paired source-video group resample,,,,,C0,-0.019685914760472434,-0.02006872213883193,-0.06147333810577135,0.019160550698638257,"[0.0, 0.033573082215659425, 0.10112225007737187, 0.16741076544018754, 0.23297094863937376]" +C3,MAE_rate_curve/sync,AURC_MAE,0.7403322090441699,0.7397981180740889,0.687350784588537,0.7922590435695701,1000,paired source-video group resample,,,,,C0,-0.024438364371830446,-0.024895216622351724,-0.0634580192814646,0.011452736864737325,"[0.0, 0.057485145950546455, 0.1839160913819273, 0.33038531757979195, 0.5056906444017303]" +C3,MAE_rate_curve/partial,AURC_MAE,0.7461467078450975,0.7451508689989603,0.6939248551405864,0.7984574466657383,1000,paired source-video group resample,,,,,C0,-0.01951514649913,-0.020026069851674988,-0.06171064071281062,0.0179561592961164,"[0.0, 0.05304705151915722, 0.14821818657736774, 0.23661207845883836, 0.3909052849857452]" +C3,MAE_rate_curve/async,AURC_MAE,0.7408972761899744,0.7392315458570606,0.6880400522334423,0.7937886976475179,1000,paired source-video group resample,,,,,C0,-0.03656176630306096,-0.037491154947853544,-0.07857194488141273,-0.0003534566962598459,"[0.0, 0.05599840150124984, 0.1757341571118529, 0.31261571285017986, 0.4833601627210972]" +C4,MAE_rate_curve/single,AURC_MAE,0.7057020665091085,0.7056414237064188,0.6558887780876792,0.7597195825172822,1000,paired source-video group 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group resample,,,,,C0,-0.09217712865477568,-0.09218424849497237,-0.12632949046126749,-0.05927197249311134,"[0.0, 0.057485145950546455, 0.1839160913819273, 0.33038531757979195, 0.5056906444017303]" +C6,MAE_rate_curve/partial,AURC_MAE,0.6812126663254973,0.6805087517448767,0.6303184667876347,0.7380527880360818,1000,paired source-video group resample,,,,,C0,-0.08444918801873025,-0.08436596187316853,-0.12119059159211265,-0.05132211491921165,"[0.0, 0.05304705151915722, 0.14821818657736774, 0.23661207845883836, 0.3909052849857452]" +C6,MAE_rate_curve/async,AURC_MAE,0.6698331927703445,0.6694495727027537,0.6207433703272102,0.7240382602030044,1000,paired source-video group resample,,,,,C0,-0.10762584972269085,-0.10697834982004628,-0.1426337633542014,-0.0723309840866653,"[0.0, 0.05599840150124984, 0.1757341571118529, 0.31261571285017986, 0.4833601627210972]" +C6_no_distance,MAE_rate_curve/single,AURC_MAE,0.6837486843019001,0.6839235127583141,0.6344665484471845,0.7386862973492913,1000,paired 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resample,,,,,C0,-0.05034587284597958,-0.050790320358380436,-0.08914810225418246,-0.012938152041745855,"[0.0, 0.033573082215659425, 0.10112225007737187, 0.16741076544018754, 0.23297094863937376]" +C6_pointmask,MAE_rate_curve/sync,AURC_MAE,0.7017936297059214,0.7016506653555764,0.6504668164317551,0.7528000496654599,1000,paired source-video group resample,,,,,C0,-0.06297694371007889,-0.06339205574972157,-0.0993055911367219,-0.027867266100222752,"[0.0, 0.057485145950546455, 0.1839160913819273, 0.33038531757979195, 0.5056906444017303]" +C6_pointmask,MAE_rate_curve/partial,AURC_MAE,0.7085819585620775,0.7085356889250016,0.6578709557695476,0.7590279192096571,1000,paired source-video group resample,,,,,C0,-0.05707989578215,-0.0574877356234787,-0.0956273111373051,-0.018861492573617446,"[0.0, 0.05304705151915722, 0.14821818657736774, 0.23661207845883836, 0.3909052849857452]" 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0.33038531757979195, 0.5056906444017303]" +C7_distill,MAE_rate_curve/partial,AURC_MAE,0.7101784247526396,0.7098540786230438,0.6657755920166913,0.7597121504780637,1000,paired source-video group resample,,,,,C0,-0.05548342959158792,-0.05573136971959852,-0.09153001161320592,-0.02233477535898931,"[0.0, 0.05304705151915722, 0.14821818657736774, 0.23661207845883836, 0.3909052849857452]" +C7_distill,MAE_rate_curve/async,AURC_MAE,0.7042659677475602,0.7044162465403558,0.659750335303317,0.7505412711649735,1000,paired source-video group resample,,,,,C0,-0.0731930747454751,-0.07332079165202143,-0.1053618440438528,-0.03831630715876946,"[0.0, 0.05599840150124984, 0.1757341571118529, 0.31261571285017986, 0.4833601627210972]" +C7_group,MAE_rate_curve/single,AURC_MAE,0.7042447845390949,0.7032374575614686,0.652376545172862,0.755512403173946,1000,paired source-video group resample,,,,,C0,-0.04111414634500332,-0.041638519054049916,-0.07862685316530389,-0.004906976422047477,"[0.0, 0.033573082215659425, 0.10112225007737187, 0.16741076544018754, 0.23297094863937376]" +C7_group,MAE_rate_curve/sync,AURC_MAE,0.7372792445231297,0.7369470009223068,0.6827687873548843,0.7862906535228722,1000,paired source-video group resample,,,,,C0,-0.027491328892870648,-0.02759361036746405,-0.06845335758057902,0.009991113262218054,"[0.0, 0.057485145950546455, 0.1839160913819273, 0.33038531757979195, 0.5056906444017303]" +C7_group,MAE_rate_curve/partial,AURC_MAE,0.7392068400094579,0.7389780260742822,0.6873068380874074,0.7884700589334414,1000,paired source-video group resample,,,,,C0,-0.0264550143347696,-0.02671536298947047,-0.06560423547984279,0.009946206242192744,"[0.0, 0.05304705151915722, 0.14821818657736774, 0.23661207845883836, 0.3909052849857452]" +C7_group,MAE_rate_curve/async,AURC_MAE,0.7329426321752713,0.7320690146334,0.6802782687611172,0.781687682500617,1000,paired source-video group resample,,,,,C0,-0.04451641031776399,-0.04427900490182446,-0.08330209965578822,-0.010522169199375086,"[0.0, 0.05599840150124984, 0.1757341571118529, 0.31261571285017986, 0.4833601627210972]" diff --git a/math/Q2/results/controlled_mask_audit.csv b/math/Q2/results/controlled_mask_audit.csv new file mode 100644 index 0000000..15e990b --- /dev/null +++ b/math/Q2/results/controlled_mask_audit.csv @@ -0,0 +1,30577 @@ +natural_missing_rate,natural_missing_rate_by_modality,realized_additional_rate,realized_additional_rate_by_modality,final_total_missing_rate,final_total_missing_rate_by_modality,synchronous_no_observation_rate,sample_id,video_id,scenario,requested_rate_per_selected_source,mask_pattern,mask_seed,selected_modalities,newly_hidden_intervals_step_half_open,original_observed_steps,newly_hidden_steps +0.32,"[0.0, 0.48, 0.48]",0.0,"[0.0, 0.0, 0.0]",0.32,"[0.0, 0.48, 0.48]",0.0,-UacrmKiTn4$_$7,-UacrmKiTn4,0.0/none,0.0,none,16831170248887602275,,"{""text"":[],""audio"":[],""vision"":[]}",102,0 +0.02666666666666669,"[0.0, 0.040000000000000036, 0.040000000000000036]",0.0,"[0.0, 0.0, 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0.6471428571428575]",0.2560989010989011,728,0.6085164835164835,0.4931643958459892,206,184,338,0.6456310679611651,0.07065217391304347,0.878698224852071,0.7309597730636597,0.956704375828628,0.5956684350967407,0.4979931508202552,0.8433454036712646,0.051943840397583256,0.9065934065934066,2.5953333377838135,2.7676987648010254,0.6341922879219055,0.633617103099823,0.0005751746357418597,0.22358527779579163,0.6864131689071655 +valid,C3,0.3,location_start_T,0.10069156293222682,0.10069156293222682,"[0.30000000000000354, 0.0, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4615567765567765,"[0.30000000000000354, 0.5295054945054959, 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0.5551648351648366]",0.26755494505494504,728,0.6071428571428571,0.4898199937576475,206,184,338,0.6893203883495146,0.05434782608695652,0.8579881656804734,0.7465690970420837,0.9823456994436758,0.5887442231178284,0.49736542135472556,0.8426723480224609,0.030446744636519918,0.9217032967032966,2.7006688117980957,2.7703518867492676,0.6885926127433777,0.6878616213798523,0.0007310720975510776,0.2258036881685257,0.7429347634315491 +valid,C3,0.3,span_long_T,0.10069156293222682,0.10069156293222682,"[0.30000000000000354, 0.0, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4615567765567765,"[0.30000000000000354, 0.5295054945054959, 0.5551648351648366]",0.16035714285714286,728,0.6098901098901099,0.4872728855753121,206,184,338,0.6844660194174758,0.04891304347826087,0.8698224852071006,0.7339414954185486,0.9738111571766707,0.5825886130332947,0.49926201650230256,0.8460326790809631,0.042617339149608705,0.9148351648351648,2.6047940254211426,2.7755062580108643,0.6404427289962769,0.6399236917495728,0.0005190519732423127,0.22051651775836945,0.6927974224090576 +valid,C3,0.3,span_multi_short_T,0.10069156293222682,0.10069156293222682,"[0.30000000000000354, 0.0, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4615567765567765,"[0.30000000000000354, 0.5295054945054959, 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0.5551648351648366]",0.0,728,0.614010989010989,0.5083291589190543,206,184,338,0.6601941747572816,0.09239130434782608,0.8698224852071006,0.7089516520500183,0.943282888403786,0.6015817523002625,0.49609680576102116,0.8412100076675415,0.036307701861465355,0.9052197802197802,2.489898681640625,2.770949363708496,0.5925698280334473,0.592565655708313,4.181569693173515e-06,0.21606193482875824,0.6446264982223511 +valid,C3,0.3,location_start_V,0.19317645467012823,0.19317645467012823,"[0.0, 0.0, 0.5876574055813588]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.43891941391941397,"[0.0, 0.5295054945054959, 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0.6816208791208818]",0.0,728,0.6098901098901099,0.4989284858669034,206,184,338,0.6601941747572816,0.07608695652173914,0.8698224852071006,0.7164756655693054,0.9516112705003446,0.5965531468391418,0.4966368595820537,0.8416152596473694,0.034418416711000294,0.9010989010989011,2.4946789741516113,2.7735626697540283,0.5946013927459717,0.5945976972579956,3.6990622902521864e-06,0.22588025033473969,0.6470868587493896 +valid,C3,0.3,location_end_V,0.012031832650855376,0.012031832650855376,"[0.0, 0.0, 0.03660174617069467]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.37173992673992673,"[0.0, 0.5295054945054959, 0.5857142857142853]",0.0,728,0.6085164835164835,0.49763920375337345,206,184,338,0.6553398058252428,0.07608695652173914,0.8698224852071006,0.7166463732719421,0.9509495782852943,0.5967321395874023,0.49606524062974994,0.8410057425498962,0.03899642796470569,0.9065934065934066,2.498540163040161,2.7707815170288086,0.5956001877784729,0.5955966711044312,3.4962588415510254e-06,0.22162963449954987,0.6480824947357178 +valid,C3,0.3,span_long_V,0.09768688768578579,0.09768688768578579,"[0.0, 0.0, 0.29717091078607255]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4059615384615385,"[0.0, 0.5295054945054959, 0.6883791208791201]",0.0,728,0.6098901098901099,0.4989284858669034,206,184,338,0.6601941747572816,0.07608695652173914,0.8698224852071006,0.7174816131591797,0.9524375124581569,0.5971121788024902,0.4963150576952344,0.8411803841590881,0.03564221072164211,0.9065934065934066,2.50453782081604,2.7715840339660645,0.598629355430603,0.598625659942627,3.696888143167598e-06,0.22440427541732788,0.6514500379562378 +valid,C3,0.3,span_multi_short_V,0.09768688768578579,0.09768688768578579,"[0.0, 0.0, 0.29717091078607255]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4059615384615385,"[0.0, 0.5295054945054959, 0.6883791208791201]",0.0,728,0.6071428571428571,0.49417740607604194,206,184,338,0.6553398058252428,0.07065217391304347,0.8698224852071006,0.7198209762573242,0.9542627266806466,0.596470832824707,0.4961586660450064,0.8410128951072693,0.036870802619627566,0.9065934065934066,2.5090439319610596,2.771914005279541,0.6009983420372009,0.600994348526001,3.980434485129081e-06,0.2230256050825119,0.6540490388870239 +valid,C3,0.3,synchrony_sync,0.21691507013507422,0.21691507013507422,"[0.30000000000000354, 0.1761774211270993, 0.17367689276640616]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.5254212454212455,"[0.30000000000000354, 0.6281043956043952, 0.6481593406593403]",0.25337912087912084,728,0.6057692307692307,0.4881817344938774,206,184,338,0.6650485436893204,0.059782608695652176,0.8668639053254438,0.7392285466194153,0.9758488908814854,0.5791566371917725,0.5012945729587569,0.8488643765449524,0.03161511832213664,0.9052197802197802,2.6002142429351807,2.7745168209075928,0.6374783515930176,0.6369290351867676,0.0005493339849635959,0.21676041185855865,0.6899773478507996 +valid,C3,0.3,synchrony_partial,0.1606943112281871,0.1606943112281871,"[0.30000000000000354, 0.1155318929339427, 0.06457046703790681]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.5020238095238095,"[0.30000000000000354, 0.604038461538462, 0.6020329670329673]",0.1646978021978022,728,0.6181318681318682,0.5051258955586794,206,184,338,0.6699029126213593,0.07608695652173914,0.8816568047337278,0.7251508235931396,0.9488413496104877,0.6016477942466736,0.49796989652425183,0.844016969203949,0.03577683161903214,0.9065934065934066,2.589043140411377,2.7753915786743164,0.6318191289901733,0.6312989592552185,0.0005201427266001701,0.22112886607646942,0.6843885183334351 +valid,C3,0.3,synchrony_async,0.20945741949355928,0.20945741949355928,"[0.30000000000000354, 0.16659314748477386, 0.16077606102751021]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.521437728937729,"[0.30000000000000354, 0.6226923076923089, 0.6416208791208796]",0.16925824175824175,728,0.6043956043956044,0.491820222170069,206,184,338,0.6456310679611651,0.07065217391304347,0.8698224852071006,0.7344034910202026,0.9649652566733213,0.5873648524284363,0.49913852333220954,0.8448799848556519,0.04529830563690636,0.9093406593406593,2.575655460357666,2.7697999477386475,0.6306455135345459,0.6302388310432434,0.0004066710826009512,0.22372829914093018,0.6822993755340576 +valid,C4,0.0,none,0.0,0.0,"[0.0, 0.0, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.0,728,0.6098901098901099,0.5569878493378154,206,184,338,0.6456310679611651,0.2554347826086957,0.7810650887573964,0.6913279294967651,0.9513293376826223,0.5684858560562134,0.5075285645522228,0.8570345640182495,0.05385225663309568,0.8983516483516484,2.538151264190674,2.8107221126556396,0.6382336020469666,0.6382023692131042,3.122318230452947e-05,0.20810236036777496,0.6501842141151428 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0.5803021978021985]",0.056428571428571425,728,0.6071428571428571,0.5513144396980693,206,184,338,0.6504854368932039,0.2391304347826087,0.7810650887573964,0.6901516914367676,0.9423340779881683,0.5765157341957092,0.508679199945502,0.8580012321472168,0.05041490298706097,0.9052197802197802,2.5577967166900635,2.8080742359161377,0.6477530002593994,0.6473243236541748,0.000428659375756979,0.20946292579174042,0.6596129536628723 +valid,C4,0.1,partial,0.0529758085036651,0.0529758085036651,"[0.08420329670329753, 0.03822459277521008, 0.03615291038442729]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.40424908424908423,"[0.08420329670329753, 0.5525274725274731, 0.5760164835164839]",0.043351648351648356,728,0.6181318681318682,0.5629823795879468,206,184,338,0.6601941747572816,0.25,0.7928994082840237,0.6881271600723267,0.9477462964781758,0.5724332332611084,0.5068940722576415,0.8560928702354431,0.06565405653564486,0.896978021978022,2.5606348514556885,2.807461977005005,0.6488605737686157,0.6483520865440369,0.0005085701704956591,0.20786507427692413,0.6607269644737244 +valid,C4,0.1,async,0.055965730621434076,0.055965730621434076,"[0.08420329670329753, 0.04282041186781863, 0.04055597458361638]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4039468864468865,"[0.08420329670329753, 0.5516208791208798, 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0.601785714285715]",0.05964285714285714,728,0.6057692307692307,0.5448574982784282,206,184,338,0.6407766990291263,0.22282608695652173,0.7928994082840237,0.7051863074302673,0.9625155199954686,0.558603048324585,0.507673148213059,0.8573735952377319,0.04350851091382268,0.9010989010989011,2.570042133331299,2.8108370304107666,0.6549414992332458,0.6542002558708191,0.0007412402774207294,0.2098354548215866,0.6666439771652222 +valid,C4,0.3,sync,0.18366496008611768,0.18366496008611768,"[0.2554945054945073, 0.14791849924316752, 0.1468227643446891]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.5004487179487179,"[0.2554945054945073, 0.6123626373626374, 0.6334890109890104]",0.18217032967032967,728,0.5961538461538461,0.527534842106031,206,184,338,0.6407766990291263,0.18478260869565216,0.7928994082840237,0.7100124955177307,0.9593676327599577,0.562080442905426,0.5095855077340617,0.8577635884284973,0.06812847626733258,0.907967032967033,2.6166911125183105,2.8060550689697266,0.6802869439125061,0.6783725023269653,0.0019144652178511024,0.21211282908916473,0.6918092370033264 +valid,C4,0.3,partial,0.14816552304516878,0.14816552304516878,"[0.25920329670329867, 0.10412618442414666, 0.07975758376464556]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.486978021978022,"[0.25920329670329867, 0.5950274725274726, 0.6067032967032975]",0.14230769230769233,728,0.5989010989010989,0.5334785261026341,206,184,338,0.6456310679611651,0.1956521739130435,0.7899408284023669,0.7163351774215698,0.9732804038460091,0.5495026111602783,0.5093533468669479,0.8578328490257263,0.041113063038050464,0.9065934065934066,2.6127071380615234,2.805129289627075,0.6775583028793335,0.6758576035499573,0.0017006900161504745,0.21300619840621948,0.6891117095947266 +valid,C4,0.3,async,0.17500872720325933,0.17500872720325933,"[0.2542582417582435, 0.14028985682217077, 0.12954125320803533]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4937454212454212,"[0.2542582417582435, 0.6036538461538465, 0.6233241758241765]",0.1337087912087912,728,0.6057692307692307,0.5389170418111896,206,184,338,0.6650485436893204,0.1956521739130435,0.7928994082840237,0.7097203731536865,0.9613115466570531,0.5613389015197754,0.5138969219718407,0.8662303686141968,0.053406955162574966,0.9065934065934066,2.6160168647766113,2.817478656768799,0.6830772161483765,0.6806262731552124,0.002450985135510564,0.21049091219902039,0.6945922374725342 +valid,C4,0.5,single,0.16685149244608855,0.16685149244608855,"[0.1620879120879121, 0.1638041073804625, 0.1748267839307003]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4674908424908425,"[0.1620879120879121, 0.6050549450549455, 0.6353296703296704]",0.08684065934065933,728,0.5961538461538461,0.5373018728963802,206,184,338,0.6310679611650486,0.22282608695652173,0.7781065088757396,0.7077146172523499,0.9631128576999805,0.5596314668655396,0.5092910323915248,0.860467255115509,0.047471394045994826,0.9038461538461539,2.5955708026885986,2.810917854309082,0.6697443723678589,0.6682873964309692,0.001456928439438343,0.21079090237617493,0.6814709305763245 +valid,C4,0.5,sync,0.330209128768783,0.330209128768783,"[0.42032967032967034, 0.28200237109380377, 0.2874135682232839]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.6007692307692307,"[0.42032967032967034, 0.678736263736264, 0.7032417582417585]",0.3127747252747253,728,0.6098901098901099,0.5318651950115886,206,184,338,0.6650485436893204,0.16304347826086957,0.8195266272189349,0.7272348999977112,0.982766093021158,0.5451382994651794,0.509232365469826,0.8592824339866638,0.04460896334641581,0.9065934065934066,2.698671579360962,2.8224802017211914,0.7255339622497559,0.7202438712120056,0.0052901082672178745,0.2339628040790558,0.7361394762992859 +valid,C4,0.5,partial,0.23623170531479354,0.23623170531479354,"[0.42032967032967034, 0.17341613672677042, 0.11239778582145649]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.5651465201465201,"[0.42032967032967034, 0.6398351648351651, 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0.6471428571428575]",0.2560989010989011,728,0.5906593406593407,0.5200467648099073,206,184,338,0.6310679611650486,0.1793478260869565,0.7899408284023669,0.7165269255638123,0.9669502830170809,0.5551301836967468,0.5127088252606401,0.8621368408203125,0.05095544039875596,0.9038461538461539,2.6266424655914307,2.8097054958343506,0.6849908828735352,0.6828132271766663,0.0021776871290057898,0.21012268960475922,0.6963889002799988 +valid,C4,0.3,location_start_T,0.10069156293222682,0.10069156293222682,"[0.30000000000000354, 0.0, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4615567765567765,"[0.30000000000000354, 0.5295054945054959, 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0.5551648351648366]",0.16035714285714286,728,0.5947802197802198,0.525344876852737,206,184,338,0.6504854368932039,0.1793478260869565,0.7869822485207101,0.7229676246643066,0.9721592931968658,0.5539432764053345,0.513436925681618,0.8651337027549744,0.03398163923686676,0.907967032967033,2.6410300731658936,2.818822145462036,0.691476583480835,0.6894509792327881,0.002025604248046875,0.21523481607437134,0.7030185461044312 +valid,C4,0.3,span_multi_short_T,0.10069156293222682,0.10069156293222682,"[0.30000000000000354, 0.0, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4615567765567765,"[0.30000000000000354, 0.5295054945054959, 0.5551648351648366]",0.1539010989010989,728,0.6071428571428571,0.5386058399227313,206,184,338,0.6601941747572816,0.19021739130434784,0.8017751479289941,0.7084731459617615,0.95430129585382,0.5685112476348877,0.5126237216893573,0.8635361790657043,0.06629022493303477,0.9052197802197802,2.647773265838623,2.806079626083374,0.6927803754806519,0.6907534599304199,0.002026882255449891,0.22048434615135193,0.7039671540260315 +valid,C4,0.3,location_start_A,0.2003851185549212,0.2003851185549212,"[0.0, 0.5970265414088254, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.44360805860805863,"[0.0, 0.7756593406593403, 0.5551648351648366]",0.0,728,0.6057692307692307,0.5576709586208229,206,184,338,0.6504854368932039,0.2717391304347826,0.7603550295857988,0.6834709644317627,0.9424449840850333,0.5742443799972534,0.5059969449858495,0.8552529215812683,0.04465316297425019,0.896978021978022,2.5180232524871826,2.811373472213745,0.6293177604675293,0.6292771697044373,4.058478225488216e-05,0.192414790391922,0.641381025314331 +valid,C4,0.3,location_middle_A,0.07214529279070561,0.07214529279070561,"[0.0, 0.21494936821846267, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.40606227106227105,"[0.0, 0.663021978021981, 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0.6816208791208818]",0.0,728,0.6071428571428571,0.553655293772217,206,184,338,0.6456310679611651,0.25,0.7781065088757396,0.6922222375869751,0.950975965811902,0.5665525794029236,0.5077181232442128,0.8573266267776489,0.056371394544839866,0.896978021978022,2.5260205268859863,2.8127121925354004,0.6309309005737305,0.6308948397636414,3.604379162425175e-05,0.20875044167041779,0.6428513526916504 +valid,C4,0.3,location_end_V,0.012031832650855376,0.012031832650855376,"[0.0, 0.0, 0.03660174617069467]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.37173992673992673,"[0.0, 0.5295054945054959, 0.5857142857142853]",0.0,728,0.6057692307692307,0.5521449299042166,206,184,338,0.6407766990291263,0.25,0.7781065088757396,0.6931080222129822,0.9515387358305389,0.5671343207359314,0.5073775614605772,0.8565467596054077,0.057168578831376625,0.8997252747252747,2.534005880355835,2.810692310333252,0.6349682807922363,0.6349362134933472,3.2025771361077204e-05,0.20778149366378784,0.6469323039054871 +valid,C4,0.3,span_long_V,0.09768688768578579,0.09768688768578579,"[0.0, 0.0, 0.29717091078607255]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4059615384615385,"[0.0, 0.5295054945054959, 0.6883791208791201]",0.0,728,0.6098901098901099,0.555693356057808,206,184,338,0.6456310679611651,0.25,0.7840236686390533,0.688922107219696,0.9425208746624658,0.5753633975982666,0.507891028813445,0.8574223518371582,0.0574537848869523,0.896978021978022,2.531496524810791,2.8119471073150635,0.6341637969017029,0.6341268420219421,3.6960125726182014e-05,0.2119438201189041,0.6460675597190857 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0.6481593406593403]",0.25337912087912084,728,0.5961538461538461,0.5258506273708355,206,184,338,0.6796116504854369,0.16847826086956522,0.7781065088757396,0.7077205181121826,0.9560675927013004,0.5673331022262573,0.5086808705203675,0.8582085967063904,0.047355427642117504,0.9038461538461539,2.6407604217529297,2.804429054260254,0.6930420994758606,0.6906667351722717,0.002375447889789939,0.20596535503864288,0.7044345736503601 +valid,C4,0.3,synchrony_partial,0.1606943112281871,0.1606943112281871,"[0.30000000000000354, 0.1155318929339427, 0.06457046703790681]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.5020238095238095,"[0.30000000000000354, 0.604038461538462, 0.6020329670329673]",0.1646978021978022,728,0.6112637362637363,0.5397402621085391,206,184,338,0.6796116504854369,0.1793478260869565,0.8047337278106509,0.7134761810302734,0.9666930171784202,0.5559995770454407,0.510187253630395,0.8594763875007629,0.05920950450248772,0.907967032967033,2.6267244815826416,2.812535285949707,0.6849125623703003,0.682677149772644,0.002235363470390439,0.2091907262802124,0.6962230205535889 +valid,C4,0.3,synchrony_async,0.20945741949355928,0.20945741949355928,"[0.30000000000000354, 0.16659314748477386, 0.16077606102751021]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.521437728937729,"[0.30000000000000354, 0.6226923076923089, 0.6416208791208796]",0.16925824175824175,728,0.5892857142857143,0.5175130281347898,206,184,338,0.6407766990291263,0.16847826086956522,0.7869822485207101,0.7202104926109314,0.9671278570023761,0.5520230531692505,0.5110345456977585,0.8616769909858704,0.05727644895131771,0.8997252747252747,2.619070529937744,2.813511371612549,0.6836082935333252,0.6807019710540771,0.00290630292147398,0.21603712439537048,0.694701611995697 +valid,C5,0.0,none,0.0,0.0,"[0.0, 0.0, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.0,728,0.6167582417582418,0.5472420438041464,206,184,338,0.6990291262135923,0.1956521739130435,0.7958579881656804,0.6614851951599121,0.8930216549130521,0.6175699830055237,0.49174852068999414,0.8373035788536072,0.05773796435895855,0.8928571428571429,2.3819849491119385,2.7619049549102783,0.5485381484031677,0.5485296845436096,8.432794857071713e-06,0.13909320533275604,0.5960483551025391 +valid,C5,0.1,single,0.033502520154928106,0.033502520154928106,"[0.03337912087912098, 0.03439424419379373, 0.03271803147679828]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.38305860805860803,"[0.03337912087912098, 0.5451923076923084, 0.5706043956043971]",0.0185989010989011,728,0.6181318681318682,0.5489006023531419,206,184,338,0.7038834951456311,0.1956521739130435,0.7958579881656804,0.6595794558525085,0.88945874600651,0.6203741431236267,0.4920802774163633,0.8378953337669373,0.05986269608467492,0.8914835164835165,2.390918731689453,2.762880802154541,0.5530403852462769,0.5530110597610474,2.9327909942367114e-05,0.14348389208316803,0.6002717614173889 +valid,C5,0.1,sync,0.057409428685793254,0.057409428685793254,"[0.0820054945054953, 0.04460700701510746, 0.04536767140601303]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4056593406593407,"[0.0820054945054953, 0.5546703296703304, 0.5803021978021985]",0.056428571428571425,728,0.6153846153846154,0.5396342159238499,206,184,338,0.6941747572815534,0.17391304347826086,0.8076923076923077,0.6589372158050537,0.8847905843889949,0.6247382164001465,0.4925871966416899,0.838698148727417,0.060096470250205675,0.8983516483516484,2.4029786586761475,2.7596659660339355,0.5568851232528687,0.5568243861198425,6.0677804867736995e-05,0.14488448202610016,0.6043494343757629 +valid,C5,0.1,partial,0.0529758085036651,0.0529758085036651,"[0.08420329670329753, 0.03822459277521008, 0.03615291038442729]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.40424908424908423,"[0.08420329670329753, 0.5525274725274731, 0.5760164835164839]",0.043351648351648356,728,0.6181318681318682,0.5483021392524529,206,184,338,0.7087378640776699,0.19021739130434784,0.7958579881656804,0.6611794233322144,0.8960318825873537,0.6156103610992432,0.4916744364065946,0.8371553421020508,0.0379934039089706,0.8901098901098901,2.4034833908081055,2.758849859237671,0.5572759509086609,0.557217538356781,5.8494220866123214e-05,0.14226530492305756,0.6048794388771057 +valid,C5,0.1,async,0.055965730621434076,0.055965730621434076,"[0.08420329670329753, 0.04282041186781863, 0.04055597458361638]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4039468864468865,"[0.08420329670329753, 0.5516208791208798, 0.5760164835164845]",0.05142857142857143,728,0.6167582417582418,0.5432278166156101,206,184,338,0.6893203883495146,0.18478260869565216,0.8076923076923077,0.6622811555862427,0.893508026072056,0.6171056628227234,0.49294278159240457,0.83913254737854,0.05998192883127338,0.8983516483516484,2.408254384994507,2.7590553760528564,0.5596915483474731,0.5596516728401184,3.98514348489698e-05,0.147719606757164,0.6072987914085388 +valid,C5,0.3,single,0.10077529965039936,0.10077529965039936,"[0.1063186813186808, 0.09791175417598566, 0.0980390854159867]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4273534798534799,"[0.1063186813186808, 0.573956043956045, 0.601785714285715]",0.05964285714285714,728,0.6112637362637363,0.5380377076765831,206,184,338,0.6893203883495146,0.1793478260869565,0.7988165680473372,0.669231653213501,0.8956744622403668,0.6156596541404724,0.4918112287600711,0.8359857797622681,0.06485877832868597,0.896978021978022,2.4159164428710938,2.757889986038208,0.560249388217926,0.5601537227630615,9.566651715431362e-05,0.14552167057991028,0.6075165867805481 +valid,C5,0.3,sync,0.18366496008611768,0.18366496008611768,"[0.2554945054945073, 0.14791849924316752, 0.1468227643446891]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.5004487179487179,"[0.2554945054945073, 0.6123626373626374, 0.6334890109890104]",0.18217032967032967,728,0.6126373626373627,0.541401215456943,206,184,338,0.6650485436893204,0.19021739130434784,0.8106508875739645,0.6740856170654297,0.9136993143137333,0.5995095372200012,0.4937200357938187,0.840497612953186,0.053928221565681486,0.8956043956043956,2.459724187850952,2.755039691925049,0.5795249342918396,0.5792222023010254,0.00030274500022642314,0.15784971415996552,0.6257649064064026 +valid,C5,0.3,partial,0.14816552304516878,0.14816552304516878,"[0.25920329670329867, 0.10412618442414666, 0.07975758376464556]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.486978021978022,"[0.25920329670329867, 0.5950274725274726, 0.6067032967032975]",0.14230769230769233,728,0.6112637362637363,0.5357198308570972,206,184,338,0.6699029126213593,0.17391304347826086,0.8136094674556213,0.6784146428108215,0.9127770212416307,0.6027075052261353,0.49289143649211886,0.8388406038284302,0.0645824611432605,0.8942307692307693,2.4566433429718018,2.7545132637023926,0.5788444876670837,0.5785822868347168,0.0002622170723043382,0.15790113806724548,0.6260029077529907 +valid,C5,0.3,async,0.17500872720325933,0.17500872720325933,"[0.2542582417582435, 0.14028985682217077, 0.12954125320803533]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4937454212454212,"[0.2542582417582435, 0.6036538461538465, 0.6233241758241765]",0.1337087912087912,728,0.6098901098901099,0.5325178988754369,206,184,338,0.6747572815533981,0.16304347826086957,0.8136094674556213,0.6756373047828674,0.8973184001250631,0.6162045001983643,0.4981202413053479,0.8470883369445801,0.03059149775040019,0.896978021978022,2.4541327953338623,2.765819549560547,0.5785694122314453,0.5783915519714355,0.0001778588048182428,0.16279031336307526,0.6258245706558228 +valid,C5,0.5,single,0.16685149244608855,0.16685149244608855,"[0.1620879120879121, 0.1638041073804625, 0.1748267839307003]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4674908424908425,"[0.1620879120879121, 0.6050549450549455, 0.6353296703296704]",0.08684065934065933,728,0.6071428571428571,0.5285253659375108,206,184,338,0.6844660194174758,0.15760869565217392,0.8047337278106509,0.6678246259689331,0.8946117714701638,0.6191571354866028,0.49207917218874075,0.8386296033859253,0.054037242022516946,0.8983516483516484,2.446805715560913,2.7546329498291016,0.5741900205612183,0.573969304561615,0.00022075198648963124,0.14752022922039032,0.6218494772911072 +valid,C5,0.5,sync,0.330209128768783,0.330209128768783,"[0.42032967032967034, 0.28200237109380377, 0.2874135682232839]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.6007692307692307,"[0.42032967032967034, 0.678736263736264, 0.7032417582417585]",0.3127747252747253,728,0.6057692307692307,0.5213298097136545,206,184,338,0.6310679611650486,0.14673913043478262,0.8402366863905325,0.6963767409324646,0.9322161546242445,0.5873285531997681,0.4960950953864169,0.8446182608604431,0.04536890901707031,0.9120879120879121,2.5487372875213623,2.7637739181518555,0.6099886894226074,0.6092244386672974,0.0007641960401087999,0.17864857614040375,0.6559954881668091 +valid,C5,0.5,partial,0.23623170531479354,0.23623170531479354,"[0.42032967032967034, 0.17341613672677042, 0.11239778582145649]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.5651465201465201,"[0.42032967032967034, 0.6398351648351651, 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0.6481593406593403]",0.25337912087912084,728,0.6016483516483516,0.5301058450681209,206,184,338,0.6747572815533981,0.17391304347826086,0.7899408284023669,0.6838570833206177,0.9243095385603125,0.5931302905082703,0.49524491136922694,0.8425077795982361,0.03958872153045056,0.8983516483516484,2.483738899230957,2.755643129348755,0.5894203782081604,0.5890901684761047,0.00033016822999343276,0.15079925954341888,0.6362156271934509 +valid,C5,0.3,synchrony_partial,0.1606943112281871,0.1606943112281871,"[0.30000000000000354, 0.1155318929339427, 0.06457046703790681]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.5020238095238095,"[0.30000000000000354, 0.604038461538462, 0.6020329670329673]",0.1646978021978022,728,0.6181318681318682,0.5514262781135847,206,184,338,0.6650485436893204,0.21195652173913043,0.8106508875739645,0.6768262386322021,0.9173706053875333,0.5965014100074768,0.4935110350667361,0.8401702046394348,0.03957863409931843,0.8956043956043956,2.468583106994629,2.7561984062194824,0.5812085866928101,0.5808792114257812,0.00032939977245405316,0.15699560940265656,0.6278435587882996 +valid,C5,0.3,synchrony_async,0.20945741949355928,0.20945741949355928,"[0.30000000000000354, 0.16659314748477386, 0.16077606102751021]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.521437728937729,"[0.30000000000000354, 0.6226923076923089, 0.6416208791208796]",0.16925824175824175,728,0.6153846153846154,0.5411840411840413,206,184,338,0.6553398058252428,0.18478260869565216,0.8254437869822485,0.6807641386985779,0.9189795590058603,0.5979559421539307,0.4921325464621979,0.8382850289344788,0.04231483861804009,0.896978021978022,2.4651546478271484,2.7534947395324707,0.5807542204856873,0.5805057883262634,0.00024844935978762805,0.16378213465213776,0.6288806796073914 +valid,C6,0.0,none,0.0,0.0,"[0.0, 0.0, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.0,728,0.6263736263736264,0.5801114274083624,206,184,338,0.6941747572815534,0.29891304347826086,0.7633136094674556,0.6456943154335022,0.8813849190313564,0.6157324910163879,0.48558900116476555,0.825786828994751,0.03072096133133867,0.885989010989011,2.303966760635376,2.7744319438934326,0.4941808581352234,0.49413588643074036,4.500564682530239e-05,0.1355716735124588,0.5317699909210205 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0.5760164835164839]",0.043351648351648356,728,0.6195054945054945,0.568898052766151,206,184,338,0.6941747572815534,0.2717391304347826,0.7633136094674556,0.6582462787628174,0.9042675433747003,0.598304271697998,0.48644176869281464,0.8264215588569641,0.03630328293030078,0.8887362637362637,2.3265907764434814,2.7751917839050293,0.5025209188461304,0.5024195313453674,0.00010140323865925893,0.13817299902439117,0.5407764911651611 +valid,C6,0.1,async,0.055965730621434076,0.055965730621434076,"[0.08420329670329753, 0.04282041186781863, 0.04055597458361638]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4039468864468865,"[0.08420329670329753, 0.5516208791208798, 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0.6883791208791201]",0.0,728,0.6263736263736264,0.5814246312735377,206,184,338,0.6990291262135923,0.30434782608695654,0.757396449704142,0.6450521349906921,0.8811303375381201,0.61766117811203,0.4853404830667741,0.8254954814910889,0.030535974181615397,0.8887362637362637,2.3104758262634277,2.7739577293395996,0.4966231882572174,0.4965746998786926,4.852267011301592e-05,0.12603648006916046,0.5347470045089722 +valid,C6,0.3,synchrony_sync,0.21691507013507422,0.21691507013507422,"[0.30000000000000354, 0.1761774211270993, 0.17367689276640616]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.5254212454212455,"[0.30000000000000354, 0.6281043956043952, 0.6481593406593403]",0.25337912087912084,728,0.6291208791208791,0.5762170427308042,206,184,338,0.7038834951456311,0.266304347826087,0.7810650887573964,0.662735641002655,0.9098049025944585,0.5976772904396057,0.4903485686372147,0.8321426510810852,0.03340759828359217,0.9010989010989011,2.420468330383301,2.764493942260742,0.5428679585456848,0.5423406958580017,0.0005272903363220394,0.1430121660232544,0.5818544030189514 +valid,C6,0.3,synchrony_partial,0.1606943112281871,0.1606943112281871,"[0.30000000000000354, 0.1155318929339427, 0.06457046703790681]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.5020238095238095,"[0.30000000000000354, 0.604038461538462, 0.6020329670329673]",0.1646978021978022,728,0.6304945054945055,0.5752769201126008,206,184,338,0.7087378640776699,0.2554347826086957,0.7869822485207101,0.6528188586235046,0.879726417182059,0.6211951375007629,0.48811207155603376,0.8292350172996521,0.04215612475361144,0.8928571428571429,2.401604652404785,2.779353618621826,0.5336208343505859,0.5331476926803589,0.00047312211245298386,0.14702092111110687,0.5716752409934998 +valid,C6,0.3,synchrony_async,0.20945741949355928,0.20945741949355928,"[0.30000000000000354, 0.16659314748477386, 0.16077606102751021]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.521437728937729,"[0.30000000000000354, 0.6226923076923089, 0.6416208791208796]",0.16925824175824175,728,0.6291208791208791,0.5739935955170545,206,184,338,0.6893203883495146,0.2554347826086957,0.7958579881656804,0.6543288826942444,0.8883779186299061,0.6126687526702881,0.4852166610746401,0.8250834941864014,0.02794261546907844,0.8928571428571429,2.3844473361968994,2.761791944503784,0.5316479206085205,0.5312361717224121,0.00041176145896315575,0.15687869489192963,0.5703586339950562 +valid,C6_no_distance,0.0,none,0.0,0.0,"[0.0, 0.0, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.0,728,0.603021978021978,0.5116790727202128,206,184,338,0.6553398058252428,0.125,0.8313609467455622,0.6800156831741333,0.9099615977641681,0.6044881939888,0.5039438593570612,0.8586037755012512,0.0480126314847679,0.885989010989011,2.297931432723999,2.808403968811035,0.47149500250816345,0.47139686346054077,9.814117947826162e-05,0.14792194962501526,0.5429384112358093 +valid,C6_no_distance,0.1,single,0.033502520154928106,0.033502520154928106,"[0.03337912087912098, 0.03439424419379373, 0.03271803147679828]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.38305860805860803,"[0.03337912087912098, 0.5451923076923084, 0.5706043956043971]",0.0185989010989011,728,0.6071428571428571,0.5188380787823315,206,184,338,0.6601941747572816,0.1358695652173913,0.8313609467455622,0.6758347153663635,0.9008190600358085,0.61191326379776,0.5043383643940932,0.8590077757835388,0.036589882571946133,0.8846153846153846,2.3031351566314697,2.8081717491149902,0.47384384274482727,0.4736623167991638,0.0001815168361645192,0.14996376633644104,0.5451262593269348 +valid,C6_no_distance,0.1,sync,0.057409428685793254,0.057409428685793254,"[0.0820054945054953, 0.04460700701510746, 0.04536767140601303]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4056593406593407,"[0.0820054945054953, 0.5546703296703304, 0.5803021978021985]",0.056428571428571425,728,0.603021978021978,0.5063580320817459,206,184,338,0.6601941747572816,0.10869565217391304,0.8372781065088757,0.6779942512512207,0.9005527309036382,0.6123272776603699,0.5047631646557449,0.8594794869422913,0.04864421793883972,0.885989010989011,2.3134260177612305,2.806450366973877,0.47682708501815796,0.47651413083076477,0.0003129875403828919,0.1484779715538025,0.5480008721351624 +valid,C6_no_distance,0.1,partial,0.0529758085036651,0.0529758085036651,"[0.08420329670329753, 0.03822459277521008, 0.03615291038442729]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.40424908424908423,"[0.08420329670329753, 0.5525274725274731, 0.5760164835164839]",0.043351648351648356,728,0.6016483516483516,0.5102185746939096,206,184,338,0.6553398058252428,0.125,0.8284023668639053,0.6817261576652527,0.9068343153279091,0.607669472694397,0.5044043533299047,0.858725905418396,0.03344730586632268,0.8832417582417582,2.3130528926849365,2.804426670074463,0.4770118296146393,0.4766868054866791,0.0003250441513955593,0.1470816433429718,0.5487915277481079 +valid,C6_no_distance,0.1,async,0.055965730621434076,0.055965730621434076,"[0.08420329670329753, 0.04282041186781863, 0.04055597458361638]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4039468864468865,"[0.08420329670329753, 0.5516208791208798, 0.5760164835164845]",0.05142857142857143,728,0.603021978021978,0.5083962041297005,206,184,338,0.6650485436893204,0.11413043478260869,0.8313609467455622,0.6788546442985535,0.9037274736944789,0.609045147895813,0.5046919644680327,0.8593211770057678,0.04384335687199793,0.8804945054945055,2.3143370151519775,2.8068063259124756,0.4781991243362427,0.4779539406299591,0.00024518315331079066,0.14838172495365143,0.549241304397583 +valid,C6_no_distance,0.3,single,0.10077529965039936,0.10077529965039936,"[0.1063186813186808, 0.09791175417598566, 0.0980390854159867]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4273534798534799,"[0.1063186813186808, 0.573956043956045, 0.601785714285715]",0.05964285714285714,728,0.6016483516483516,0.5104171172143991,206,184,338,0.6456310679611651,0.125,0.834319526627219,0.6842509508132935,0.9118921646165563,0.6017282605171204,0.5042787462455491,0.8581734299659729,0.033883049224431715,0.8873626373626373,2.3233883380889893,2.801600217819214,0.4801526665687561,0.4796600043773651,0.000492676452267915,0.1498512476682663,0.5513209700584412 +valid,C6_no_distance,0.3,sync,0.18366496008611768,0.18366496008611768,"[0.2554945054945073, 0.14791849924316752, 0.1468227643446891]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.5004487179487179,"[0.2554945054945073, 0.6123626373626374, 0.6334890109890104]",0.18217032967032967,728,0.6002747252747253,0.5078592967988163,206,184,338,0.6504854368932039,0.11956521739130435,0.8313609467455622,0.6915753483772278,0.9221619304963045,0.5919369459152222,0.5050535412076946,0.8600478172302246,0.05068780404034553,0.885989010989011,2.3570899963378906,2.7995214462280273,0.494854211807251,0.4936692416667938,0.0011849923757836223,0.15761712193489075,0.565216064453125 +valid,C6_no_distance,0.3,partial,0.14816552304516878,0.14816552304516878,"[0.25920329670329867, 0.10412618442414666, 0.07975758376464556]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.486978021978022,"[0.25920329670329867, 0.5950274725274726, 0.6067032967032975]",0.14230769230769233,728,0.6002747252747253,0.5035969855838348,206,184,338,0.6456310679611651,0.10869565217391304,0.8402366863905325,0.6867015361785889,0.9168567496513598,0.5981215238571167,0.5053624501796731,0.861283540725708,0.06438011827540921,0.8873626373626373,2.355496644973755,2.799398183822632,0.4937240183353424,0.49260184168815613,0.0011221958557143807,0.14871539175510406,0.5646313428878784 +valid,C6_no_distance,0.3,async,0.17500872720325933,0.17500872720325933,"[0.2542582417582435, 0.14028985682217077, 0.12954125320803533]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4937454212454212,"[0.2542582417582435, 0.6036538461538465, 0.6233241758241765]",0.1337087912087912,728,0.5865384615384616,0.4937375742619148,206,184,338,0.6407766990291263,0.10869565217391304,0.8136094674556213,0.7048642635345459,0.9449383334066542,0.5716733932495117,0.5103592018766053,0.8680533766746521,0.050310954615309995,0.8832417582417582,2.3551599979400635,2.818431854248047,0.4943493902683258,0.4934805929660797,0.0008687807712703943,0.1426064372062683,0.5644980669021606 +valid,C6_no_distance,0.5,single,0.16685149244608855,0.16685149244608855,"[0.1620879120879121, 0.1638041073804625, 0.1748267839307003]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4674908424908425,"[0.1620879120879121, 0.6050549450549455, 0.6353296703296704]",0.08684065934065933,728,0.5975274725274725,0.5034451788004649,206,184,338,0.6553398058252428,0.10869565217391304,0.8284023668639053,0.6825225949287415,0.9092156457397311,0.6047633290290833,0.5034140770896709,0.8581359386444092,0.04626582939546189,0.8818681318681318,2.3456084728240967,2.797497034072876,0.4890317916870117,0.48807504773139954,0.0009567051311023533,0.14906100928783417,0.5599066019058228 +valid,C6_no_distance,0.5,sync,0.330209128768783,0.330209128768783,"[0.42032967032967034, 0.28200237109380377, 0.2874135682232839]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.6007692307692307,"[0.42032967032967034, 0.678736263736264, 0.7032417582417585]",0.3127747252747253,728,0.6002747252747253,0.5037948026643373,206,184,338,0.6407766990291263,0.10869565217391304,0.8431952662721893,0.6847909688949585,0.8960111944189016,0.61216139793396,0.5046291925853802,0.8571000099182129,0.040857984346675355,0.8901098901098901,2.4293463230133057,2.7924225330352783,0.5202634334564209,0.5174888968467712,0.0027745207771658897,0.1692734807729721,0.5879436731338501 +valid,C6_no_distance,0.5,partial,0.23623170531479354,0.23623170531479354,"[0.42032967032967034, 0.17341613672677042, 0.11239778582145649]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.5651465201465201,"[0.42032967032967034, 0.6398351648351651, 0.635274725274725]",0.24862637362637363,728,0.5989010989010989,0.5050668816026986,206,184,338,0.6456310679611651,0.11413043478260869,0.834319526627219,0.6986975073814392,0.9324403285552503,0.579910933971405,0.5115398146998509,0.8708056807518005,0.055180452518410715,0.8804945054945055,2.417854070663452,2.814492702484131,0.5168108344078064,0.5142998099327087,0.002510938560590148,0.15570221841335297,0.5840623378753662 +valid,C6_no_distance,0.5,async,0.3120007279622296,0.3120007279622296,"[0.4065934065934066, 0.2579016785179102, 0.27065519914311004]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.5900000000000001,"[0.4065934065934066, 0.6680769230769213, 0.6953296703296687]",0.23804945054945056,728,0.5961538461538461,0.49672251941318407,206,184,338,0.6601941747572816,0.09782608695652174,0.8284023668639053,0.6976437568664551,0.921867305917475,0.5922781825065613,0.5126114806036176,0.8706068992614746,0.05456122281132165,0.8818681318681318,2.412856101989746,2.8198182582855225,0.5135301947593689,0.5117381811141968,0.001791996299289167,0.14064928889274597,0.5830172896385193 +valid,C6_no_distance,0.7,single,0.23221469003340273,0.23221469003340273,"[0.22115384615384592, 0.2612316954439274, 0.21388076914343795]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.5095421245421247,"[0.22115384615384592, 0.65239010989011, 0.655082417582419]",0.1204945054945055,728,0.6016483516483516,0.5070397297060157,206,184,338,0.6650485436893204,0.11413043478260869,0.8284023668639053,0.6993075609207153,0.9227717289377729,0.5944802165031433,0.5087453754869518,0.8667778372764587,0.03488803519816189,0.896978021978022,2.395965337753296,2.8084123134613037,0.508386492729187,0.5064146518707275,0.001971904654055834,0.14375267922878265,0.5781477093696594 +valid,C6_no_distance,0.7,sync,0.505389528795785,0.505389528795785,"[0.5807692307692247, 0.47634612944176064, 0.4580784091507095]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.7128296703296704,"[0.5807692307692247, 0.7772252747252746, 0.7804945054945048]",0.44958791208791204,728,0.5947802197802198,0.5069876749474366,206,184,338,0.6019417475728155,0.14130434782608695,0.8372781065088757,0.713942289352417,0.9592106196830549,0.5535411834716797,0.5199459431681731,0.8810686469078064,0.04756647332029029,0.8914835164835165,2.5477800369262695,2.8207948207855225,0.5636929273605347,0.5574854016304016,0.006207493599504232,0.16609056293964386,0.6271430850028992 +valid,C6_no_distance,0.7,partial,0.39062347526393004,0.39062347526393004,"[0.5788461538461478, 0.31403194162971376, 0.27664384900565697]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.6740018315018315,"[0.5788461538461478, 0.7185989010989093, 0.7245604395604472]",0.40997252747252755,728,0.6112637362637363,0.5271121447457674,206,184,338,0.6456310679611651,0.15217391304347827,0.8402366863905325,0.7028897404670715,0.9405053604435603,0.5665954947471619,0.5154218630537399,0.8763142824172974,0.07305360253859354,0.8914835164835165,2.5309665203094482,2.813135862350464,0.5541664361953735,0.548302173614502,0.005864223465323448,0.1684773564338684,0.6167246103286743 +valid,C6_no_distance,0.7,async,0.48300135283868606,0.48300135283868606,"[0.5932692307692244, 0.43288957390738114, 0.42157969775951804]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.7052930402930403,"[0.5932692307692244, 0.7602747252747305, 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0.6883791208791201]",0.0,728,0.6043956043956044,0.512375512418798,206,184,338,0.6504854368932039,0.125,0.8372781065088757,0.6780402660369873,0.9066544320938281,0.6052189469337463,0.5039651738829387,0.8586159348487854,0.04056978291207617,0.8846153846153846,2.2870514392852783,2.810041904449463,0.4677826166152954,0.46767154335975647,0.00011111463390989229,0.15054407715797424,0.5382970571517944 +valid,C6_no_distance,0.3,synchrony_sync,0.21691507013507422,0.21691507013507422,"[0.30000000000000354, 0.1761774211270993, 0.17367689276640616]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.5254212454212455,"[0.30000000000000354, 0.6281043956043952, 0.6481593406593403]",0.25337912087912084,728,0.5961538461538461,0.5004410501920359,206,184,338,0.6456310679611651,0.10869565217391304,0.8313609467455622,0.6964983940124512,0.9240079224936297,0.5917818546295166,0.507749968942057,0.8629916906356812,0.044692197302868074,0.8804945054945055,2.374363422393799,2.800792932510376,0.5000799894332886,0.4987024962902069,0.0013774668332189322,0.14465463161468506,0.5709747672080994 +valid,C6_no_distance,0.3,synchrony_partial,0.1606943112281871,0.1606943112281871,"[0.30000000000000354, 0.1155318929339427, 0.06457046703790681]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.5020238095238095,"[0.30000000000000354, 0.604038461538462, 0.6020329670329673]",0.1646978021978022,728,0.5961538461538461,0.5051836334462471,206,184,338,0.6359223300970874,0.125,0.8284023668639053,0.6970412135124207,0.9225480160713003,0.5913355350494385,0.506016095622675,0.8603171110153198,0.03613695907560022,0.8777472527472527,2.368182897567749,2.805279493331909,0.4988555908203125,0.49756747484207153,0.0012880951398983598,0.14646659791469574,0.5686797499656677 +valid,C6_no_distance,0.3,synchrony_async,0.20945741949355928,0.20945741949355928,"[0.30000000000000354, 0.16659314748477386, 0.16077606102751021]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.521437728937729,"[0.30000000000000354, 0.6226923076923089, 0.6416208791208796]",0.16925824175824175,728,0.6016483516483516,0.5039578620584847,206,184,338,0.6601941747572816,0.10326086956521739,0.8372781065088757,0.6824854016304016,0.9049218738934315,0.6063346862792969,0.5056557870720163,0.8609285354614258,0.04320379993417761,0.8873626373626373,2.363499641418457,2.801095485687256,0.4974028170108795,0.4962787330150604,0.0011240869062021375,0.15004919469356537,0.5668689608573914 +valid,C6_no_reconstruction,0.0,none,0.0,0.0,"[0.0, 0.0, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.0,728,0.6016483516483516,0.5202652256673378,206,184,338,0.6650485436893204,0.14673913043478262,0.8106508875739645,0.6958225965499878,0.9330084973405222,0.5885183215141296,0.5025339750564322,0.8509365320205688,0.04845173661034186,0.8928571428571429,2.3902220726013184,2.7945191860198975,0.5634521842002869,0.5634352564811707,1.692845398792997e-05,0.1890193670988083,0.6063776612281799 +valid,C6_no_reconstruction,0.1,single,0.033502520154928106,0.033502520154928106,"[0.03337912087912098, 0.03439424419379373, 0.03271803147679828]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.38305860805860803,"[0.03337912087912098, 0.5451923076923084, 0.5706043956043971]",0.0185989010989011,728,0.6002747252747253,0.5169083449614574,206,184,338,0.6601941747572816,0.14130434782608695,0.8136094674556213,0.6993690729141235,0.9348456954617017,0.5868916511535645,0.5023233461115164,0.8504254817962646,0.05567758350254416,0.8928571428571429,2.4024767875671387,2.79293155670166,0.5669052004814148,0.566868007183075,3.719741289387457e-05,0.1880558282136917,0.6097264289855957 +valid,C6_no_reconstruction,0.1,sync,0.057409428685793254,0.057409428685793254,"[0.0820054945054953, 0.04460700701510746, 0.04536767140601303]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4056593406593407,"[0.0820054945054953, 0.5546703296703304, 0.5803021978021985]",0.056428571428571425,728,0.6016483516483516,0.5187734410912527,206,184,338,0.6699029126213593,0.14130434782608695,0.8106508875739645,0.6921753287315369,0.9179788791828124,0.601701021194458,0.5029531663455595,0.8508331179618835,0.07187423503005898,0.8983516483516484,2.417815685272217,2.789848804473877,0.5718045234680176,0.5717378258705139,6.672218296444044e-05,0.18558460474014282,0.6142747402191162 +valid,C6_no_reconstruction,0.1,partial,0.0529758085036651,0.0529758085036651,"[0.08420329670329753, 0.03822459277521008, 0.03615291038442729]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.40424908424908423,"[0.08420329670329753, 0.5525274725274731, 0.5760164835164839]",0.043351648351648356,728,0.6016483516483516,0.5157735122089314,206,184,338,0.6650485436893204,0.1358695652173913,0.8165680473372781,0.7000133395195007,0.9417619152059631,0.5820462703704834,0.5026777618407421,0.8510737419128418,0.05215315782761834,0.8983516483516484,2.4202451705932617,2.7895853519439697,0.5727391242980957,0.5726679563522339,7.109072612365708e-05,0.1829950511455536,0.615588366985321 +valid,C6_no_reconstruction,0.1,async,0.055965730621434076,0.055965730621434076,"[0.08420329670329753, 0.04282041186781863, 0.04055597458361638]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4039468864468865,"[0.08420329670329753, 0.5516208791208798, 0.5760164835164845]",0.05142857142857143,728,0.5989010989010989,0.5128310047552057,206,184,338,0.6699029126213593,0.13043478260869565,0.8106508875739645,0.6975716948509216,0.9257568484925308,0.5936945080757141,0.5035482471125383,0.8525945544242859,0.044708975273501754,0.8956043956043956,2.428295850753784,2.7924270629882812,0.5756955146789551,0.5756346583366394,6.0881800891365856e-05,0.18525128066539764,0.6172874569892883 +valid,C6_no_reconstruction,0.3,single,0.10077529965039936,0.10077529965039936,"[0.1063186813186808, 0.09791175417598566, 0.0980390854159867]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4273534798534799,"[0.1063186813186808, 0.573956043956045, 0.601785714285715]",0.05964285714285714,728,0.6002747252747253,0.5206449767886464,206,184,338,0.6553398058252428,0.15217391304347827,0.8106508875739645,0.703782320022583,0.9444478707313719,0.5792710781097412,0.5026483557715105,0.8514201641082764,0.04827124715506376,0.896978021978022,2.44488263130188,2.791378974914551,0.5798749327659607,0.5797304511070251,0.00014452844334300607,0.18708699941635132,0.6226592659950256 +valid,C6_no_reconstruction,0.3,sync,0.18366496008611768,0.18366496008611768,"[0.2554945054945073, 0.14791849924316752, 0.1468227643446891]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.5004487179487179,"[0.2554945054945073, 0.6123626373626374, 0.6334890109890104]",0.18217032967032967,728,0.592032967032967,0.49867915829165493,206,184,338,0.6601941747572816,0.10869565217391304,0.8136094674556213,0.7136086225509644,0.9357202484737509,0.5889030694961548,0.5028191696964722,0.8519359827041626,0.052349157999832543,0.8983516483516484,2.51239275932312,2.785808801651001,0.6021613478660583,0.6017847657203674,0.0003765236178878695,0.18310949206352234,0.6438292264938354 +valid,C6_no_reconstruction,0.3,partial,0.14816552304516878,0.14816552304516878,"[0.25920329670329867, 0.10412618442414666, 0.07975758376464556]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.486978021978022,"[0.25920329670329867, 0.5950274725274726, 0.6067032967032975]",0.14230769230769233,728,0.5975274725274725,0.5091381972477246,206,184,338,0.6650485436893204,0.125,0.8136094674556213,0.708671510219574,0.943148824442679,0.5819876194000244,0.500118672975913,0.847955048084259,0.038408161888083256,0.9093406593406593,2.5018324851989746,2.775395393371582,0.5997633934020996,0.5994231700897217,0.0003401984286028892,0.18151716887950897,0.6413524150848389 +valid,C6_no_reconstruction,0.3,async,0.17500872720325933,0.17500872720325933,"[0.2542582417582435, 0.14028985682217077, 0.12954125320803533]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4937454212454212,"[0.2542582417582435, 0.6036538461538465, 0.6233241758241765]",0.1337087912087912,728,0.6098901098901099,0.525559035291173,206,184,338,0.6941747572815534,0.14130434782608695,0.8136094674556213,0.7013431787490845,0.9232647651960552,0.5978975296020508,0.5024217331680343,0.8536381721496582,0.04091242258692836,0.9052197802197802,2.5205307006835938,2.79042387008667,0.6038336157798767,0.6035045385360718,0.0003290379827376455,0.17321860790252686,0.6443148851394653 +valid,C6_no_reconstruction,0.5,single,0.16685149244608855,0.16685149244608855,"[0.1620879120879121, 0.1638041073804625, 0.1748267839307003]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4674908424908425,"[0.1620879120879121, 0.6050549450549455, 0.6353296703296704]",0.08684065934065933,728,0.6057692307692307,0.521565604364054,206,184,338,0.6747572815533981,0.14130434782608695,0.8165680473372781,0.7003881931304932,0.9394121061954498,0.5878214240074158,0.5015309571085504,0.8503543138504028,0.03097276856283566,0.9024725274725275,2.4916059970855713,2.783886671066284,0.600360631942749,0.599987268447876,0.00037337568937800825,0.1837887167930603,0.6425393223762512 +valid,C6_no_reconstruction,0.5,sync,0.330209128768783,0.330209128768783,"[0.42032967032967034, 0.28200237109380377, 0.2874135682232839]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.6007692307692307,"[0.42032967032967034, 0.678736263736264, 0.7032417582417585]",0.3127747252747253,728,0.603021978021978,0.5103805957593329,206,184,338,0.6990291262135923,0.10869565217391304,0.8136094674556213,0.7190809845924377,0.9376486978225157,0.5898188948631287,0.49989512984760825,0.8484047651290894,0.05535110213108115,0.9203296703296703,2.6516692638397217,2.7781639099121094,0.6478151082992554,0.6466209292411804,0.00119423505384475,0.18025633692741394,0.6874412298202515 +valid,C6_no_reconstruction,0.5,partial,0.23623170531479354,0.23623170531479354,"[0.42032967032967034, 0.17341613672677042, 0.11239778582145649]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.5651465201465201,"[0.42032967032967034, 0.6398351648351651, 0.635274725274725]",0.24862637362637363,728,0.6057692307692307,0.5154088848751237,206,184,338,0.6844660194174758,0.125,0.8195266272189349,0.7154918909072876,0.9406249417022992,0.5862635970115662,0.5054398620648359,0.8592013120651245,0.024925322691490375,0.9093406593406593,2.632240056991577,2.7939326763153076,0.6422931551933289,0.6412857174873352,0.0010074478341266513,0.17789404094219208,0.6819989681243896 +valid,C6_no_reconstruction,0.5,async,0.3120007279622296,0.3120007279622296,"[0.4065934065934066, 0.2579016785179102, 0.27065519914311004]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.5900000000000001,"[0.4065934065934066, 0.6680769230769213, 0.6953296703296687]",0.23804945054945056,728,0.5906593406593407,0.4909340577214805,206,184,338,0.6747572815533981,0.09239130434782608,0.8106508875739645,0.7356505393981934,0.9709581619583614,0.5602580904960632,0.5083535572487787,0.8627154231071472,0.04870010298359525,0.9024725274725275,2.6459176540374756,2.7947804927825928,0.6485304236412048,0.6476343870162964,0.0008960908162407577,0.16630299389362335,0.6865618228912354 +valid,C6_no_reconstruction,0.7,single,0.23221469003340273,0.23221469003340273,"[0.22115384615384592, 0.2612316954439274, 0.21388076914343795]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.5095421245421247,"[0.22115384615384592, 0.65239010989011, 0.655082417582419]",0.1204945054945055,728,0.5892857142857143,0.4937095651523246,206,184,338,0.6699029126213593,0.09782608695652174,0.8076923076923077,0.7239422798156738,0.9459090124149964,0.5851625204086304,0.50672096196033,0.8602827191352844,0.05469725890965253,0.9052197802197802,2.559399366378784,2.794888973236084,0.6246117949485779,0.6237711906433105,0.0008406289271079004,0.16799558699131012,0.6658414602279663 +valid,C6_no_reconstruction,0.7,sync,0.505389528795785,0.505389528795785,"[0.5807692307692247, 0.47634612944176064, 0.4580784091507095]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.7128296703296704,"[0.5807692307692247, 0.7772252747252746, 0.7804945054945048]",0.44958791208791204,728,0.592032967032967,0.4835011880150848,206,184,338,0.6796116504854369,0.07065217391304347,0.8224852071005917,0.7612572908401489,0.9936205809669257,0.545553982257843,0.514641834258471,0.87520432472229,0.057044024364306375,0.9120879120879121,2.8389923572540283,2.8114051818847656,0.726079523563385,0.72312992811203,0.002949619898572564,0.15774329006671906,0.7595593929290771 +valid,C6_no_reconstruction,0.7,partial,0.39062347526393004,0.39062347526393004,"[0.5788461538461478, 0.31403194162971376, 0.27664384900565697]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.6740018315018315,"[0.5788461538461478, 0.7185989010989093, 0.7245604395604472]",0.40997252747252755,728,0.6016483516483516,0.49671535080173523,206,184,338,0.6844660194174758,0.08695652173913043,0.8313609467455622,0.7489723563194275,0.9816708433734875,0.5501648187637329,0.5083767071390082,0.8667750954627991,0.061205053845277205,0.9107142857142857,2.811969041824341,2.7981512546539307,0.7090732455253601,0.7062726616859436,0.0028006467036902905,0.16461743414402008,0.7423130869865417 +valid,C6_no_reconstruction,0.7,async,0.48300135283868606,0.48300135283868606,"[0.5932692307692244, 0.43288957390738114, 0.42157969775951804]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.7052930402930403,"[0.5932692307692244, 0.7602747252747305, 0.7623351648351689]",0.40626373626373624,728,0.6016483516483516,0.4913258251714236,206,184,338,0.6941747572815534,0.07608695652173914,0.8313609467455622,0.7631208896636963,0.9862647612208,0.5544081330299377,0.5145057966550899,0.877392590045929,0.052078680104606735,0.9175824175824175,2.86877703666687,2.822442054748535,0.7419517636299133,0.7395554184913635,0.002396258059889078,0.15434424579143524,0.7744645476341248 +valid,C6_no_reconstruction,0.3,modality_T,0.10069156293222682,0.10069156293222682,"[0.30000000000000354, 0.0, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4615567765567765,"[0.30000000000000354, 0.5295054945054959, 0.5551648351648366]",0.16016483516483515,728,0.6002747252747253,0.5072452753711304,206,184,338,0.6941747572815534,0.10869565217391304,0.8106508875739645,0.7134279608726501,0.9437716197385886,0.5802155137062073,0.5034448120537669,0.8532750606536865,0.03428987732955387,0.9010989010989011,2.522357940673828,2.7913875579833984,0.6021409034729004,0.6017498970031738,0.0003910392988473177,0.17852939665317535,0.6432880759239197 +valid,C6_no_reconstruction,0.3,modality_A,0.056929076618108816,0.056929076618108816,"[0.0, 0.16961424063829394, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.3940018315018315,"[0.0, 0.6268406593406597, 0.5551648351648366]",0.0,728,0.6016483516483516,0.5199799259397838,206,184,338,0.6601941747572816,0.14673913043478262,0.8136094674556213,0.6972677707672119,0.9354649071831923,0.5884665250778198,0.502262777261492,0.8502750396728516,0.05053871460668333,0.8942307692307693,2.3925418853759766,2.7945220470428467,0.5653061270713806,0.565287172794342,1.8892978914664127e-05,0.19097265601158142,0.6088922619819641 +valid,C6_no_reconstruction,0.3,modality_V,0.05742852460922659,0.05742852460922659,"[0.0, 0.0, 0.1747019212866935]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.3925091575091575,"[0.0, 0.5295054945054959, 0.6480219780219784]",0.0,728,0.6016483516483516,0.5202926276965792,206,184,338,0.6650485436893204,0.14673913043478262,0.8106508875739645,0.6950706839561462,0.9329375510684372,0.5886265635490417,0.5026613926702285,0.8512023091316223,0.04803343514328474,0.8928571428571429,2.3890469074249268,2.7947487831115723,0.5633761286735535,0.5633586645126343,1.7425565602025017e-05,0.18487133085727692,0.6063473224639893 +valid,C6_no_reconstruction,0.3,modality_TA,0.15458357737606096,0.15458357737606096,"[0.30000000000000354, 0.1605656309459839, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4928388278388279,"[0.30000000000000354, 0.6233516483516487, 0.5551648351648366]",0.16804945054945056,728,0.5961538461538461,0.5065902931756591,206,184,338,0.6747572815533981,0.11956521739130435,0.8076923076923077,0.7176585793495178,0.953675783201997,0.5720103979110718,0.5028081156907162,0.8528652191162109,0.04308357228944589,0.9065934065934066,2.5387938022613525,2.7848329544067383,0.6116911768913269,0.6112551093101501,0.00043606478720903397,0.18370850384235382,0.6523889303207397 +valid,C6_no_reconstruction,0.3,modality_TV,0.15615011288036257,0.15615011288036257,"[0.30000000000000354, 0.0, 0.16870910916901322]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.49219780219780224,"[0.30000000000000354, 0.5295054945054959, 0.6470879120879123]",0.15978021978021978,728,0.5989010989010989,0.5037696301538707,206,184,338,0.6796116504854369,0.10326086956521739,0.8195266272189349,0.7069001197814941,0.928127293953164,0.5936524271965027,0.5018936786195256,0.8504840731620789,0.025441451714589048,0.9024725274725275,2.531923770904541,2.7796480655670166,0.6098533868789673,0.6094442009925842,0.00040915681165643036,0.17897632718086243,0.6502895951271057 +valid,C6_no_reconstruction,0.3,modality_AV,0.11349860023427828,0.11349860023427828,"[0.0, 0.17129020672936607, 0.17037755036349378]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.42464285714285716,"[0.0, 0.6267582417582415, 0.6471703296703297]",0.0,728,0.6016483516483516,0.5182741835926872,206,184,338,0.6650485436893204,0.14130434782608695,0.8136094674556213,0.6964878439903259,0.9337154612351619,0.5900610089302063,0.5018076874975448,0.8499292135238647,0.05077744950796222,0.8942307692307693,2.391453742980957,2.794156312942505,0.5646492838859558,0.5646297335624695,1.956168307515327e-05,0.18723323941230774,0.6082068681716919 +valid,C6_no_reconstruction,0.3,modality_TAV,0.2119442342526272,0.2119442342526272,"[0.30000000000000354, 0.1696415678704756, 0.16522858721492592]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.5246886446886447,"[0.30000000000000354, 0.6269230769230772, 0.6471428571428575]",0.2560989010989011,728,0.5906593406593407,0.4981992029683943,206,184,338,0.6504854368932039,0.11413043478260869,0.8136094674556213,0.7205085158348083,0.9581113675734635,0.5690979957580566,0.5030619860766475,0.8527392148971558,0.06198455565250837,0.9024725274725275,2.538750171661377,2.7812790870666504,0.6081514358520508,0.6076797842979431,0.0004716362163890153,0.17789407074451447,0.6499307155609131 +valid,C6_no_reconstruction,0.3,location_start_T,0.10069156293222682,0.10069156293222682,"[0.30000000000000354, 0.0, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4615567765567765,"[0.30000000000000354, 0.5295054945054959, 0.5551648351648366]",0.038543956043956044,728,0.6112637362637363,0.5306775590681346,206,184,338,0.6990291262135923,0.15760869565217392,0.8047337278106509,0.7143445014953613,0.9498935388843496,0.5800430178642273,0.5056824536966004,0.8579435348510742,0.04490233470614138,0.9024725274725275,2.523184299468994,2.798894166946411,0.6075230836868286,0.6072844862937927,0.0002385711995884776,0.15797023475170135,0.6490270495414734 +valid,C6_no_reconstruction,0.3,location_middle_T,0.10069156293222682,0.10069156293222682,"[0.30000000000000354, 0.0, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4615567765567765,"[0.30000000000000354, 0.5295054945054959, 0.5551648351648366]",0.1664835164835165,728,0.5975274725274725,0.5109217211763902,206,184,338,0.6650485436893204,0.13043478260869565,0.8106508875739645,0.7166770100593567,0.9623758359807074,0.5646106600761414,0.5029090848426836,0.8521662950515747,0.04724099634440391,0.907967032967033,2.5223612785339355,2.7795164585113525,0.6069275736808777,0.6065562963485718,0.0003712793695740402,0.18911533057689667,0.6484342217445374 +valid,C6_no_reconstruction,0.3,location_end_T,0.10069156293222682,0.10069156293222682,"[0.30000000000000354, 0.0, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4615567765567765,"[0.30000000000000354, 0.5295054945054959, 0.5551648351648366]",0.26755494505494504,728,0.6057692307692307,0.5134057664136272,206,184,338,0.6796116504854369,0.11956521739130435,0.8254437869822485,0.7019791007041931,0.9213564756086683,0.591676652431488,0.5023373148965153,0.8535845279693604,0.05263041577987619,0.9038461538461539,2.5804286003112793,2.7808032035827637,0.6165151000022888,0.6160123348236084,0.0005027762963436544,0.18569935858249664,0.6538811326026917 +valid,C6_no_reconstruction,0.3,span_long_T,0.10069156293222682,0.10069156293222682,"[0.30000000000000354, 0.0, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4615567765567765,"[0.30000000000000354, 0.5295054945054959, 0.5551648351648366]",0.16035714285714286,728,0.6098901098901099,0.5294628957004927,206,184,338,0.6699029126213593,0.16304347826086957,0.8165680473372781,0.7097036242485046,0.9483153200086865,0.5748408436775208,0.5031782962727658,0.8543016314506531,0.044348976441792066,0.9052197802197802,2.521730422973633,2.7866361141204834,0.6025817394256592,0.6021784543991089,0.00040321069536730647,0.18075978755950928,0.6433248519897461 +valid,C6_no_reconstruction,0.3,span_multi_short_T,0.10069156293222682,0.10069156293222682,"[0.30000000000000354, 0.0, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4615567765567765,"[0.30000000000000354, 0.5295054945054959, 0.5551648351648366]",0.1539010989010989,728,0.6016483516483516,0.5183272955146325,206,184,338,0.6796116504854369,0.14130434782608695,0.8047337278106509,0.7004514336585999,0.9246789993870027,0.5944291949272156,0.5020953028800323,0.8525019884109497,0.0363109969830775,0.9038461538461539,2.5059139728546143,2.7810463905334473,0.597016453742981,0.5967524647712708,0.0002640053862705827,0.17371053993701935,0.6377541422843933 +valid,C6_no_reconstruction,0.3,location_start_A,0.2003851185549212,0.2003851185549212,"[0.0, 0.5970265414088254, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.44360805860805863,"[0.0, 0.7756593406593403, 0.5551648351648366]",0.0,728,0.5934065934065934,0.5082272451336022,206,184,338,0.6504854368932039,0.13043478260869565,0.8106508875739645,0.7033993005752563,0.9406286486684808,0.5856781601905823,0.5035526660945809,0.8520424962043762,0.0598775944211981,0.8956043956043956,2.394436836242676,2.796653985977173,0.5659434795379639,0.565919041633606,2.436909926473163e-05,0.20161262154579163,0.6099733710289001 +valid,C6_no_reconstruction,0.3,location_middle_A,0.07214529279070561,0.07214529279070561,"[0.0, 0.21494936821846267, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.40606227106227105,"[0.0, 0.663021978021981, 0.5551648351648366]",0.0,728,0.6002747252747253,0.5156745016208303,206,184,338,0.6650485436893204,0.1358695652173913,0.8136094674556213,0.7011321783065796,0.9369817572927718,0.5883570909500122,0.5025589470420596,0.8506944179534912,0.055571205504647996,0.8956043956043956,2.391619920730591,2.7938361167907715,0.5651046633720398,0.5650851130485535,1.9529172277543694e-05,0.19096404314041138,0.6089015007019043 +valid,C6_no_reconstruction,0.3,location_end_A,0.012218129834169183,0.012218129834169183,"[0.0, 0.03640264232185844, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.37236263736263736,"[0.0, 0.5619230769230764, 0.5551648351648366]",0.0,728,0.6002747252747253,0.5176057623064478,206,184,338,0.6650485436893204,0.14130434782608695,0.8106508875739645,0.6970194578170776,0.934360747723024,0.5887131690979004,0.5021556373648194,0.8502863645553589,0.04933752872786681,0.8928571428571429,2.391188383102417,2.7947163581848145,0.5640913844108582,0.5640739798545837,1.7368145563523285e-05,0.1892002820968628,0.6074897050857544 +valid,C6_no_reconstruction,0.3,span_long_A,0.10046375561263678,0.10046375561263678,"[0.0, 0.29932127187336466, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4085531135531135,"[0.0, 0.6704945054945051, 0.5551648351648366]",0.0,728,0.5947802197802198,0.5082131513799591,206,184,338,0.6601941747572816,0.125,0.8106508875739645,0.7017729878425598,0.9374224948634621,0.5876383185386658,0.5023087103256844,0.8501863479614258,0.058612946666531524,0.8942307692307693,2.396409273147583,2.7930376529693604,0.5665058493614197,0.5664870142936707,1.885039637272712e-05,0.19332954287528992,0.6101901531219482 +valid,C6_no_reconstruction,0.3,span_multi_short_A,0.10046375561263678,0.10046375561263678,"[0.0, 0.29932127187336466, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4085531135531135,"[0.0, 0.6704945054945051, 0.5551648351648366]",0.0,728,0.5989010989010989,0.5146589396436304,206,184,338,0.6601941747572816,0.1358695652173913,0.8136094674556213,0.6984926462173462,0.9356634907523048,0.5883760452270508,0.5029308312710891,0.851334810256958,0.052293249825527396,0.8956043956043956,2.39396595954895,2.7952260971069336,0.5654669404029846,0.5654484629631042,1.8476954210200347e-05,0.19385632872581482,0.6090364456176758 +valid,C6_no_reconstruction,0.3,location_start_V,0.19317645467012823,0.19317645467012823,"[0.0, 0.0, 0.5876574055813588]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.43891941391941397,"[0.0, 0.5295054945054959, 0.7872527472527471]",0.0,728,0.603021978021978,0.5225492046712977,206,184,338,0.6650485436893204,0.15217391304347827,0.8106508875739645,0.6947979927062988,0.933550462557192,0.588141918182373,0.5028195638944822,0.851442277431488,0.04989989073230672,0.8956043956043956,2.38973069190979,2.795905590057373,0.5640730261802673,0.5640519857406616,2.0945210053469054e-05,0.18194244801998138,0.6070156097412109 +valid,C6_no_reconstruction,0.3,location_middle_V,0.07025012492138243,0.07025012492138243,"[0.0, 0.0, 0.21370620049716513]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.40370879120879116,"[0.0, 0.5295054945054959, 0.6816208791208818]",0.0,728,0.6002747252747253,0.517448436487664,206,184,338,0.6650485436893204,0.14130434782608695,0.8106508875739645,0.6951202750205994,0.9325246075919369,0.5881863236427307,0.502242640489154,0.850700855255127,0.04859642058119668,0.8914835164835165,2.383753776550293,2.794520616531372,0.5613689422607422,0.561350405216217,1.8511205780669115e-05,0.18213771283626556,0.6040604710578918 +valid,C6_no_reconstruction,0.3,location_end_V,0.012031832650855376,0.012031832650855376,"[0.0, 0.0, 0.03660174617069467]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.37173992673992673,"[0.0, 0.5295054945054959, 0.5857142857142853]",0.0,728,0.6002747252747253,0.5194301869893779,206,184,338,0.6650485436893204,0.14673913043478262,0.8076923076923077,0.6964459419250488,0.933083718134694,0.5879771113395691,0.5025025470690564,0.8508979082107544,0.04997084781036273,0.8928571428571429,2.3882768154144287,2.794952392578125,0.5625650882720947,0.5625476837158203,1.7330805349047296e-05,0.18710170686244965,0.6053875088691711 +valid,C6_no_reconstruction,0.3,span_long_V,0.09768688768578579,0.09768688768578579,"[0.0, 0.0, 0.29717091078607255]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4059615384615385,"[0.0, 0.5295054945054959, 0.6883791208791201]",0.0,728,0.6057692307692307,0.5261936174158057,206,184,338,0.6650485436893204,0.15760869565217392,0.8136094674556213,0.6936109066009521,0.9329646077572813,0.5887360572814941,0.5022610422456435,0.8506226539611816,0.04463222209405111,0.8942307692307693,2.3913328647613525,2.7938382625579834,0.5643920302391052,0.5643734931945801,1.8615815861267038e-05,0.18318015336990356,0.6073679327964783 +valid,C6_no_reconstruction,0.3,span_multi_short_V,0.09768688768578579,0.09768688768578579,"[0.0, 0.0, 0.29717091078607255]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4059615384615385,"[0.0, 0.5295054945054959, 0.6883791208791201]",0.0,728,0.6043956043956044,0.5255313251577809,206,184,338,0.6650485436893204,0.15760869565217392,0.8106508875739645,0.6943562030792236,0.933189112868246,0.5887292623519897,0.5023280147571799,0.8506815433502197,0.04691269924188708,0.8956043956043956,2.3929548263549805,2.7941787242889404,0.5650855898857117,0.5650670528411865,1.8544951672083698e-05,0.18406692147254944,0.608128547668457 +valid,C6_no_reconstruction,0.3,synchrony_sync,0.21691507013507422,0.21691507013507422,"[0.30000000000000354, 0.1761774211270993, 0.17367689276640616]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.5254212454212455,"[0.30000000000000354, 0.6281043956043952, 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0.6020329670329673]",0.1646978021978022,728,0.6002747252747253,0.5051711057426024,206,184,338,0.6990291262135923,0.10326086956521739,0.8106508875739645,0.7045269012451172,0.9206071314013177,0.6023101210594177,0.5010927638451848,0.8496101498603821,0.04557234896244584,0.8983516483516484,2.519791603088379,2.78405499458313,0.6024143695831299,0.6020171642303467,0.00039714129525236785,0.17674387991428375,0.6438475251197815 +valid,C6_no_reconstruction,0.3,synchrony_async,0.20945741949355928,0.20945741949355928,"[0.30000000000000354, 0.16659314748477386, 0.16077606102751021]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.521437728937729,"[0.30000000000000354, 0.6226923076923089, 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0.6416208791208796]",0.16925824175824175,728,0.6098901098901099,0.5506538840736852,206,184,338,0.6213592233009708,0.2391304347826087,0.8047337278106509,0.6900760531425476,0.9243771169869076,0.5824931859970093,0.500872340647094,0.8514899015426636,0.058483285358646414,0.8942307692307693,2.6157314777374268,2.7853846549987793,0.5903934240341187,0.5894365310668945,0.0009568625828251243,0.2133188396692276,0.6736868619918823 +valid,C7_distill,0.0,none,0.0,0.0,"[0.0, 0.0, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.0,728,0.5906593406593407,0.5243846543289639,206,184,338,0.6601941747572816,0.18478260869565216,0.7692307692307693,0.6742965579032898,0.8981109357355169,0.6013434529304504,0.503583581952715,0.8561596870422363,0.04524039550796968,0.8667582417582418,2.3017966747283936,2.8153645992279053,0.5134543776512146,0.513435423374176,1.8957358406623825e-05,0.1675664335489273,0.5485575199127197 +valid,C7_distill,0.1,single,0.033502520154928106,0.033502520154928106,"[0.03337912087912098, 0.03439424419379373, 0.03271803147679828]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.38305860805860803,"[0.03337912087912098, 0.5451923076923084, 0.5706043956043971]",0.0185989010989011,728,0.592032967032967,0.524562777336849,206,184,338,0.6504854368932039,0.18478260869565216,0.7781065088757396,0.6799377799034119,0.904535052116391,0.595530092716217,0.5040805847483587,0.8567439317703247,0.0377316278415722,0.8653846153846154,2.3125691413879395,2.8164291381835938,0.5180022120475769,0.5179587006568909,4.349577648099512e-05,0.1716255098581314,0.5530665516853333 +valid,C7_distill,0.1,sync,0.057409428685793254,0.057409428685793254,"[0.0820054945054953, 0.04460700701510746, 0.04536767140601303]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4056593406593407,"[0.0820054945054953, 0.5546703296703304, 0.5803021978021985]",0.056428571428571425,728,0.5906593406593407,0.5217284909062792,206,184,338,0.6650485436893204,0.17391304347826086,0.772189349112426,0.6786344647407532,0.902233265639928,0.5993814468383789,0.5044886776661361,0.8569976687431335,0.037790007848333536,0.8736263736263736,2.326866626739502,2.811084508895874,0.5238932371139526,0.5238164067268372,7.682030991418287e-05,0.17216527462005615,0.5593820810317993 +valid,C7_distill,0.1,partial,0.0529758085036651,0.0529758085036651,"[0.08420329670329753, 0.03822459277521008, 0.03615291038442729]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.40424908424908423,"[0.08420329670329753, 0.5525274725274731, 0.5760164835164839]",0.043351648351648356,728,0.5906593406593407,0.5215462508144882,206,184,338,0.6650485436893204,0.17391304347826086,0.772189349112426,0.6799012422561646,0.9074751366606286,0.5955010652542114,0.5039451825095217,0.8568593263626099,0.03516314088643252,0.8667582417582418,2.3264684677124023,2.8142082691192627,0.5246660709381104,0.5245866775512695,7.937666669022292e-05,0.1706320196390152,0.5601410269737244 +valid,C7_distill,0.1,async,0.055965730621434076,0.055965730621434076,"[0.08420329670329753, 0.04282041186781863, 0.04055597458361638]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4039468864468865,"[0.08420329670329753, 0.5516208791208798, 0.5760164835164845]",0.05142857142857143,728,0.5865384615384616,0.5152940636105828,206,184,338,0.6553398058252428,0.16304347826086957,0.7751479289940828,0.6802725195884705,0.9020681579640761,0.5975505113601685,0.5053950825688477,0.8590822219848633,0.0516676063147875,0.8653846153846154,2.3259968757629395,2.814605951309204,0.5244093537330627,0.5243479609489441,6.138626486063004e-05,0.17523297667503357,0.5593441724777222 +valid,C7_distill,0.3,single,0.10077529965039936,0.10077529965039936,"[0.1063186813186808, 0.09791175417598566, 0.0980390854159867]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4273534798534799,"[0.1063186813186808, 0.573956043956045, 0.601785714285715]",0.05964285714285714,728,0.5975274725274725,0.5284759249629695,206,184,338,0.6699029126213593,0.1793478260869565,0.7810650887573964,0.6799160242080688,0.9019475620341081,0.6005235910415649,0.5040227825030493,0.8561485409736633,0.029878812749962246,0.8736263736263736,2.3430569171905518,2.811501979827881,0.5309827327728271,0.5308508276939392,0.00013184220006223768,0.17294879257678986,0.5663501620292664 +valid,C7_distill,0.3,sync,0.18366496008611768,0.18366496008611768,"[0.2554945054945073, 0.14791849924316752, 0.1468227643446891]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.5004487179487179,"[0.2554945054945073, 0.6123626373626374, 0.6334890109890104]",0.18217032967032967,728,0.5865384615384616,0.5119109142364956,206,184,338,0.6601941747572816,0.15217391304347827,0.7781065088757396,0.6936126947402954,0.9144702882064513,0.5927407145500183,0.5023867696732438,0.8530648946762085,0.059053080176914116,0.8818681318681318,2.4043869972229004,2.8020341396331787,0.5559917092323303,0.5556297898292542,0.0003619274648372084,0.18291808664798737,0.5917712450027466 +valid,C7_distill,0.3,partial,0.14816552304516878,0.14816552304516878,"[0.25920329670329867, 0.10412618442414666, 0.07975758376464556]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.486978021978022,"[0.25920329670329867, 0.5950274725274726, 0.6067032967032975]",0.14230769230769233,728,0.6002747252747253,0.5253127418657062,206,184,338,0.6747572815533981,0.16304347826086957,0.7928994082840237,0.692629873752594,0.9282297197341056,0.5833005905151367,0.5030428694635393,0.8539884686470032,0.0431146841127794,0.8887362637362637,2.395695686340332,2.802818536758423,0.5562655925750732,0.555915355682373,0.0003502403851598501,0.18059484660625458,0.5924844145774841 +valid,C7_distill,0.3,async,0.17500872720325933,0.17500872720325933,"[0.2542582417582435, 0.14028985682217077, 0.12954125320803533]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4937454212454212,"[0.2542582417582435, 0.6036538461538465, 0.6233241758241765]",0.1337087912087912,728,0.5851648351648352,0.504594820384294,206,184,338,0.6553398058252428,0.13043478260869565,0.7899408284023669,0.6937493085861206,0.9149900767304183,0.5920988321304321,0.5086052057769718,0.8631793260574341,0.046517487738158655,0.8818681318681318,2.3871774673461914,2.815697193145752,0.5540140271186829,0.5537383556365967,0.0002756629837676883,0.18973030149936676,0.5898513197898865 +valid,C7_distill,0.5,single,0.16685149244608855,0.16685149244608855,"[0.1620879120879121, 0.1638041073804625, 0.1748267839307003]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4674908424908425,"[0.1620879120879121, 0.6050549450549455, 0.6353296703296704]",0.08684065934065933,728,0.5879120879120879,0.5207954930594249,206,184,338,0.6601941747572816,0.17391304347826086,0.7692307692307693,0.6808550357818604,0.9004912082321309,0.6040370464324951,0.5037570498504819,0.856528639793396,0.04056941406739934,0.8777472527472527,2.3727269172668457,2.809053897857666,0.5451414585113525,0.5448626279830933,0.0002788564015645534,0.17595316469669342,0.581145167350769 +valid,C7_distill,0.5,sync,0.330209128768783,0.330209128768783,"[0.42032967032967034, 0.28200237109380377, 0.2874135682232839]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.6007692307692307,"[0.42032967032967034, 0.678736263736264, 0.7032417582417585]",0.3127747252747253,728,0.5989010989010989,0.5206919745351754,206,184,338,0.6650485436893204,0.15217391304347827,0.8017751479289941,0.7106931209564209,0.936733027485394,0.5825034976005554,0.5033342544337462,0.8545408248901367,0.03343959115854986,0.8846153846153846,2.5121231079101562,2.8090293407440186,0.603930652141571,0.6029177904129028,0.0010129117872565985,0.19823765754699707,0.6405313611030579 +valid,C7_distill,0.5,partial,0.23623170531479354,0.23623170531479354,"[0.42032967032967034, 0.17341613672677042, 0.11239778582145649]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.5651465201465201,"[0.42032967032967034, 0.6398351648351651, 0.635274725274725]",0.24862637362637363,728,0.6002747252747253,0.523034287265772,206,184,338,0.6601941747572816,0.15760869565217392,0.8047337278106509,0.7164063453674316,0.9644542942835725,0.5545317530632019,0.5072184023803163,0.86138916015625,0.024610065251261345,0.8832417582417582,2.4992282390594482,2.8150038719177246,0.5974858999252319,0.5966101288795471,0.0008757879259064794,0.1932077705860138,0.6333432197570801 +valid,C7_distill,0.5,async,0.3120007279622296,0.3120007279622296,"[0.4065934065934066, 0.2579016785179102, 0.27065519914311004]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.5900000000000001,"[0.4065934065934066, 0.6680769230769213, 0.6953296703296687]",0.23804945054945056,728,0.5906593406593407,0.5076204822568879,206,184,338,0.6456310679611651,0.1358695652173913,0.8047337278106509,0.7036042213439941,0.9248570202821017,0.5872247815132141,0.5094637264092267,0.8675886988639832,0.02833213894576817,0.8736263736263736,2.4718291759490967,2.8242197036743164,0.5893922448158264,0.5887660384178162,0.0006262024398893118,0.1995006948709488,0.6252672076225281 +valid,C7_distill,0.7,single,0.23221469003340273,0.23221469003340273,"[0.22115384615384592, 0.2612316954439274, 0.21388076914343795]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.5095421245421247,"[0.22115384615384592, 0.65239010989011, 0.655082417582419]",0.1204945054945055,728,0.5865384615384616,0.5153735153735154,206,184,338,0.6601941747572816,0.16304347826086957,0.772189349112426,0.7121081352233887,0.9321715243764459,0.5826635360717773,0.5069874563972685,0.8619224429130554,0.03803755969300375,0.885989010989011,2.446012496948242,2.824169397354126,0.5768414735794067,0.5761287808418274,0.0007127287681214511,0.1800328493118286,0.613429844379425 +valid,C7_distill,0.7,sync,0.505389528795785,0.505389528795785,"[0.5807692307692247, 0.47634612944176064, 0.4580784091507095]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.7128296703296704,"[0.5807692307692247, 0.7772252747252746, 0.7804945054945048]",0.44958791208791204,728,0.5865384615384616,0.4850243746615983,206,184,338,0.6407766990291263,0.08152173913043478,0.8284023668639053,0.7548737525939941,0.9805789596807174,0.5589423775672913,0.5145571477539002,0.8716524839401245,0.04097283811687115,0.8983516483516484,2.687494993209839,2.8269259929656982,0.6810379028320312,0.6790910363197327,0.0019468595273792744,0.2271478921175003,0.7173656225204468 +valid,C7_distill,0.7,partial,0.39062347526393004,0.39062347526393004,"[0.5788461538461478, 0.31403194162971376, 0.27664384900565697]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.6740018315018315,"[0.5788461538461478, 0.7185989010989093, 0.7245604395604472]",0.40997252747252755,728,0.5892857142857143,0.48734234269197635,206,184,338,0.6504854368932039,0.08695652173913043,0.8254437869822485,0.7626818418502808,0.9909259555592903,0.5498490929603577,0.5120872952521791,0.8708199262619019,0.04974212882282969,0.8887362637362637,2.681598663330078,2.828535556793213,0.6761065721511841,0.6740971803665161,0.0020094383507966995,0.235586017370224,0.712878406047821 +valid,C7_distill,0.7,async,0.48300135283868606,0.48300135283868606,"[0.5932692307692244, 0.43288957390738114, 0.42157969775951804]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.7052930402930403,"[0.5932692307692244, 0.7602747252747305, 0.7623351648351689]",0.40626373626373624,728,0.5810439560439561,0.48348889101970594,206,184,338,0.6067961165048543,0.09239130434782608,0.8313609467455622,0.7557876110076904,0.9806256415691429,0.5574042201042175,0.5162316712011122,0.8751515746116638,0.04732670471235945,0.9024725274725275,2.6759588718414307,2.831348419189453,0.6762083172798157,0.6746838092803955,0.0015245265094563365,0.23389217257499695,0.7135176062583923 +valid,C7_distill,0.3,modality_T,0.10069156293222682,0.10069156293222682,"[0.30000000000000354, 0.0, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4615567765567765,"[0.30000000000000354, 0.5295054945054959, 0.5551648351648366]",0.16016483516483515,728,0.5947802197802198,0.5192083738317917,206,184,338,0.6747572815533981,0.15217391304347827,0.7869822485207101,0.6946868300437927,0.9302554599547397,0.5827596783638,0.5069522216263266,0.8596484065055847,0.03428886360028289,0.8804945054945055,2.4262423515319824,2.814871072769165,0.5677874088287354,0.5673661828041077,0.0004211732011754066,0.18909278512001038,0.6041210889816284 +valid,C7_distill,0.3,modality_A,0.056929076618108816,0.056929076618108816,"[0.0, 0.16961424063829394, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.3940018315018315,"[0.0, 0.6268406593406597, 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0.6480219780219784]",0.0,728,0.5906593406593407,0.5245944271283881,206,184,338,0.6601941747572816,0.18478260869565216,0.7692307692307693,0.6733604073524475,0.8973722694271473,0.6015283465385437,0.503326641970764,0.8558681607246399,0.0466965139730946,0.8667582417582418,2.2987406253814697,2.814777374267578,0.5118309259414673,0.5118123888969421,1.8533111870056018e-05,0.1656036078929901,0.5469996929168701 +valid,C7_distill,0.3,modality_TA,0.15458357737606096,0.15458357737606096,"[0.30000000000000354, 0.1605656309459839, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4928388278388279,"[0.30000000000000354, 0.6233516483516487, 0.5551648351648366]",0.16804945054945056,728,0.5947802197802198,0.5199177365844032,206,184,338,0.6844660194174758,0.15760869565217392,0.7781065088757396,0.7061866521835327,0.9429765323295655,0.5715773105621338,0.5059108529912475,0.8592308759689331,0.039184104241840136,0.8901098901098901,2.433919668197632,2.806962728500366,0.5703361630439758,0.5698554515838623,0.0004807047953363508,0.18072189390659332,0.6063434481620789 +valid,C7_distill,0.3,modality_TV,0.15615011288036257,0.15615011288036257,"[0.30000000000000354, 0.0, 0.16870910916901322]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.49219780219780224,"[0.30000000000000354, 0.5295054945054959, 0.6470879120879123]",0.15978021978021978,728,0.5906593406593407,0.5183560679594418,206,184,338,0.6699029126213593,0.16304347826086957,0.7751479289940828,0.6997418403625488,0.9291589019576403,0.5814394354820251,0.5096385877401528,0.8630898594856262,0.04774039410627805,0.8818681318681318,2.4235928058624268,2.805420160293579,0.567852795124054,0.5674269795417786,0.00042586278868839145,0.18879662454128265,0.6030336618423462 +valid,C7_distill,0.3,modality_AV,0.11349860023427828,0.11349860023427828,"[0.0, 0.17129020672936607, 0.17037755036349378]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.42464285714285716,"[0.0, 0.6267582417582415, 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0.6471428571428575]",0.2560989010989011,728,0.5879120879120879,0.5147849485115562,206,184,338,0.6650485436893204,0.15760869565217392,0.7751479289940828,0.6974321007728577,0.9251677657397854,0.5849357843399048,0.5067837113199093,0.8611478805541992,0.038866016890976456,0.885989010989011,2.4201998710632324,2.808198928833008,0.5623499155044556,0.561913788318634,0.00043617855408228934,0.18205061554908752,0.5987576246261597 +valid,C7_distill,0.3,location_start_T,0.10069156293222682,0.10069156293222682,"[0.30000000000000354, 0.0, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4615567765567765,"[0.30000000000000354, 0.5295054945054959, 0.5551648351648366]",0.038543956043956044,728,0.5865384615384616,0.511511062493729,206,184,338,0.6553398058252428,0.15217391304347827,0.7810650887573964,0.6997548937797546,0.9341963096382427,0.573676586151123,0.5137023347791598,0.8712642788887024,0.04775850511677974,0.875,2.343264102935791,2.83622145652771,0.5359293818473816,0.5357721447944641,0.00015724972763564438,0.18357430398464203,0.5723201632499695 +valid,C7_distill,0.3,location_middle_T,0.10069156293222682,0.10069156293222682,"[0.30000000000000354, 0.0, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4615567765567765,"[0.30000000000000354, 0.5295054945054959, 0.5551648351648366]",0.1664835164835165,728,0.5892857142857143,0.5171666262881364,206,184,338,0.6601941747572816,0.16304347826086957,0.7781065088757396,0.6943658590316772,0.9291662469928518,0.5807386040687561,0.5030921651584934,0.8551530241966248,0.04770183243921825,0.8832417582417582,2.4160783290863037,2.7976419925689697,0.559045672416687,0.558775782585144,0.00026987111777998507,0.18065838515758514,0.5950493216514587 +valid,C7_distill,0.3,location_end_T,0.10069156293222682,0.10069156293222682,"[0.30000000000000354, 0.0, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4615567765567765,"[0.30000000000000354, 0.5295054945054959, 0.5551648351648366]",0.26755494505494504,728,0.592032967032967,0.508251376876906,206,184,338,0.6310679611650486,0.1358695652173913,0.8165680473372781,0.7089433073997498,0.9328048437369824,0.5851706862449646,0.5064729919161349,0.8585339784622192,0.041199440566393034,0.8887362637362637,2.4759044647216797,2.801145553588867,0.5943931341171265,0.5938383936882019,0.0005547591135837138,0.2306724637746811,0.6314458847045898 +valid,C7_distill,0.3,span_long_T,0.10069156293222682,0.10069156293222682,"[0.30000000000000354, 0.0, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4615567765567765,"[0.30000000000000354, 0.5295054945054959, 0.5551648351648366]",0.16035714285714286,728,0.592032967032967,0.5125667684491214,206,184,338,0.6699029126213593,0.14130434782608695,0.7899408284023669,0.7017372250556946,0.9262595570800953,0.5866219401359558,0.5065717080471845,0.8593159914016724,0.05494726232283715,0.8846153846153846,2.421283483505249,2.8130838871002197,0.563542366027832,0.5631558895111084,0.00038641667924821377,0.18627513945102692,0.6000488996505737 +valid,C7_distill,0.3,span_multi_short_T,0.10069156293222682,0.10069156293222682,"[0.30000000000000354, 0.0, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4615567765567765,"[0.30000000000000354, 0.5295054945054959, 0.5551648351648366]",0.1539010989010989,728,0.592032967032967,0.5111374501205009,206,184,338,0.6553398058252428,0.14130434782608695,0.7988165680473372,0.6955581307411194,0.9115187307056035,0.6000438332557678,0.5055732554112994,0.8575285077095032,0.05586145564422502,0.8887362637362637,2.438910961151123,2.800104856491089,0.572319507598877,0.5719878077507019,0.0003317195805720985,0.19666603207588196,0.6082754731178284 +valid,C7_distill,0.3,location_start_A,0.2003851185549212,0.2003851185549212,"[0.0, 0.5970265414088254, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.44360805860805863,"[0.0, 0.7756593406593403, 0.5551648351648366]",0.0,728,0.5865384615384616,0.5217154051385475,206,184,338,0.6601941747572816,0.18478260869565216,0.7603550295857988,0.6686100959777832,0.8884693627643341,0.6051310896873474,0.5023010150293789,0.8545963168144226,0.04969261050388053,0.8681318681318682,2.2832772731781006,2.8147871494293213,0.5055178999900818,0.5055000185966492,1.7871941963676363e-05,0.15444302558898926,0.5398032069206238 +valid,C7_distill,0.3,location_middle_A,0.07214529279070561,0.07214529279070561,"[0.0, 0.21494936821846267, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.40606227106227105,"[0.0, 0.663021978021981, 0.5551648351648366]",0.0,728,0.5934065934065934,0.5279880392243421,206,184,338,0.6650485436893204,0.19021739130434784,0.7692307692307693,0.6700723171234131,0.8987304541593942,0.5992106199264526,0.503247621789293,0.855986475944519,0.04594268039851397,0.8653846153846154,2.2885847091674805,2.816908597946167,0.508356511592865,0.508338451385498,1.8079072106047533e-05,0.161086767911911,0.5431526899337769 +valid,C7_distill,0.3,location_end_A,0.012218129834169183,0.012218129834169183,"[0.0, 0.03640264232185844, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.37236263736263736,"[0.0, 0.5619230769230764, 0.5551648351648366]",0.0,728,0.592032967032967,0.5257562617604755,206,184,338,0.6650485436893204,0.18478260869565216,0.7692307692307693,0.6709986329078674,0.8935063583561916,0.6050497889518738,0.5028353669224368,0.8551759719848633,0.04388814996723293,0.8653846153846154,2.2974698543548584,2.8149588108062744,0.5109065175056458,0.5108893513679504,1.7227646821993403e-05,0.1641194075345993,0.5460053086280823 +valid,C7_distill,0.3,span_long_A,0.10046375561263678,0.10046375561263678,"[0.0, 0.29932127187336466, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4085531135531135,"[0.0, 0.6704945054945051, 0.5551648351648366]",0.0,728,0.5892857142857143,0.5250774567847739,206,184,338,0.6601941747572816,0.19021739130434784,0.7633136094674556,0.6705284714698792,0.8910990340256616,0.6059636473655701,0.502821720235537,0.855269193649292,0.0458717557018275,0.864010989010989,2.2936019897460938,2.8151185512542725,0.5101895928382874,0.5101726055145264,1.701211294857785e-05,0.16295571625232697,0.5450270175933838 +valid,C7_distill,0.3,span_multi_short_A,0.10046375561263678,0.10046375561263678,"[0.0, 0.29932127187336466, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4085531135531135,"[0.0, 0.6704945054945051, 0.5551648351648366]",0.0,728,0.592032967032967,0.5270259629279203,206,184,338,0.6601941747572816,0.19021739130434784,0.7692307692307693,0.6682427525520325,0.8897555943093743,0.6068456768989563,0.5028943536389162,0.855317234992981,0.04619469829313048,0.864010989010989,2.293999671936035,2.814598321914673,0.510107696056366,0.5100902318954468,1.740449260978494e-05,0.16371870040893555,0.5448917746543884 +valid,C7_distill,0.3,location_start_V,0.19317645467012823,0.19317645467012823,"[0.0, 0.0, 0.5876574055813588]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.43891941391941397,"[0.0, 0.5295054945054959, 0.7872527472527471]",0.0,728,0.5851648351648352,0.5226160970625854,206,184,338,0.6553398058252428,0.19021739130434784,0.757396449704142,0.6726104021072388,0.8949409113190966,0.6025909185409546,0.5036780089424414,0.8566752076148987,0.05317085170811349,0.8667582417582418,2.2943263053894043,2.815093994140625,0.5112558007240295,0.5112342238426208,2.1615955120068975e-05,0.1667356938123703,0.5462139844894409 +valid,C7_distill,0.3,location_middle_V,0.07025012492138243,0.07025012492138243,"[0.0, 0.0, 0.21370620049716513]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.40370879120879116,"[0.0, 0.5295054945054959, 0.6816208791208818]",0.0,728,0.5879120879120879,0.5222388556015782,206,184,338,0.6553398058252428,0.18478260869565216,0.7662721893491125,0.6742833256721497,0.8969830889814144,0.6010740995407104,0.5035280313749488,0.8561091423034668,0.05164697532961658,0.8653846153846154,2.2948451042175293,2.8160221576690674,0.5102893114089966,0.5102692246437073,2.0065011995029636e-05,0.1677747517824173,0.5452736616134644 +valid,C7_distill,0.3,location_end_V,0.012031832650855376,0.012031832650855376,"[0.0, 0.0, 0.03660174617069467]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.37173992673992673,"[0.0, 0.5295054945054959, 0.5857142857142853]",0.0,728,0.5892857142857143,0.5217744545289903,206,184,338,0.6601941747572816,0.1793478260869565,0.7692307692307693,0.6765652894973755,0.9007022012399275,0.5992234945297241,0.5033987469253637,0.8557796478271484,0.049610940268733986,0.8667582417582418,2.301994800567627,2.815256357192993,0.5130425095558167,0.5130250453948975,1.742690074024722e-05,0.1670445203781128,0.5482271909713745 +valid,C7_distill,0.3,span_long_V,0.09768688768578579,0.09768688768578579,"[0.0, 0.0, 0.29717091078607255]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4059615384615385,"[0.0, 0.5295054945054959, 0.6883791208791201]",0.0,728,0.5892857142857143,0.5263450347681772,206,184,338,0.6601941747572816,0.1956521739130435,0.7603550295857988,0.673602283000946,0.8982034461286371,0.6009500622749329,0.5033803599930139,0.855807900428772,0.05162727267860055,0.8667582417582418,2.299124240875244,2.8144423961639404,0.5121555328369141,0.512135922908783,1.9628940208349377e-05,0.16458816826343536,0.5473587512969971 +valid,C7_distill,0.3,span_multi_short_V,0.09768688768578579,0.09768688768578579,"[0.0, 0.0, 0.29717091078607255]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4059615384615385,"[0.0, 0.5295054945054959, 0.6883791208791201]",0.0,728,0.5892857142857143,0.5265223800406479,206,184,338,0.6601941747572816,0.1956521739130435,0.7603550295857988,0.6738946437835693,0.8984012430587518,0.6009039282798767,0.5030749886826039,0.8554898500442505,0.045650532530559285,0.8667582417582418,2.2997660636901855,2.814085006713867,0.5124813318252563,0.5124618411064148,1.948168210219592e-05,0.16359977424144745,0.5477859377861023 +valid,C7_distill,0.3,synchrony_sync,0.21691507013507422,0.21691507013507422,"[0.30000000000000354, 0.1761774211270993, 0.17367689276640616]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.5254212454212455,"[0.30000000000000354, 0.6281043956043952, 0.6481593406593403]",0.25337912087912084,728,0.5892857142857143,0.5107037624967199,206,184,338,0.6796116504854369,0.1358695652173913,0.7810650887573964,0.6894748210906982,0.9127572676767112,0.5965097546577454,0.5036485117526205,0.8555349707603455,0.040513869415927724,0.8846153846153846,2.4210782051086426,2.801400899887085,0.5658730268478394,0.5654641389846802,0.00040890619857236743,0.17885522544384003,0.6018058657646179 +valid,C7_distill,0.3,synchrony_partial,0.1606943112281871,0.1606943112281871,"[0.30000000000000354, 0.1155318929339427, 0.06457046703790681]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.5020238095238095,"[0.30000000000000354, 0.604038461538462, 0.6020329670329673]",0.1646978021978022,728,0.5989010989010989,0.5196887636246904,206,184,338,0.6844660194174758,0.14673913043478262,0.7928994082840237,0.6934294104576111,0.9126398802368259,0.5965877175331116,0.5046841133682132,0.8571012616157532,0.038113306839387504,0.8832417582417582,2.408038854598999,2.8127458095550537,0.5579918026924133,0.5575881600379944,0.00040362062281928957,0.17786897718906403,0.5940291285514832 +valid,C7_distill,0.3,synchrony_async,0.20945741949355928,0.20945741949355928,"[0.30000000000000354, 0.16659314748477386, 0.16077606102751021]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.521437728937729,"[0.30000000000000354, 0.6226923076923089, 0.6416208791208796]",0.16925824175824175,728,0.6016483516483516,0.5241910459760358,206,184,338,0.6747572815533981,0.15217391304347827,0.8017751479289941,0.6821228861808777,0.8991478143812776,0.6061596274375916,0.5043131920820114,0.855997622013092,0.03154694542780026,0.8846153846153846,2.4020659923553467,2.801358222961426,0.5562353730201721,0.5558819770812988,0.0003533773124217987,0.1903383880853653,0.5924426913261414 +valid,C7_group,0.0,none,0.0,0.0,"[0.0, 0.0, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.0,728,0.6085164835164835,0.5116842947005743,206,184,338,0.6747572815533981,0.11413043478260869,0.8372781065088757,0.6860519051551819,0.9252575709031406,0.5912197232246399,0.5028534301325684,0.8551200032234192,0.0515357157276882,0.8928571428571429,2.44551157951355,2.783597946166992,0.6084316968917847,0.6084202527999878,1.1523725333972834e-05,0.1267874389886856,0.619817316532135 +valid,C7_group,0.1,single,0.033502520154928106,0.033502520154928106,"[0.03337912087912098, 0.03439424419379373, 0.03271803147679828]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.38305860805860803,"[0.03337912087912098, 0.5451923076923084, 0.5706043956043971]",0.0185989010989011,728,0.6085164835164835,0.5099890852385828,206,184,338,0.6747572815533981,0.10869565217391304,0.8402366863905325,0.6862916946411133,0.9258597296434946,0.5910477042198181,0.5033288700438524,0.8553639650344849,0.05723805185202714,0.8942307692307693,2.463982105255127,2.784114122390747,0.6153778433799744,0.6153483390808105,2.9492242902051657e-05,0.13325057923793793,0.6267867684364319 +valid,C7_group,0.1,sync,0.057409428685793254,0.057409428685793254,"[0.0820054945054953, 0.04460700701510746, 0.04536767140601303]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4056593406593407,"[0.0820054945054953, 0.5546703296703304, 0.5803021978021985]",0.056428571428571425,728,0.5989010989010989,0.4895275318081212,206,184,338,0.6699029126213593,0.07608695652173914,0.8402366863905325,0.6929094791412354,0.9213454455100748,0.5956986546516418,0.5038209993402167,0.856522262096405,0.04431794133487639,0.896978021978022,2.483696222305298,2.7812204360961914,0.6215575933456421,0.6215001344680786,5.7480163377476856e-05,0.13867542147636414,0.6329324841499329 +valid,C7_group,0.1,partial,0.0529758085036651,0.0529758085036651,"[0.08420329670329753, 0.03822459277521008, 0.03615291038442729]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.40424908424908423,"[0.08420329670329753, 0.5525274725274731, 0.5760164835164839]",0.043351648351648356,728,0.5975274725274725,0.4907362260992237,206,184,338,0.6699029126213593,0.08152173913043478,0.834319526627219,0.7017626166343689,0.9438621176506266,0.5769387483596802,0.5025645531442993,0.8543615937232971,0.04435367067600345,0.9010989010989011,2.482412099838257,2.7821567058563232,0.6227995753288269,0.6227447986602783,5.4783424275228754e-05,0.137740820646286,0.6342558860778809 +valid,C7_group,0.1,async,0.055965730621434076,0.055965730621434076,"[0.08420329670329753, 0.04282041186781863, 0.04055597458361638]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4039468864468865,"[0.08420329670329753, 0.5516208791208798, 0.5760164835164845]",0.05142857142857143,728,0.5975274725274725,0.48669941770158065,206,184,338,0.6699029126213593,0.07065217391304347,0.8402366863905325,0.69637531042099,0.9296973412257324,0.5881722569465637,0.5052266317913854,0.8589293360710144,0.05098074944792212,0.8928571428571429,2.4934823513031006,2.780679225921631,0.6250931620597839,0.6250423192977905,5.0786933570634574e-05,0.14747953414916992,0.6365020275115967 +valid,C7_group,0.3,single,0.10077529965039936,0.10077529965039936,"[0.1063186813186808, 0.09791175417598566, 0.0980390854159867]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4273534798534799,"[0.1063186813186808, 0.573956043956045, 0.601785714285715]",0.05964285714285714,728,0.5989010989010989,0.49015574781208127,206,184,338,0.6796116504854369,0.07608695652173914,0.834319526627219,0.7045457363128662,0.9380842295815184,0.583071768283844,0.5051888492722213,0.8582696318626404,0.04101182156047978,0.8942307692307693,2.5102062225341797,2.7861506938934326,0.6310259699821472,0.6309073567390442,0.0001186215304187499,0.14113637804985046,0.6425090432167053 +valid,C7_group,0.3,sync,0.18366496008611768,0.18366496008611768,"[0.2554945054945073, 0.14791849924316752, 0.1468227643446891]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.5004487179487179,"[0.2554945054945073, 0.6123626373626374, 0.6334890109890104]",0.18217032967032967,728,0.6002747252747253,0.4816221864596062,206,184,338,0.6504854368932039,0.059782608695652176,0.863905325443787,0.7177635431289673,0.9573691569537374,0.5661795139312744,0.5045437182286794,0.857754647731781,0.04156625360905469,0.9038461538461539,2.5944480895996094,2.7785251140594482,0.6616429686546326,0.6612945199012756,0.0003484586486592889,0.1668543964624405,0.6728068590164185 +valid,C7_group,0.3,partial,0.14816552304516878,0.14816552304516878,"[0.25920329670329867, 0.10412618442414666, 0.07975758376464556]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.486978021978022,"[0.25920329670329867, 0.5950274725274726, 0.6067032967032975]",0.14230769230769233,728,0.603021978021978,0.47998237537414346,206,184,338,0.6456310679611651,0.05434782608695652,0.8757396449704142,0.7138437032699585,0.9509089300331054,0.573399543762207,0.5063665747107217,0.8595925569534302,0.0311204168003994,0.9065934065934066,2.574791669845581,2.7784743309020996,0.6572321653366089,0.6569209098815918,0.0003112632839474827,0.16630439460277557,0.6685746312141418 +valid,C7_group,0.3,async,0.17500872720325933,0.17500872720325933,"[0.2542582417582435, 0.14028985682217077, 0.12954125320803533]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4937454212454212,"[0.2542582417582435, 0.6036538461538465, 0.6233241758241765]",0.1337087912087912,728,0.6016483516483516,0.48286727898702897,206,184,338,0.6456310679611651,0.059782608695652176,0.8698224852071006,0.7180367112159729,0.9444572741596972,0.5806990265846252,0.5104795310800547,0.8661132454872131,0.03460579083024801,0.9148351648351648,2.592299222946167,2.7894041538238525,0.6656634211540222,0.665399432182312,0.0002640645543579012,0.1847512423992157,0.6769996285438538 +valid,C7_group,0.5,single,0.16685149244608855,0.16685149244608855,"[0.1620879120879121, 0.1638041073804625, 0.1748267839307003]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4674908424908425,"[0.1620879120879121, 0.6050549450549455, 0.6353296703296704]",0.08684065934065933,728,0.6043956043956044,0.5059109153432723,206,184,338,0.6601941747572816,0.10869565217391304,0.8402366863905325,0.7071334719657898,0.9482637475624074,0.5768412351608276,0.5064077331989506,0.8601922392845154,0.043998221856552173,0.8983516483516484,2.555694341659546,2.784839391708374,0.652484655380249,0.6521745324134827,0.00031016941647976637,0.15328256785869598,0.6639654040336609 +valid,C7_group,0.5,sync,0.330209128768783,0.330209128768783,"[0.42032967032967034, 0.28200237109380377, 0.2874135682232839]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.6007692307692307,"[0.42032967032967034, 0.678736263736264, 0.7032417582417585]",0.3127747252747253,728,0.6016483516483516,0.47004685552268155,206,184,338,0.6407766990291263,0.03804347826086957,0.8846153846153846,0.7520185112953186,0.9922188881542421,0.5440298914909363,0.5075000488028996,0.862060546875,0.030628205123510988,0.9162087912087912,2.744828701019287,2.7928919792175293,0.7206804752349854,0.7196080684661865,0.001072459970600903,0.2082364410161972,0.7316300868988037 +valid,C7_group,0.5,partial,0.23623170531479354,0.23623170531479354,"[0.42032967032967034, 0.17341613672677042, 0.11239778582145649]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.5651465201465201,"[0.42032967032967034, 0.6398351648351651, 0.635274725274725]",0.24862637362637363,728,0.5961538461538461,0.46481200148766727,206,184,338,0.6407766990291263,0.03260869565217391,0.8757396449704142,0.7419087886810303,0.9808695304584909,0.5512108206748962,0.5145337520205764,0.871751070022583,0.038120132676520174,0.9065934065934066,2.711859703063965,2.804388999938965,0.7067751288414001,0.7058316469192505,0.0009434911189600825,0.19639189541339874,0.7177286744117737 +valid,C7_group,0.5,async,0.3120007279622296,0.3120007279622296,"[0.4065934065934066, 0.2579016785179102, 0.27065519914311004]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.5900000000000001,"[0.4065934065934066, 0.6680769230769213, 0.6953296703296687]",0.23804945054945056,728,0.6098901098901099,0.4868969554242713,206,184,338,0.6407766990291263,0.059782608695652176,0.8905325443786982,0.7342203855514526,0.9732589998884945,0.5622817873954773,0.5150087069856654,0.8731838464736938,0.05751317952360426,0.9134615384615384,2.7309603691101074,2.801368474960327,0.7168037295341492,0.7160341143608093,0.0007696091779507697,0.20801454782485962,0.728086531162262 +valid,C7_group,0.7,single,0.23221469003340273,0.23221469003340273,"[0.22115384615384592, 0.2612316954439274, 0.21388076914343795]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.5095421245421247,"[0.22115384615384592, 0.65239010989011, 0.655082417582419]",0.1204945054945055,728,0.5961538461538461,0.4884027579194865,206,184,338,0.6456310679611651,0.08152173913043478,0.8461538461538461,0.7348288893699646,0.966793699933628,0.5657607913017273,0.513070017880673,0.8706056475639343,0.039269216031163616,0.896978021978022,2.617692232131958,2.8100175857543945,0.6786830425262451,0.6779820919036865,0.0007009717519395053,0.1636187583208084,0.6902087926864624 +valid,C7_group,0.7,sync,0.505389528795785,0.505389528795785,"[0.5807692307692247, 0.47634612944176064, 0.4580784091507095]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.7128296703296704,"[0.5807692307692247, 0.7772252747252746, 0.7804945054945048]",0.44958791208791204,728,0.5879120879120879,0.4564096574254754,206,184,338,0.5776699029126213,0.03804347826086957,0.893491124260355,0.8039528727531433,1.0435931447657478,0.5142754316329956,0.5244555973797748,0.8870420455932617,0.054012581419486276,0.9148351648351648,2.923591375350952,2.833920955657959,0.8039596080780029,0.8017536401748657,0.0022060310002416372,0.2521463930606842,0.8145663738250732 +valid,C7_group,0.7,partial,0.39062347526393004,0.39062347526393004,"[0.5788461538461478, 0.31403194162971376, 0.27664384900565697]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.6740018315018315,"[0.5788461538461478, 0.7185989010989093, 0.7245604395604472]",0.40997252747252755,728,0.5659340659340659,0.4234608837213146,206,184,338,0.5436893203883495,0.005434782608695652,0.8846153846153846,0.8193768262863159,1.0717310728195293,0.4812347888946533,0.5252597716888627,0.8898241519927979,0.07443091068621521,0.9134615384615384,2.8862345218658447,2.83217453956604,0.7818465232849121,0.7795372605323792,0.0023092820774763823,0.2537541687488556,0.7927380204200745 +valid,C7_group,0.7,async,0.48300135283868606,0.48300135283868606,"[0.5932692307692244, 0.43288957390738114, 0.42157969775951804]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.7052930402930403,"[0.5932692307692244, 0.7602747252747305, 0.7623351648351689]",0.40626373626373624,728,0.5879120879120879,0.4536387142978671,206,184,338,0.5679611650485437,0.03260869565217391,0.9023668639053254,0.8060576319694519,1.051301338221365,0.5125513672828674,0.5322813432477767,0.8983481526374817,0.058708665298891606,0.9217032967032966,2.9334726333618164,2.840348720550537,0.8088424205780029,0.8068150281906128,0.0020274713169783354,0.2787218689918518,0.819914698600769 +valid,C7_group,0.3,modality_T,0.10069156293222682,0.10069156293222682,"[0.30000000000000354, 0.0, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4615567765567765,"[0.30000000000000354, 0.5295054945054959, 0.5551648351648366]",0.16016483516483515,728,0.5892857142857143,0.46066025455894294,206,184,338,0.6407766990291263,0.03260869565217391,0.8609467455621301,0.7292237877845764,0.9676148316401383,0.5572686791419983,0.5113536413661146,0.8663360476493835,0.03869289114743799,0.9065934065934066,2.6030967235565186,2.791116952896118,0.6669511198997498,0.6665979027748108,0.00035319526796229184,0.18094299733638763,0.678074836730957 +valid,C7_group,0.3,modality_A,0.056929076618108816,0.056929076618108816,"[0.0, 0.16961424063829394, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.3940018315018315,"[0.0, 0.6268406593406597, 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0.6480219780219784]",0.0,728,0.6016483516483516,0.5042605037712021,206,184,338,0.6747572815533981,0.10869565217391304,0.8254437869822485,0.6932002305984497,0.9339126616818396,0.5855700373649597,0.5024117228831605,0.8546078205108643,0.04705358800161017,0.8914835164835165,2.4462316036224365,2.7841920852661133,0.6090024709701538,0.6089901924133301,1.2304343727009837e-05,0.12059278786182404,0.6205311417579651 +valid,C7_group,0.3,modality_TA,0.15458357737606096,0.15458357737606096,"[0.30000000000000354, 0.1605656309459839, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4928388278388279,"[0.30000000000000354, 0.6233516483516487, 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0.5551648351648366]",0.26755494505494504,728,0.6016483516483516,0.4666669027543165,206,184,338,0.6019417475728155,0.03260869565217391,0.9112426035502958,0.7316970229148865,0.9480264970359934,0.5912908315658569,0.5110139704505328,0.8664156794548035,0.051195164630701236,0.9093406593406593,2.7151944637298584,2.792081117630005,0.7178066372871399,0.7172861695289612,0.0005204986082389951,0.2425491362810135,0.7291560769081116 +valid,C7_group,0.3,span_long_T,0.10069156293222682,0.10069156293222682,"[0.30000000000000354, 0.0, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4615567765567765,"[0.30000000000000354, 0.5295054945054959, 0.5551648351648366]",0.16035714285714286,728,0.6002747252747253,0.4755757240008096,206,184,338,0.6407766990291263,0.04891304347826087,0.8757396449704142,0.7145537734031677,0.9429056407223688,0.5793851613998413,0.5079124398840459,0.8620046377182007,0.04858801730877747,0.9120879120879121,2.6015989780426025,2.782161235809326,0.6664382219314575,0.6661048531532288,0.0003333849017508328,0.18127746880054474,0.6775016188621521 +valid,C7_group,0.3,span_multi_short_T,0.10069156293222682,0.10069156293222682,"[0.30000000000000354, 0.0, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4615567765567765,"[0.30000000000000354, 0.5295054945054959, 0.5551648351648366]",0.1539010989010989,728,0.603021978021978,0.4891074372355046,206,184,338,0.6553398058252428,0.07065217391304347,0.8609467455621301,0.7114484310150146,0.9468978325133636,0.5756534934043884,0.5072763327562291,0.8607984185218811,0.03414913582114073,0.9010989010989011,2.593212366104126,2.778794527053833,0.6644482612609863,0.6642063856124878,0.00024184731591958553,0.18629631400108337,0.6754754185676575 +valid,C7_group,0.3,location_start_A,0.2003851185549212,0.2003851185549212,"[0.0, 0.5970265414088254, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.44360805860805863,"[0.0, 0.7756593406593403, 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0.5551648351648366]",0.0,728,0.603021978021978,0.5057193445940249,206,184,338,0.6747572815533981,0.10869565217391304,0.8284023668639053,0.6911180019378662,0.9319875139333276,0.586514949798584,0.5024843596577928,0.8544747233390808,0.045553898090844626,0.8942307692307693,2.443307399749756,2.7842085361480713,0.6088773608207703,0.6088649034500122,1.2469772627810016e-05,0.12250152230262756,0.620316743850708 +valid,C7_group,0.3,location_end_A,0.012218129834169183,0.012218129834169183,"[0.0, 0.03640264232185844, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.37236263736263736,"[0.0, 0.5619230769230764, 0.5551648351648366]",0.0,728,0.6057692307692307,0.5077628257349466,206,184,338,0.6747572815533981,0.10869565217391304,0.834319526627219,0.6869874000549316,0.9255946812374676,0.591266930103302,0.5024750375171664,0.8546248078346252,0.04286167369439051,0.8914835164835165,2.443835973739624,2.7834136486053467,0.6078216433525085,0.6078099012374878,1.168659764516633e-05,0.12491586804389954,0.6192470192909241 +valid,C7_group,0.3,span_long_A,0.10046375561263678,0.10046375561263678,"[0.0, 0.29932127187336466, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4085531135531135,"[0.0, 0.6704945054945051, 0.5551648351648366]",0.0,728,0.6085164835164835,0.513416477702192,206,184,338,0.6747572815533981,0.11956521739130435,0.834319526627219,0.690218448638916,0.9312123847891612,0.5882331132888794,0.5022952739908858,0.8542475700378418,0.05126464800847755,0.8942307692307693,2.4556326866149902,2.7825546264648438,0.6134862303733826,0.6134747266769409,1.1493194506329019e-05,0.12273188680410385,0.6250050067901611 +valid,C7_group,0.3,span_multi_short_A,0.10046375561263678,0.10046375561263678,"[0.0, 0.29932127187336466, 0.0]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4085531135531135,"[0.0, 0.6704945054945051, 0.5551648351648366]",0.0,728,0.6085164835164835,0.513416477702192,206,184,338,0.6747572815533981,0.11956521739130435,0.834319526627219,0.6897726655006409,0.9304584544242402,0.5885758399963379,0.5024095611291453,0.8546000719070435,0.048114364659720715,0.8928571428571429,2.4537172317504883,2.783405303955078,0.6123944520950317,0.612383246421814,1.1239861123613082e-05,0.12191381305456161,0.6239029169082642 +valid,C7_group,0.3,location_start_V,0.19317645467012823,0.19317645467012823,"[0.0, 0.0, 0.5876574055813588]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.43891941391941397,"[0.0, 0.5295054945054959, 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0.5857142857142853]",0.0,728,0.603021978021978,0.5057193445940249,206,184,338,0.6747572815533981,0.10869565217391304,0.8284023668639053,0.6898821592330933,0.9292504701897984,0.5878564119338989,0.5024968970195555,0.8545445799827576,0.043091767068420155,0.8901098901098901,2.441678762435913,2.7837138175964355,0.606282651424408,0.6062709093093872,1.1755465493479278e-05,0.12353598326444626,0.6177225708961487 +valid,C7_group,0.3,span_long_V,0.09768688768578579,0.09768688768578579,"[0.0, 0.0, 0.29717091078607255]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.4059615384615385,"[0.0, 0.5295054945054959, 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0.6883791208791201]",0.0,728,0.6071428571428571,0.5126163431119378,206,184,338,0.6796116504854369,0.11956521739130435,0.8284023668639053,0.6865583062171936,0.9224864419080372,0.5963611006736755,0.502382073686788,0.8546035289764404,0.04217641759704757,0.8942307692307693,2.4535820484161377,2.7842366695404053,0.6117274761199951,0.6117154359817505,1.2012919796688948e-05,0.11882655322551727,0.6233139038085938 +valid,C7_group,0.3,synchrony_sync,0.21691507013507422,0.21691507013507422,"[0.30000000000000354, 0.1761774211270993, 0.17367689276640616]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.5254212454212455,"[0.30000000000000354, 0.6281043956043952, 0.6481593406593403]",0.25337912087912084,728,0.592032967032967,0.4685336829264865,206,184,338,0.6553398058252428,0.043478260869565216,0.8520710059171598,0.725333571434021,0.9638541702891106,0.5632575750350952,0.5089390849055021,0.8631634712219238,0.04815735246290217,0.9024725274725275,2.628369092941284,2.7811200618743896,0.6741431951522827,0.6737390756607056,0.0004041623033117503,0.16398340463638306,0.6854046583175659 +valid,C7_group,0.3,synchrony_partial,0.1606943112281871,0.1606943112281871,"[0.30000000000000354, 0.1155318929339427, 0.06457046703790681]",0.36155677655677654,"[0.0, 0.5295054945054959, 0.5551648351648366]",0.5020238095238095,"[0.30000000000000354, 0.604038461538462, 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0.6416208791208796]",0.16925824175824175,728,0.5975274725274725,0.4684562423732539,206,184,338,0.6456310679611651,0.03804347826086957,0.8727810650887574,0.7251530885696411,0.9609705291282016,0.5695079565048218,0.506161196799791,0.858941376209259,0.039323603877654455,0.9120879120879121,2.6206741333007812,2.777359962463379,0.6767795085906982,0.6764330863952637,0.000346398854162544,0.18655642867088318,0.6883273124694824 diff --git a/math/Q2/results/crg_student.pt b/math/Q2/results/crg_student.pt new file mode 100644 index 0000000..07e532a Binary files /dev/null and b/math/Q2/results/crg_student.pt differ diff --git a/math/Q2/results/group_bootstrap_ci.csv b/math/Q2/results/group_bootstrap_ci.csv new file mode 100644 index 0000000..ac94daa --- /dev/null +++ b/math/Q2/results/group_bootstrap_ci.csv @@ -0,0 +1,8 @@ +metric,estimate,ci_2_5,ci_97_5,replicates,unit +accuracy,0.6732320304207147,0.6389280203708787,0.7099405325043925,1000,source video group 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b/math/Q2/results/q2_gate_positions.png new file mode 100644 index 0000000..f90638b Binary files /dev/null and b/math/Q2/results/q2_gate_positions.png differ diff --git a/math/Q2/results/reliability_hparam_tuning.csv b/math/Q2/results/reliability_hparam_tuning.csv new file mode 100644 index 0000000..b03d7e7 --- /dev/null +++ b/math/Q2/results/reliability_hparam_tuning.csv @@ -0,0 +1,70 @@ +model,rho_imp,lambda_u,lambda_gap,lambda_span,inner_selection_nll,scenario_selection_nll,selected,selection_split,note,group_lambda,group_temperature,risk_candidate_selected,candidate +teacher,0.5,0.0,0.0,0.0,2.8498539328575134,"{""0.0/natural"": 2.830216884613037, ""0.3/single"": 2.8259665966033936, ""0.3/sync"": 2.84348726272583, ""0.5/async"": 2.899744987487793}",False,reliability_validation,,,,, +teacher,0.5,0.05,0.05,0.05,2.8493970036506653,"{""0.0/natural"": 2.83003568649292, ""0.3/single"": 2.82570481300354, ""0.3/sync"": 2.8433682918548584, ""0.5/async"": 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0.8373432159423828, + "ece_15": 0.05973948173961796, + "selection_nll": 2.761949062347412, + "interval_90_coverage": 0.8928571428571429, + "interval_90_mean_width": 2.38193416595459, + "predictive_variance_mean_uncalibrated": 0.5485386848449707, + "within_trajectory_variance_mean": 0.548530638217926, + "between_trajectory_variance_mean": 8.043976777116768e-06, + "predictive_mean_mean_calibrated": 0.1391187161207199, + "predictive_variance_mean_calibrated": 0.596049964427948, + "selected_model": "C5", + "temperature": 1.212728800581531 +} \ No newline at end of file diff --git a/math/Q2/test_model.py b/math/Q2/test_model.py new file mode 100644 index 0000000..c2d4d28 --- /dev/null +++ b/math/Q2/test_model.py @@ -0,0 +1,316 @@ +"""Numerical checks for the Q2 state posterior, joint sampling, and decoder.""" +from __future__ import annotations + +import unittest +from types import SimpleNamespace + +import numpy as np +import torch +from scipy.special import betainc as scipy_betainc + +from crg import CRG, ReliabilityGRU, StructuredGaussianImputer +from train import ( + _decode_mixture, + _calibrated_mixture_moments, + _group_ids, + _missing_rate_summary, + _predictive_intervals, + _trajectory_variance_components, + continuous_mask, + controlled_group_bootstrap, + gate_diagnostic_rows, + regularized_beta, + smooth_group_risk, + validate_attachment3_predictions, +) + + +class StructuredGaussianTests(unittest.TestCase): + def test_filter_nll_matches_dense_marginal_gaussian(self) -> None: + torch.manual_seed(73) + model = StructuredGaussianImputer((2, 2, 2)).double() + xs = [torch.randn(1, 2, 2, dtype=torch.float64) for _ in range(3)] + observed = torch.ones(1, 2, 3, dtype=torch.bool) + got = model.observed_nll(xs, observed)[0] + + with torch.no_grad(): + transition = model._transition() + p0, q = model._covariances() + emissions = model.emissions() + emission = torch.cat(emissions, dim=0) + noise = torch.block_diag(*[torch.diag(torch.nn.functional.softplus(raw) + 1e-4) for raw in model.r_raw]) + offset = torch.cat(list(model.biases)) + state_mean = torch.cat((model.mu0, transition @ model.mu0)) + p01 = p0 @ transition.T + p11 = transition @ p0 @ transition.T + q + state_cov = torch.cat((torch.cat((p0, p01), dim=1), torch.cat((p01.T, p11), dim=1)), dim=0) + observation_map = torch.block_diag(emission, emission) + observation_cov = observation_map @ state_cov @ observation_map.T + torch.block_diag(noise, noise) + observation_mean = torch.cat((offset + emission @ model.mu0, + offset + emission @ (transition @ model.mu0))) + values = torch.cat((torch.cat([xs[m][0, 0] for m in range(3)]), + torch.cat([xs[m][0, 1] for m in range(3)]))) + residual = values - observation_mean + expected = 0.5 * ( + residual @ torch.linalg.solve(observation_cov, residual) + + torch.linalg.slogdet(observation_cov).logabsdet + + len(values) * np.log(2.0 * np.pi) + ) + torch.testing.assert_close(got, expected, rtol=2e-4, atol=2e-4) + + def test_joint_trajectory_draws_retain_temporal_dependence(self) -> None: + torch.manual_seed(19) + model = StructuredGaussianImputer((2, 2, 2)) + with torch.no_grad(): + for emission in model.emission_raw: + emission.zero_() + model.emission_raw[1][0, 0] = 1.0 + xs = [torch.zeros(1, 2, 2) for _ in range(3)] + observed = torch.zeros(1, 2, 3, dtype=torch.bool) + draws, _ = model.complete(xs, observed, 1600, joint_draws=True) + temporal_correlation = float(np.corrcoef(draws[1][:, 0, 0, 0].cpu(), draws[1][:, 0, 1, 0].cpu())[0, 1]) + self.assertGreater(temporal_correlation, 0.15) + + +class LossAndMaskTests(unittest.TestCase): + def test_beta_cdf_matches_scipy(self) -> None: + a = torch.tensor([0.7, 2.0, 5.0]) + b = torch.tensor([1.3, 3.0, 2.5]) + x = torch.tensor([0.2, 0.8, 0.55]) + actual = regularized_beta(x, a, b).detach().cpu().numpy() + expected = scipy_betainc(a.numpy(), b.numpy(), x.numpy()) + np.testing.assert_allclose(actual, expected, rtol=2e-5, atol=2e-6) + + def test_mask_is_contiguous_and_preserves_each_selected_source(self) -> None: + original = np.ones((50, 3), dtype=bool) + for mode in ("single", "sync", "partial", "async"): + masked = continuous_mask(original, 0.5, mode, np.random.default_rng(101)) + hidden = original & ~masked + for modality in range(3): + positions = np.flatnonzero(hidden[:, modality]) + if len(positions): + self.assertEqual(int(positions[-1] - positions[0] + 1), len(positions)) + self.assertGreaterEqual(int(masked[:, modality].sum()), 10) + + def test_point_mask_keeps_rate_but_breaks_contiguous_span(self) -> None: + original = np.ones((50, 3), dtype=bool) + masked = continuous_mask(original, 0.3, "single", np.random.default_rng(887), + modalities=(1,), kind="point") + hidden = np.flatnonzero(original[:, 1] & ~masked[:, 1]) + self.assertEqual(len(hidden), 15) + self.assertGreaterEqual(int(masked[:, 1].sum()), 10) + runs = np.split(hidden, np.flatnonzero(np.diff(hidden) > 1) + 1) + self.assertGreater(len([run for run in runs if len(run)]), 1) + + def test_position_and_gap_structure_controls_hold_total_missing_fixed(self) -> None: + original = np.ones((50, 3), dtype=bool) + counts = [] + for location in ("start", "middle", "end"): + masked = continuous_mask( + original, 0.3, "single", np.random.default_rng(22), + modalities=(0,), location=location, + ) + hidden = np.flatnonzero(original[:, 0] & ~masked[:, 0]) + counts.append(len(hidden)) + if location == "start": + self.assertEqual(int(hidden[0]), 0) + elif location == "end": + self.assertEqual(int(hidden[-1]), 49) + else: + self.assertLessEqual(abs(float(hidden.mean()) - 24.5), 1.0) + self.assertEqual(counts, [15, 15, 15]) + + long = continuous_mask( + original, 0.3, "single", np.random.default_rng(22), + modalities=(0,), span_structure="long", + ) + short = continuous_mask( + original, 0.3, "single", np.random.default_rng(22), + modalities=(0,), span_structure="multi_short", + ) + long_hidden = np.flatnonzero(original[:, 0] & ~long[:, 0]) + short_hidden = np.flatnonzero(original[:, 0] & ~short[:, 0]) + self.assertEqual(len(long_hidden), len(short_hidden)) + short_runs = np.split(short_hidden, np.flatnonzero(np.diff(short_hidden) > 1) + 1) + self.assertGreaterEqual(len([run for run in short_runs if len(run)]), 2) + + def test_group_id_uses_any_newly_hidden_source(self) -> None: + original = np.ones((2, 50, 3), dtype=bool) + current = original.copy() + current[0, 10:20, 1] = False + current[1, 15:25, 2] = False + groups = _group_ids(original, current) + self.assertNotEqual(int(groups[0]), int(groups[1])) + + def test_missing_rates_follow_equal_modality_pdf_denominators(self) -> None: + original = np.asarray([ + [1, 1, 0], [1, 1, 0], [1, 0, 0], [1, 0, 0], + ], dtype=bool) + current = original.copy() + current[0, 0] = False + rates = _missing_rate_summary(original, current) + np.testing.assert_allclose(rates["natural_by_modality"], [0.0, 0.5, 1.0]) + self.assertAlmostEqual(rates["natural_global"], 0.5) + np.testing.assert_allclose(rates["final_by_modality"], [0.25, 0.5, 1.0]) + self.assertAlmostEqual(rates["final_global"], 7.0 / 12.0) + np.testing.assert_allclose(rates["additional_by_modality"][:2], [0.25, 0.0]) + self.assertTrue(np.isnan(rates["additional_by_modality"][2])) + + def test_smooth_group_risk_matches_prior_weighted_formula(self) -> None: + losses = torch.tensor([1.0, 2.0, 4.0], dtype=torch.float64) + group_ids = np.asarray([0, 0, 1]) + lambda_group, tau = 0.2, 0.5 + group_losses = torch.tensor([1.5, 4.0], dtype=torch.float64) + priors = torch.tensor([2 / 3, 1 / 3], dtype=torch.float64) + expected = ((1 - lambda_group) * (priors * group_losses).sum() + + lambda_group * tau * torch.logsumexp(priors.log() + group_losses / tau, dim=0)) + actual = smooth_group_risk(losses, group_ids, lambda_group, tau) + torch.testing.assert_close(actual, expected) + + def test_controlled_group_bootstrap_is_paired_and_reports_aurc(self) -> None: + split = SimpleNamespace( + n=4, + class_y=np.asarray([0, 0, 1, 2]), + regression_y=np.asarray([-1.0, -0.5, 0.0, 1.0]), + groups=np.asarray(["v1", "v1", "v2", "v3"]), + mask=np.ones((4, 50, 3), dtype=bool), + ) + scenarios = ["0.0/none"] + [f"{rate:.1f}/{mode}" for mode in ("single", "sync", "partial", "async") + for rate in (0.1, 0.3, 0.5, 0.7)] + scenario_masks = {} + for scenario in scenarios: + mask = split.mask.copy() + rate_name, pattern = scenario.split("/", 1) + rate = float(rate_name) + if rate > 0: + modality = {"single": 0, "sync": 0, "partial": 1, "async": 2}[pattern] + count = int(round(rate * 50)) + mask[:, :count, modality] = False + scenario_masks[scenario] = mask + predictions = {} + for model, shift in (("C0", 0.0), ("C1", 0.1)): + predictions[model] = {} + for index, scenario in enumerate(scenarios): + predictions[model][scenario] = { + "predicted_class": np.asarray([0, 1, 1, 2]), + "predicted_score": split.regression_y + shift + index * 0.01, + } + rows = controlled_group_bootstrap(split, predictions, scenario_masks, repeats=20, seed=29) + self.assertTrue(any(row["metric"] == "AURC_MAE" and row["model"] == "C1" for row in rows)) + paired = next(row for row in rows if row["model"] == "C1" and row["scenario"] == "0.3/single" and row["metric"] == "mae") + self.assertAlmostEqual(paired["delta_estimate"], 0.1) + self.assertAlmostEqual(paired["delta_to_natural_mae"], 0.02) + self.assertEqual(paired["replicates"], 20) + + def test_attachment3_submission_invariants(self) -> None: + rows = [ + {"case_id": "case-a", "predicted_class": 0, "predicted_sentiment": -0.2, + "p_negative": 0.5, "p_neutral": 0.3, "p_positive": 0.2, + "interval_90_lower": -1.0, "interval_90_upper": 0.5}, + {"case_id": "case-b", "predicted_class": 1, "predicted_sentiment": 0.0, + "p_negative": 0.2, "p_neutral": 0.6, "p_positive": 0.2, + "interval_90_lower": -0.5, "interval_90_upper": 0.5}, + ] + validate_attachment3_predictions(["case-a", "case-b"], rows) + rows[1]["predicted_sentiment"] = 1e-9 + with self.assertRaisesRegex(ValueError, "polarity mismatch"): + validate_attachment3_predictions(["case-a", "case-b"], rows) + + def test_gate_diagnostic_rows_keep_sample_position_and_modality(self) -> None: + split = SimpleNamespace(ids=["v1$_$c1"], groups=np.asarray(["v1"]), + mask=np.ones((1, 2, 3), dtype=bool)) + scalar = np.zeros((1, 2, 3), dtype=np.float32) + predictions = { + "fusion_weights": np.full((1, 2, 3), 0.2, dtype=np.float32), + "null_weights": np.full((1, 2), 0.4, dtype=np.float32), + "time_pool_weights": np.full((1, 2), 0.5, dtype=np.float32), + "reliability": np.ones((1, 2, 3), dtype=np.float32), + "imputation_uncertainty": scalar, + "gap": scalar, + "span": scalar, + "distance_before": scalar, + "distance_after": scalar, + } + rows = gate_diagnostic_rows(split, predictions) + self.assertEqual(len(rows), 6) + self.assertEqual(rows[0]["sample_id"], "v1$_$c1") + self.assertEqual(rows[-1]["modality"], "vision") + + def test_decoder_uses_neutral_priority_and_exact_zero(self) -> None: + probabilities = np.asarray([[[1 / 3, 1 / 3, 1 / 3]], [[1 / 3, 1 / 3, 1 / 3]]], dtype=np.float32) + beta = np.full((2, 1, 2, 2), 2.0, dtype=np.float32) + _, classes, scores = _decode_mixture(probabilities, beta) + self.assertEqual(int(classes[0]), 1) + self.assertEqual(float(scores[0]), 0.0) + + def test_calibrated_signed_mixture_interval_and_variance_components(self) -> None: + probabilities = np.asarray( + [[[0.25, 0.5, 0.25]], [[0.4, 0.2, 0.4]]], dtype=np.float64, + ) + beta = np.full((2, 1, 2, 2), 2.0, dtype=np.float64) + low, high = _predictive_intervals(probabilities, beta, temperature=1.5) + self.assertLess(float(low[0]), 0.0) + self.assertGreater(float(high[0]), 0.0) + self.assertLess(float(low[0]), float(high[0])) + total, within, between = _trajectory_variance_components(probabilities, beta) + np.testing.assert_allclose(total, within + between, rtol=1e-6, atol=1e-7) + mean_cold, variance_cold = _calibrated_mixture_moments(probabilities, beta, temperature=0.5) + mean_warm, variance_warm = _calibrated_mixture_moments(probabilities, beta, temperature=2.0) + self.assertTrue(np.isfinite(mean_cold).all() and np.isfinite(variance_cold).all()) + self.assertGreater(abs(float(variance_cold[0] - variance_warm[0])), 1e-5) + + +class RecurrentAndVariantTests(unittest.TestCase): + def test_gru_reset_gate_is_applied_before_candidate_recurrent_map(self) -> None: + model = ReliabilityGRU(input_dim=1, hidden=1) + with torch.no_grad(): + model.x_proj.weight.zero_() + model.x_proj.bias.copy_(torch.tensor([10.0, 0.0, 1.0])) + model.h_proj.weight.zero_() + model.candidate_h.weight.fill_(2.0) + x = torch.zeros(1, 2, 1) + rho = torch.ones(1, 2) + distance = torch.zeros(1, 2) + actual = model._one_direction(x, rho, distance, reverse=False, reliability_update=False) + z = torch.sigmoid(torch.tensor(10.0)) + first = z * torch.tanh(torch.tensor(1.0)) + reset = torch.sigmoid(torch.tensor(0.0)) + candidate = torch.tanh(torch.tensor(1.0) + 2.0 * reset * first) + expected = (1.0 - z) * first + z * candidate + torch.testing.assert_close(actual[0, 1, 0], expected) + + def test_all_ablation_architectures_forward_and_backward(self) -> None: + torch.manual_seed(9) + options = { + "C1": dict(use_imputer=False, use_joint_draws=False, use_final_gate=False, use_source_attention=False, reliability_update=False, use_low_rank=False), + "C2": dict(use_imputer=True, use_joint_draws=False, use_final_gate=False, use_source_attention=False, reliability_update=False, use_low_rank=False), + "C3": dict(use_imputer=True, use_joint_draws=True, use_final_gate=True, use_source_attention=False, reliability_update=False, use_low_rank=False), + "C4": dict(use_imputer=True, use_joint_draws=True, use_final_gate=True, use_source_attention=True, reliability_update=False, use_low_rank=False), + "C5": dict(use_imputer=True, use_joint_draws=True, use_final_gate=True, use_source_attention=True, reliability_update=True, use_low_rank=False), + "C6": dict(use_imputer=True, use_joint_draws=True, use_final_gate=True, use_source_attention=True, reliability_update=True, use_low_rank=True), + } + xs = [torch.randn(1, 4, width) for width in (3, 2, 2)] + observed = torch.ones(1, 4, 3, dtype=torch.bool) + observed[:, 1:3, 1] = False + for name, flags in options.items(): + with self.subTest(model=name): + model = CRG(input_dims=(3, 2, 2), **flags) + output = model(xs, observed, paths=2, joint_draws=flags["use_joint_draws"]) + loss = output["class_logits"].sum() + output["beta_params"].sum() + loss.backward() + expected_paths = 2 if flags["use_imputer"] else 1 + self.assertEqual(tuple(output["class_probs"].shape), (1, 3)) + self.assertEqual(tuple(output["fusion_weights_by_path"].shape), (expected_paths, 1, 4, 3)) + self.assertEqual(tuple(output["null_weights_by_path"].shape), (expected_paths, 1, 4)) + self.assertEqual(tuple(output["time_pool_weights_by_path"].shape), (expected_paths, 1, 4)) + torch.testing.assert_close( + output["fusion_weights_by_path"].sum(dim=-1) + output["null_weights_by_path"], + torch.ones((expected_paths, 1, 4)), + ) + torch.testing.assert_close( + output["time_pool_weights_by_path"].sum(dim=-1), torch.ones((expected_paths, 1)), + ) + + +if __name__ == "__main__": + unittest.main() diff --git a/math/Q2/train.py b/math/Q2/train.py new file mode 100644 index 0000000..2363101 --- /dev/null +++ b/math/Q2/train.py @@ -0,0 +1,2047 @@ +"""Train/evaluate the Q2 model under the V2 official split and ablation design.""" +from __future__ import annotations + +import argparse +import copy +import csv +from contextlib import contextmanager +import hashlib +import json +import math +import random +import time +from pathlib import Path +from typing import Any + +import numpy as np +import torch +from scipy.optimize import minimize_scalar +from scipy.special import betainc, betaincinv +from scipy.stats import pearsonr +from sklearn.linear_model import LogisticRegression, Ridge +from sklearn.metrics import accuracy_score, f1_score, mean_absolute_error, mean_squared_error, recall_score +from sklearn.model_selection import GroupShuffleSplit +from torch.nn import functional as F +from transformers import AutoModel + +from crg import CRG, INPUT_DIMS, MODALITIES, StructuredGaussianImputer +from data import ( + ATTACHMENT3_ALIGNED, + ROOT, + SplitData, + fit_preprocessor, + load_attachment3_case, + load_official_splits, + transform_split, +) + +Q2_DIR = Path(__file__).resolve().parent +RESULTS = Q2_DIR / "results" +TEXT_MODEL_ID = "google-bert/bert-base-uncased" +SEED = 20260924 +MASK_RATES = (0.0, 0.1, 0.3, 0.5, 0.7) +MASK_MODES = ("single", "sync", "partial", "async") +DELTA_U = 0.01 +DISTILL_TEMPERATURE = 2.0 +LAMBDA_Y = 1.0 +LAMBDA_DISTILL = 0.1 +LAMBDA_RECON = 0.05 +LAMBDA_GROUP = 0.1 +GROUP_TEMPERATURE = 0.1 +GROUP_RISK_CANDIDATES = ((0.05, 0.1), (0.1, 0.05), (0.1, 0.1), (0.1, 0.2), (0.2, 0.1)) +LAMBDA_EMISSION = 1e-4 +LAMBDA_TRANSITION = 1e-4 +DEFAULT_RELIABILITY = (0.5, 0.05, 0.05, 0.05) +RELIABILITY_CANDIDATES = ( + (0.5, 0.0, 0.0, 0.0), + (0.5, 0.05, 0.05, 0.05), + (0.5, 0.1, 0.0, 0.0), + (0.3, 0.05, 0.05, 0.05), + (0.7, 0.05, 0.05, 0.05), +) + + +def seed_everything(seed: int) -> None: + random.seed(seed) + np.random.seed(seed) + torch.manual_seed(seed) + torch.cuda.manual_seed_all(seed) + torch.backends.cudnn.benchmark = False + torch.backends.cudnn.deterministic = True + + +@contextmanager +def fixed_torch_seed(seed: int, device: torch.device): + devices = [device.index if device.index is not None else torch.cuda.current_device()] if device.type == "cuda" else [] + with torch.random.fork_rng(devices=devices): + torch.manual_seed(int(seed)) + if device.type == "cuda": + torch.cuda.manual_seed_all(int(seed)) + yield + + +def sha256(path: Path) -> str: + digest = hashlib.sha256() + with path.open("rb") as stream: + for block in iter(lambda: stream.read(1024 * 1024), b""): + digest.update(block) + return digest.hexdigest() + + +def label_resolution_from_train(labels: np.ndarray) -> float: + """Use half the smallest positive nonzero magnitude spacing in fit labels.""" + magnitudes = np.unique(np.round(np.abs(np.asarray(labels, dtype=np.float64)) / 3.0, 6)) + spacing = np.diff(magnitudes) + spacing = spacing[spacing > 1e-5] + return float(np.clip(0.5 * spacing.min(), 1e-4, 0.1)) if len(spacing) else 0.01 + + +def fit_magnitude_priors(labels: np.ndarray) -> np.ndarray: + """Method-of-moments sign-specific Beta priors from train labels only.""" + result = np.zeros((2, 2), dtype=np.float64) + for slot, selected in enumerate((np.asarray(labels) < 0, np.asarray(labels) > 0)): + values = np.abs(np.asarray(labels, dtype=np.float64)[selected]) / 3.0 + values = np.clip(values, 1e-4, 1.0 - 1e-4) + if len(values) < 2: + mean, concentration = 0.5, 4.0 + else: + mean, variance = float(values.mean()), float(values.var(ddof=1)) + concentration = mean * (1.0 - mean) / max(variance, 1e-5) - 1.0 + concentration = float(np.clip(concentration, 2.0, 100.0)) + result[slot] = (max(1e-3, mean * concentration), max(1e-3, (1.0 - mean) * concentration)) + return result.astype(np.float32) + + +def assert_group_disjoint(splits: dict[str, SplitData]) -> dict[str, int]: + overlap: dict[str, int] = {} + for left, right in (("train", "valid"), ("train", "test"), ("valid", "test")): + shared = set(splits[left].groups) & set(splits[right].groups) + overlap[f"{left}_{right}"] = len(shared) + if shared: + raise ValueError(f"source-video leakage across {left}/{right}: {sorted(shared)[:5]}") + return overlap + + +def select_rows(split: SplitData, indices: np.ndarray, name: str) -> SplitData: + idx = np.asarray(indices, dtype=np.int64) + return SplitData( + name=name, + x={m: split.x[m][idx].copy() for m in MODALITIES}, + mask=split.mask[idx].copy(), + class_y=split.class_y[idx].copy() if split.class_y is not None else None, + regression_y=split.regression_y[idx].copy() if split.regression_y is not None else None, + ids=[split.ids[int(i)] for i in idx], + groups=split.groups[idx].copy(), + ) + + +def split_calibration(train: SplitData, seed: int, fraction: float = 0.1) -> tuple[SplitData, SplitData]: + splitter = GroupShuffleSplit(n_splits=1, test_size=fraction, random_state=seed) + fit_idx, cal_idx = next(splitter.split(np.zeros(train.n), train.class_y, train.groups)) + fit, cal = select_rows(train, fit_idx, "fit"), select_rows(train, cal_idx, "calibration") + if set(fit.groups) & set(cal.groups): + raise AssertionError("internal fit/calibration source videos overlap") + return fit, cal + + +def _best_interval( + visible: np.ndarray, + wanted: int, + cap: int, + location: str, + rng: np.random.Generator, +) -> tuple[int, int] | None: + steps = len(visible) + candidates: list[tuple[int, int, int, int]] = [] + for left in range(steps): + hits = 0 + for right in range(left, steps): + hits += int(visible[right]) + count = min(hits, cap) + if count: + candidates.append((abs(count - wanted), right - left + 1, left, right)) + if not candidates: + return None + best = min((error, span) for error, span, _, _ in candidates) + tied = [(left, right) for error, span, left, right in candidates if (error, span) == best] + if location == "start": + return min(tied, key=lambda pair: (pair[0], pair[1])) + if location == "end": + return max(tied, key=lambda pair: (pair[1], pair[0])) + if location == "middle": + center = (steps - 1) / 2 + return min(tied, key=lambda pair: (abs((pair[0] + pair[1]) / 2 - center), pair[0])) + if location != "random": + raise ValueError(f"unknown interval location: {location}") + return tied[int(rng.integers(0, len(tied)))] + + +def _spread_short_spans(visible: np.ndarray, wanted: int, cap: int) -> np.ndarray: + positions = np.flatnonzero(visible) + count = min(int(wanted), int(cap), len(positions)) + chosen = np.zeros(len(visible), dtype=bool) + if count <= 0: + return chosen + n_spans = min(3, count) + chunks = np.array_split(positions, n_spans) + allocations = [count // n_spans + int(i < count % n_spans) for i in range(n_spans)] + for chunk, amount in zip(chunks, allocations): + if amount <= 0 or len(chunk) == 0: + continue + amount = min(amount, len(chunk)) + start = max(0, (len(chunk) - amount) // 2) + chosen[chunk[start:start + amount]] = True + return chosen + + +def continuous_mask( + original: np.ndarray, + rate: float, + mode: str, + rng: np.random.Generator, + *, + modalities: tuple[int, ...] | None = None, + location: str = "random", + span_structure: str = "long", + kind: str = "continuous", +) -> np.ndarray: + """Hide contiguous feature rows while preserving at least 20% per selected source. + + ``sync``, ``partial`` and ``async`` use a shared, shifted-overlap, or + staggered span layout. Evaluation controls may pin the affected modalities, + gap location, and one-long versus several-short structure. + """ + observed = np.asarray(original, dtype=bool) + result = observed.copy() + if rate <= 0 or mode == "none": + return result + steps, modality_count = observed.shape + present = [m for m in range(modality_count) if observed[:, m].any()] + if not present: + return result + if modalities is not None: + selected = [int(m) for m in modalities if int(m) in present] + if not selected: + return result + elif mode == "single": + selected = [int(rng.choice(present))] + elif mode in {"sync", "partial", "async"}: + if len(present) == 1: + selected = present + else: + count = int(rng.integers(2, min(3, len(present)) + 1)) + selected = sorted(int(v) for v in rng.choice(present, size=count, replace=False)) + else: + raise ValueError(f"unknown mask mode: {mode}") + + def max_hide(modality: int) -> int: + count = int(observed[:, modality].sum()) + keep = max(1, int(math.ceil(0.2 * count))) + return max(0, count - keep) + + target = {m: min(max_hide(m), int(round(rate * int(observed[:, m].sum())))) for m in selected} + if kind == "point": + for modality in selected: + candidates = np.flatnonzero(observed[:, modality]) + count = target[modality] + if count > 0: + hidden = rng.choice(candidates, size=count, replace=False) + result[hidden, modality] = False + return result + if kind != "continuous": + raise ValueError(f"unknown mask kind: {kind}") + if mode == "sync": + span = max(1, int(round(rate * steps))) + if location == "start": + left = 0 + elif location == "end": + left = steps - span + elif location == "middle": + left = (steps - span) // 2 + elif location == "random": + left = int(rng.integers(0, max(1, steps - span + 1))) + else: + raise ValueError(f"unknown interval location: {location}") + right = min(steps - 1, left + span - 1) + for m in selected: + candidates = np.flatnonzero(observed[left:right + 1, m]) + left + amount = min(len(candidates), max_hide(m), target[m]) + if amount: + offset = 0 if location != "end" else len(candidates) - amount + candidates = candidates[max(0, offset):max(0, offset) + amount] + result[candidates, m] = False + else: + common_span = max(1, int(round(rate * steps))) + for rank, m in enumerate(selected): + wanted = target[m] + if wanted <= 0: + continue + cap = max_hide(m) + if span_structure == "multi_short": + hide = _spread_short_spans(observed[:, m], wanted, cap) + elif span_structure != "long": + raise ValueError(f"unknown span structure: {span_structure}") + elif mode == "single" and location != "random": + span = max(1, int(round(rate * steps))) + if location == "start": + left = 0 + elif location == "end": + left = steps - span + elif location == "middle": + left = (steps - span) // 2 + else: + raise ValueError(f"unknown interval location: {location}") + right = min(steps - 1, left + span - 1) + hide = np.zeros(steps, dtype=bool) + candidates = np.flatnonzero(observed[left:right + 1, m]) + left + hide[candidates[:cap]] = True + elif mode in {"partial", "async"}: + if mode == "partial": + base_left = int(rng.integers(0, max(1, steps - common_span + 1))) if location == "random" else ( + 0 if location == "start" else steps - common_span if location == "end" else (steps - common_span) // 2 + ) + offset = int(round(rank * common_span * 0.5)) + else: + base_left = 0 if location == "random" else ( + 0 if location == "start" else steps - common_span if location == "end" else (steps - common_span) // 2 + ) + available = max(1, steps - common_span + 1) + offsets = np.rint(np.linspace(0, max(0, available - 1), len(selected))).astype(int) + if location == "random": + rng.shuffle(offsets) + offset = int(offsets[rank]) + left = min(max(0, base_left + offset), max(0, steps - common_span)) + right = min(steps - 1, left + common_span - 1) + hide = np.zeros(steps, dtype=bool) + candidates = np.flatnonzero(observed[left:right + 1, m]) + left + amount = min(len(candidates), wanted, cap) + if amount: + hide[candidates[:amount]] = True + else: + interval = _best_interval(observed[:, m], wanted, cap, location, rng) + hide = np.zeros(steps, dtype=bool) + if interval is not None: + left, right = interval + candidates = np.flatnonzero(observed[left:right + 1, m]) + left + amount = min(len(candidates), wanted, cap) + if amount: + offset = 0 if location != "end" else len(candidates) - amount + hide[candidates[max(0, offset):max(0, offset) + amount]] = True + result[hide, m] = False + return result + + +def make_scenarios(split: SplitData, seed: int) -> dict[str, np.ndarray]: + scenarios = {"0.0/none": split.mask.copy()} + for rate in MASK_RATES[1:]: + for mode in MASK_MODES: + key = f"{rate:.1f}/{mode}" + masks = [] + for sample_id, original in zip(split.ids, split.mask): + sample_seed = int.from_bytes(hashlib.sha256(f"{seed}:{sample_id}:{key}".encode()).digest()[:8], "little") + masks.append(continuous_mask(original, rate, mode, np.random.default_rng(sample_seed))) + scenarios[key] = np.stack(masks) + + modality_sets = ( + ((0,), "T"), ((1,), "A"), ((2,), "V"), + ((0, 1), "TA"), ((0, 2), "TV"), ((1, 2), "AV"), ((0, 1, 2), "TAV"), + ) + for selected, label in modality_sets: + key = f"0.3/modality_{label}" + scenarios[key] = np.stack([ + continuous_mask( + original, 0.3, "sync", np.random.default_rng(_scenario_seed(seed, sample_id, key)), + modalities=selected, + ) + for sample_id, original in zip(split.ids, split.mask) + ]) + + for modality_index, label in enumerate(("T", "A", "V")): + for location in ("start", "middle", "end"): + key = f"0.3/location_{location}_{label}" + scenarios[key] = np.stack([ + continuous_mask( + original, 0.3, "single", np.random.default_rng(_scenario_seed(seed, sample_id, key)), + modalities=(modality_index,), location=location, + ) + for sample_id, original in zip(split.ids, split.mask) + ]) + for structure in ("long", "multi_short"): + key = f"0.3/span_{structure}_{label}" + scenarios[key] = np.stack([ + continuous_mask( + original, 0.3, "single", np.random.default_rng(_scenario_seed(seed, sample_id, key)), + modalities=(modality_index,), span_structure=structure, + ) + for sample_id, original in zip(split.ids, split.mask) + ]) + + for mode in ("sync", "partial", "async"): + key = f"0.3/synchrony_{mode}" + scenarios[key] = np.stack([ + continuous_mask( + original, 0.3, mode, np.random.default_rng(_scenario_seed(seed, sample_id, key)), + modalities=(0, 1, 2), + ) + for sample_id, original in zip(split.ids, split.mask) + ]) + return scenarios + + +def _scenario_seed(seed: int, sample_id: str, key: str) -> int: + return int.from_bytes(hashlib.sha256(f"{seed}:{sample_id}:{key}".encode()).digest()[:8], "little") + + +def make_reliability_scenarios(split: SplitData, seed: int) -> dict[str, np.ndarray]: + scenarios = {"0.0/natural": split.mask.copy()} + for rate, mode in ((0.3, "single"), (0.3, "sync"), (0.5, "async")): + key = f"{rate:.1f}/{mode}" + scenarios[key] = np.stack([ + continuous_mask(original, rate, mode, np.random.default_rng(_scenario_seed(seed, sample_id, key))) + for sample_id, original in zip(split.ids, split.mask) + ]) + return scenarios + + +def to_device_batch( + arrays: dict[str, np.ndarray], masks: np.ndarray, indices: np.ndarray, device: torch.device, +) -> tuple[list[torch.Tensor], torch.Tensor]: + idx = np.asarray(indices, dtype=np.int64) + xs = [torch.from_numpy(arrays[m][idx]).to(device=device, dtype=torch.float32) for m in MODALITIES] + observed = torch.from_numpy(masks[idx].astype(bool)).to(device=device) + return xs, observed + + +def _betacf(a: torch.Tensor, b: torch.Tensor, x: torch.Tensor, iterations: int = 64) -> torch.Tensor: + """Differentiable continued fraction for the regularized incomplete beta.""" + tiny = 1e-12 + qab, qap, qam = a + b, a + 1.0, a - 1.0 + c = torch.ones_like(x) + d = 1.0 - qab * x / qap + d = 1.0 / torch.where(d.abs() < tiny, torch.full_like(d, tiny), d) + h = d + for m in range(1, iterations + 1): + mf = float(m) + aa = mf * (b - mf) * x / ((qam + 2.0 * mf) * (a + 2.0 * mf)) + d = 1.0 + aa * d + d = 1.0 / torch.where(d.abs() < tiny, torch.full_like(d, tiny), d) + c = 1.0 + aa / torch.where(c.abs() < tiny, torch.full_like(c, tiny), c) + h = h * d * c + aa = -(a + mf) * (qab + mf) * x / ((a + 2.0 * mf) * (qap + 2.0 * mf)) + d = 1.0 + aa * d + d = 1.0 / torch.where(d.abs() < tiny, torch.full_like(d, tiny), d) + c = 1.0 + aa / torch.where(c.abs() < tiny, torch.full_like(c, tiny), c) + h = h * d * c + return h + + +def regularized_beta(x: torch.Tensor, a: torch.Tensor, b: torch.Tensor) -> torch.Tensor: + x_full, a_full, b_full = torch.broadcast_tensors(x, a, b) + safe_x = x_full.clamp(1e-7, 1.0 - 1e-7) + log_bt = torch.lgamma(a_full + b_full) - torch.lgamma(a_full) - torch.lgamma(b_full) + log_bt = log_bt + a_full * torch.log(safe_x) + b_full * torch.log1p(-safe_x) + bt = torch.exp(log_bt.clamp(-80.0, 30.0)) + lower = safe_x < (a_full + 1.0) / (a_full + b_full + 2.0) + direct = bt * _betacf(a_full, b_full, safe_x) / a_full + complement = 1.0 - bt * _betacf(b_full, a_full, 1.0 - safe_x) / b_full + result = torch.where(lower, direct, complement).clamp(0.0, 1.0) + return torch.where(x_full <= 0.0, torch.zeros_like(result), torch.where(x_full >= 1.0, torch.ones_like(result), result)) + + +def supervised_loss_per_sample( + output: dict[str, Any], class_y: torch.Tensor, regression_y: torch.Tensor, +) -> tuple[torch.Tensor, dict[str, torch.Tensor]]: + probs = output["class_probs_by_path"].clamp_min(1e-8) + beta = output["beta_params"].clamp_min(1e-4) + path_count, batch = probs.shape[:2] + negative = class_y == 0 + neutral = class_y == 1 + positive = class_y == 2 + u = (regression_y.abs() / 3.0).clamp(0.0, 1.0) + lo = (u - DELTA_U).clamp(0.0, 1.0) + hi = (u + DELTA_U).clamp(0.0, 1.0) + neutral_mass = probs[:, :, 1] + neg_params = beta[:, :, 0, :] + pos_params = beta[:, :, 1, :] + cdf_hi_neg = regularized_beta(hi.unsqueeze(0), neg_params[..., 0], neg_params[..., 1]) + cdf_lo_neg = regularized_beta(lo.unsqueeze(0), neg_params[..., 0], neg_params[..., 1]) + cdf_hi_pos = regularized_beta(hi.unsqueeze(0), pos_params[..., 0], pos_params[..., 1]) + cdf_lo_pos = regularized_beta(lo.unsqueeze(0), pos_params[..., 0], pos_params[..., 1]) + neg_mass = probs[:, :, 0] * (cdf_hi_neg - cdf_lo_neg).clamp_min(1e-12) + pos_mass = probs[:, :, 2] * (cdf_hi_pos - cdf_lo_pos).clamp_min(1e-12) + selected = torch.where(neutral.unsqueeze(0), neutral_mass, torch.where(negative.unsqueeze(0), neg_mass, pos_mass)) + mixture_mass = selected.mean(dim=0).clamp_min(1e-12) + nll = -torch.log(mixture_mass) + beta_mean = beta[..., 0] / beta.sum(dim=-1) + conditional = 3.0 * (probs[:, :, 2] * beta_mean[:, :, 1] - probs[:, :, 0] * beta_mean[:, :, 0]) + mean_score = conditional.mean(dim=0) + scaled_error = (regression_y - mean_score) / 3.0 + huber = F.huber_loss(scaled_error, torch.zeros_like(scaled_error), reduction="none", delta=0.25) + total = nll + LAMBDA_Y * huber + return total, {"nll": nll, "huber": huber, "mean_score": mean_score} + + +def reconstruction_loss_per_sample( + output: dict[str, Any], xs: list[torch.Tensor], hidden: torch.Tensor, +) -> torch.Tensor: + batch = hidden.shape[0] + per_modal = [] + for m, prediction in enumerate(output["reconstructions"]): + target = xs[m].unsqueeze(0) + error = (prediction - target).abs().mean(dim=-1) + mask = hidden[:, :, m].float().unsqueeze(0) + numerator = (error * mask).sum(dim=(0, 2)) + denominator = mask.sum(dim=(0, 2)).clamp_min(1.0) + per_modal.append(numerator / denominator) + values = torch.stack(per_modal, dim=-1) + active = torch.stack([hidden[:, :, m].any(dim=1) for m in range(len(MODALITIES))], dim=-1).float() + return (values * active).sum(dim=-1) / active.sum(dim=-1).clamp_min(1.0) + + +def _regularized_logits(probabilities: np.ndarray, temperature: float) -> np.ndarray: + logp = np.log(np.clip(probabilities, 1e-12, 1.0)) / temperature + logp -= logp.max(axis=1, keepdims=True) + exp = np.exp(logp) + return exp / exp.sum(axis=1, keepdims=True) + + +def _decode_mixture( + probabilities_by_path: np.ndarray, + beta_params: np.ndarray, + temperature: float = 1.0, +) -> tuple[np.ndarray, np.ndarray, np.ndarray]: + pbar = _regularized_logits(probabilities_by_path.mean(axis=0), temperature) + maximum = pbar.max(axis=1, keepdims=True) + ties = np.isclose(pbar, maximum, rtol=0.0, atol=1e-12) + predicted_class = np.asarray([next(c for c in (1, 0, 2) if row[c]) for row in ties], dtype=np.int64) + score = np.zeros(len(predicted_class), dtype=np.float32) + for i, cls in enumerate(predicted_class): + if cls == 1: + continue + sign_index = 0 if cls == 0 else 1 + weights = probabilities_by_path[:, i, cls] + params = beta_params[:, i, sign_index] + denominator = float(weights.sum()) + if denominator <= 1e-12: + magnitude = 0.5 + else: + low, high = 0.0, 1.0 + for _ in range(48): + middle = (low + high) / 2.0 + cdf = float(np.dot(weights, betainc(params[:, 0], params[:, 1], middle)) / denominator) + if cdf < 0.5: + low = middle + else: + high = middle + magnitude = (low + high) / 2.0 + score[i] = (-3.0 if cls == 0 else 3.0) * magnitude + return pbar, predicted_class, score + + +def _predictive_intervals( + probabilities_by_path: np.ndarray, + beta_params: np.ndarray, + temperature: float, + quantiles: tuple[float, float] = (0.05, 0.95), +) -> tuple[np.ndarray, np.ndarray]: + """Central intervals of the calibrated signed point-mass/Beta mixture.""" + pbar = _regularized_logits(probabilities_by_path.mean(axis=0), temperature) + lower = np.empty(len(pbar), dtype=np.float32) + upper = np.empty(len(pbar), dtype=np.float32) + for i, marginal in enumerate(pbar): + negative_weight = probabilities_by_path[:, i, 0].astype(np.float64) + positive_weight = probabilities_by_path[:, i, 2].astype(np.float64) + negative_weight /= negative_weight.sum() + positive_weight /= positive_weight.sum() + negative = beta_params[:, i, 0].astype(np.float64) + positive = beta_params[:, i, 1].astype(np.float64) + + def cdf(value: float) -> float: + if value < 0.0: + magnitude_threshold = min(1.0, max(0.0, -value / 3.0)) + conditional = np.dot( + negative_weight, + 1.0 - betainc(negative[:, 0], negative[:, 1], magnitude_threshold), + ) + return float(marginal[0] * conditional) + magnitude_threshold = min(1.0, max(0.0, value / 3.0)) + conditional = np.dot( + positive_weight, + betainc(positive[:, 0], positive[:, 1], magnitude_threshold), + ) + return float(marginal[0] + marginal[1] + marginal[2] * conditional) + + for slot, quantile in enumerate(quantiles): + lo, hi = -3.0, 3.0 + for _ in range(52): + mid = (lo + hi) / 2.0 + if cdf(mid) >= quantile: + hi = mid + else: + lo = mid + if slot == 0: + lower[i] = hi + else: + upper[i] = hi + return lower, upper + + +def _trajectory_variance_components( + probabilities_by_path: np.ndarray, + beta_params: np.ndarray, +) -> tuple[np.ndarray, np.ndarray, np.ndarray]: + """Verify Var(Y)=E_b Var(Y|b)+Var_b(E[Y|b]) before class calibration.""" + probs = np.asarray(probabilities_by_path, dtype=np.float64) + beta = np.asarray(beta_params, dtype=np.float64) + mean = beta[..., 0] / beta.sum(axis=-1) + second = beta[..., 0] * (beta[..., 0] + 1.0) / (beta.sum(axis=-1) * (beta.sum(axis=-1) + 1.0)) + path_mean = 3.0 * (probs[..., 2] * mean[..., 1] - probs[..., 0] * mean[..., 0]) + path_second = 9.0 * (probs[..., 2] * second[..., 1] + probs[..., 0] * second[..., 0]) + conditional_variance = np.maximum(0.0, path_second - np.square(path_mean)) + within = conditional_variance.mean(axis=0) + between = path_mean.var(axis=0) + total = within + between + return total.astype(np.float32), within.astype(np.float32), between.astype(np.float32) + + +def _calibrated_mixture_moments( + probabilities_by_path: np.ndarray, + beta_params: np.ndarray, + temperature: float, +) -> tuple[np.ndarray, np.ndarray]: + """Recompute mean and variance after temperature calibration of class mass.""" + pcal = _regularized_logits(probabilities_by_path.mean(axis=0), temperature) + beta = np.asarray(beta_params, dtype=np.float64) + raw_probs = np.asarray(probabilities_by_path, dtype=np.float64) + beta_mean = beta[..., 0] / beta.sum(axis=-1) + beta_second = beta[..., 0] * (beta[..., 0] + 1.0) / (beta.sum(axis=-1) * (beta.sum(axis=-1) + 1.0)) + conditional_mean = np.zeros((raw_probs.shape[1], 2), dtype=np.float64) + conditional_second = np.zeros((raw_probs.shape[1], 2), dtype=np.float64) + for sign_index, class_index in enumerate((0, 2)): + weights = raw_probs[:, :, class_index] + weights = weights / weights.sum(axis=0, keepdims=True) + conditional_mean[:, sign_index] = np.sum(weights * beta_mean[:, :, sign_index], axis=0) + conditional_second[:, sign_index] = np.sum(weights * beta_second[:, :, sign_index], axis=0) + mean = 3.0 * (pcal[:, 2] * conditional_mean[:, 1] - pcal[:, 0] * conditional_mean[:, 0]) + second = 9.0 * (pcal[:, 2] * conditional_second[:, 1] + pcal[:, 0] * conditional_second[:, 0]) + variance = np.maximum(0.0, second - np.square(mean)) + return mean.astype(np.float32), variance.astype(np.float32) + + +def calculate_metrics( + y_cls: np.ndarray, + y_reg: np.ndarray, + probs: np.ndarray, + pred_cls: np.ndarray, + pred_reg: np.ndarray, + selection_nll: float | None = None, + interval_lower: np.ndarray | None = None, + interval_upper: np.ndarray | None = None, + variance_components: tuple[np.ndarray, np.ndarray, np.ndarray] | None = None, + calibrated_moments: tuple[np.ndarray, np.ndarray] | None = None, +) -> dict[str, Any]: + p = np.clip(probs, 1e-8, 1.0) + onehot = np.eye(3, dtype=np.float64)[y_cls] + nll = float(-np.log(p[np.arange(len(y_cls)), y_cls]).mean()) + confidence = p.max(axis=1) + correct = (pred_cls == y_cls).astype(np.float64) + ece = 0.0 + for left in np.linspace(0, 1, 16)[:-1]: + right = left + 1 / 15 + selected = (confidence >= left) & (confidence < right if right < 1 else confidence <= right) + if selected.any(): + ece += selected.mean() * abs(confidence[selected].mean() - correct[selected].mean()) + pearson = float(pearsonr(y_reg, pred_reg).statistic) if np.std(y_reg) > 0 and np.std(pred_reg) > 0 else float("nan") + support = np.bincount(y_cls.astype(int), minlength=3) + result = { + "n": int(len(y_cls)), + "accuracy": float(accuracy_score(y_cls, pred_cls)), + "macro_f1": float(f1_score(y_cls, pred_cls, labels=[0, 1, 2], average="macro", zero_division=0)), + "negative_support": int(support[0]), + "neutral_support": int(support[1]), + "positive_support": int(support[2]), + "negative_recall": float(recall_score(y_cls, pred_cls, labels=[0], average="macro", zero_division=0)), + "middle_recall": float(recall_score(y_cls, pred_cls, labels=[1], average="macro", zero_division=0)), + "positive_recall": float(recall_score(y_cls, pred_cls, labels=[2], average="macro", zero_division=0)), + "regression_mae": float(mean_absolute_error(y_reg, pred_reg)), + "regression_rmse": float(np.sqrt(mean_squared_error(y_reg, pred_reg))), + "pearson": pearson, + "brier": float(np.square(probs - onehot).sum(axis=1).mean()), + "classification_nll": nll, + "ece_15": float(ece), + } + if selection_nll is not None: + result["selection_nll"] = float(selection_nll) + if interval_lower is not None and interval_upper is not None: + result["interval_90_coverage"] = float(np.mean((y_reg >= interval_lower) & (y_reg <= interval_upper))) + result["interval_90_mean_width"] = float(np.mean(interval_upper - interval_lower)) + if variance_components is not None: + total, within, between = variance_components + result["predictive_variance_mean_uncalibrated"] = float(np.mean(total)) + result["within_trajectory_variance_mean"] = float(np.mean(within)) + result["between_trajectory_variance_mean"] = float(np.mean(between)) + if calibrated_moments is not None: + calibrated_mean, calibrated_variance = calibrated_moments + result["predictive_mean_mean_calibrated"] = float(np.mean(calibrated_mean)) + result["predictive_variance_mean_calibrated"] = float(np.mean(calibrated_variance)) + return result + + +def evaluate( + model: CRG, + arrays: dict[str, np.ndarray], + split: SplitData, + device: torch.device, + batch_size: int, + *, + masks: np.ndarray | None = None, + temperature: float = 1.0, + collect_gate_diagnostics: bool = False, +) -> tuple[dict[str, Any], dict[str, np.ndarray]]: + model.eval() + source_masks = split.mask if masks is None else np.asarray(masks, dtype=bool) + prob_paths, beta_paths, loss_parts = [], [], [] + gate_parts: dict[str, list[np.ndarray]] = { + "fusion_weights": [], "null_weights": [], "time_pool_weights": [], "reliability": [], + "imputation_uncertainty": [], "gap": [], "span": [], "distance_before": [], "distance_after": [], + } + with torch.inference_mode(): + for start in range(0, split.n, batch_size): + idx = np.arange(start, min(split.n, start + batch_size)) + xs, observed = to_device_batch(arrays, source_masks, idx, device) + out = model(xs, observed, paths=16 if model.use_joint_draws else 1, joint_draws=model.use_joint_draws) + prob_paths.append(out["class_probs_by_path"].cpu().numpy()) + beta_paths.append(out["beta_params"].cpu().numpy()) + if collect_gate_diagnostics: + for name, key in (("fusion_weights", "fusion_weights_by_path"), + ("null_weights", "null_weights_by_path"), + ("time_pool_weights", "time_pool_weights_by_path")): + gate_parts[name].append(out[key].mean(dim=0).cpu().numpy()) + for name in ("reliability", "imputation_uncertainty", "gap", "span", "distance_before", "distance_after"): + gate_parts[name].append(out[name].cpu().numpy()) + cy = torch.from_numpy(split.class_y[idx]).to(device) + ry = torch.from_numpy(split.regression_y[idx]).to(device) + nll, _ = supervised_loss_per_sample(out, cy, ry) + loss_parts.append(nll.cpu().numpy()) + ppaths = np.concatenate(prob_paths, axis=1) + betas = np.concatenate(beta_paths, axis=1) + probs, pred_class, pred_score = _decode_mixture(ppaths, betas, temperature) + interval_lower, interval_upper = _predictive_intervals(ppaths, betas, temperature) + variance_components = _trajectory_variance_components(ppaths, betas) + calibrated_moments = _calibrated_mixture_moments(ppaths, betas, temperature) + metrics = calculate_metrics( + split.class_y, split.regression_y, probs, pred_class, pred_score, + float(np.mean(np.concatenate(loss_parts))), interval_lower, interval_upper, variance_components, + calibrated_moments, + ) + predictions = { + "probabilities": probs, + "probabilities_by_path": ppaths, + "beta_params": betas, + "predicted_class": pred_class, + "predicted_score": pred_score, + "interval_lower": interval_lower, + "interval_upper": interval_upper, + "predictive_variance_uncalibrated": variance_components[0], + "within_trajectory_variance": variance_components[1], + "between_trajectory_variance": variance_components[2], + "predictive_mean_calibrated": calibrated_moments[0], + "predictive_variance_calibrated": calibrated_moments[1], + } + if collect_gate_diagnostics: + predictions.update({name: np.concatenate(values, axis=0) for name, values in gate_parts.items()}) + return metrics, predictions + + +def gate_diagnostic_rows(split: SplitData, predictions: dict[str, np.ndarray]) -> list[dict[str, Any]]: + required = {"fusion_weights", "null_weights", "time_pool_weights", "reliability", + "imputation_uncertainty", "gap", "span", "distance_before", "distance_after"} + if not required.issubset(predictions): + raise ValueError(f"missing gate diagnostic arrays: {sorted(required - set(predictions))}") + rows = [] + for sample_index, sample_id in enumerate(split.ids): + for step in range(split.mask.shape[1]): + for modality_index, modality in enumerate(MODALITIES): + rows.append({ + "sample_id": sample_id, + "video_id": split.groups[sample_index], + "step": step, + "relative_position": step / max(1, split.mask.shape[1] - 1), + "modality": modality, + "observed": bool(split.mask[sample_index, step, modality_index]), + "fusion_weight_mean_over_paths": float(predictions["fusion_weights"][sample_index, step, modality_index]), + "null_weight_mean_over_paths": float(predictions["null_weights"][sample_index, step]), + "reliability": float(predictions["reliability"][sample_index, step, modality_index]), + "imputation_uncertainty": float(predictions["imputation_uncertainty"][sample_index, step, modality_index]), + "nearest_observation_gap": float(predictions["gap"][sample_index, step, modality_index]), + "continuous_missing_span": float(predictions["span"][sample_index, step, modality_index]), + "distance_before": float(predictions["distance_before"][sample_index, step, modality_index]), + "distance_after": float(predictions["distance_after"][sample_index, step, modality_index]), + "time_pool_weight_mean_over_paths": float(predictions["time_pool_weights"][sample_index, step]), + }) + return rows + + +def fit_temperature(probabilities: np.ndarray, class_y: np.ndarray) -> float: + def objective(log_temperature: float) -> float: + p = _regularized_logits(probabilities, float(np.exp(log_temperature))) + return float(-np.log(np.clip(p[np.arange(len(class_y)), class_y], 1e-12, 1.0)).mean()) + + fitted = minimize_scalar(objective, bounds=(-2.0, 2.0), method="bounded", options={"xatol": 1e-5}) + return float(np.exp(fitted.x)) + + +def _group_ids(original_mask: np.ndarray, hidden_mask: np.ndarray) -> np.ndarray: + # Group by which sources received new artificial gaps, not only by sources + # that were erased completely (the mask design deliberately preserves 20%). + original = np.asarray(original_mask, dtype=bool) + current = np.asarray(hidden_mask, dtype=bool) + hidden_mod = (original & ~current).any(axis=1) + bits = hidden_mod[:, 0].astype(int) + 2 * hidden_mod[:, 1].astype(int) + 4 * hidden_mod[:, 2].astype(int) + # PDF (5.62): total missing rate is computed per source on the valid time + # axis, then averaged equally across T/A/V (never weighted by feature size + # or by the number of naturally observed rows). + final_missing_by_modality = 1.0 - current.mean(axis=1) + realized_rate = final_missing_by_modality.mean(axis=1) + coarse = np.where(realized_rate <= 0.2, 0, np.where(realized_rate <= 0.5, 1, 2)) + return bits * 3 + coarse + + +def _missing_rate_summary(original: np.ndarray, current: np.ndarray) -> dict[str, Any]: + """Return PDF (5.62)–(5.63) rates, with equal modality weighting.""" + original = np.asarray(original, dtype=bool) + current = np.asarray(current, dtype=bool) + if original.shape != current.shape or original.ndim not in (2, 3): + raise ValueError("mask rate inputs must have matching [T,M] or [N,T,M] shapes") + newly_hidden = original & ~current + natural = 1.0 - original.mean(axis=-2) + final = 1.0 - current.mean(axis=-2) + observed_count = original.sum(axis=-2) + additional_count = newly_hidden.sum(axis=-2) + additional = np.divide( + additional_count, observed_count, + out=np.full(np.shape(additional_count), np.nan, dtype=np.float64), + where=observed_count > 0, + ) + synchronous = (~current.any(axis=-1)).mean(axis=-1) + return { + "natural_by_modality": natural, + "additional_by_modality": additional, + "final_by_modality": final, + "natural_global": float(np.mean(natural)), + "additional_global": float(np.nanmean(additional)), + "final_global": float(np.mean(final)), + "synchronous_no_observation": synchronous, + } + + +def smooth_group_risk( + losses: torch.Tensor, + group_ids: np.ndarray, + lambda_group: float = LAMBDA_GROUP, + group_temperature: float = GROUP_TEMPERATURE, +) -> torch.Tensor: + gids = torch.as_tensor(group_ids, device=losses.device, dtype=torch.long) + unique = torch.unique(gids) + group_losses, priors = [], [] + for group in unique: + selected = gids == group + group_losses.append(losses[selected].mean()) + priors.append(selected.float().mean()) + values = torch.stack(group_losses) + prior = torch.stack(priors).clamp_min(1e-8) + expected = (prior * values).sum() + worst = group_temperature * torch.logsumexp(torch.log(prior) + values / group_temperature, dim=0) + return (1.0 - lambda_group) * expected + lambda_group * worst + + +def _distillation_per_sample( + student: dict[str, Any], teacher: dict[str, Any], original: np.ndarray, current: np.ndarray, +) -> torch.Tensor: + temp = DISTILL_TEMPERATURE + p_teacher = teacher["tempered_probs_by_path"].mean(dim=0).detach().clamp_min(1e-8) + p_student = student["tempered_probs_by_path"].mean(dim=0).clamp_min(1e-8) + entropy = -(p_teacher * p_teacher.log()).sum(dim=-1) + confidence_weight = (1.0 - entropy / math.log(3.0)).clamp(0.0, 1.0) + retain_by_modality = [] + orig_t = torch.as_tensor(original, device=p_teacher.device, dtype=torch.float32) + curr_t = torch.as_tensor(current, device=p_teacher.device, dtype=torch.float32) + for m in range(len(MODALITIES)): + denominator = orig_t[:, :, m].sum(dim=1) + retained = (orig_t[:, :, m] * curr_t[:, :, m]).sum(dim=1) / denominator.clamp_min(1.0) + retain_by_modality.append(torch.where(denominator > 0, retained, torch.ones_like(retained))) + retain = torch.stack(retain_by_modality, dim=-1).mean(dim=-1) + weight = confidence_weight * retain + kl = (p_teacher * (p_teacher.log() - p_student.log())).sum(dim=-1) * temp * temp + teacher_score = teacher["mixed_score"].detach() + student_score = student["mixed_score"] + reg = F.huber_loss((teacher_score - student_score) / 3.0, torch.zeros_like(teacher_score), reduction="none", delta=0.25) + return weight * (kl + reg) + + +def fit_imputer( + imputer: StructuredGaussianImputer, + arrays: dict[str, np.ndarray], + split: SplitData, + device: torch.device, + epochs: int, + batch_size: int, + seed: int, +) -> list[dict[str, float]]: + imputer.train() + optimizer = torch.optim.AdamW(imputer.parameters(), lr=3e-4, weight_decay=1e-4) + rng = np.random.default_rng(seed) + history = [] + for epoch in range(1, epochs + 1): + order = rng.permutation(split.n) + losses = [] + for start in range(0, split.n, batch_size): + idx = order[start:start + batch_size] + xs, observed = to_device_batch(arrays, split.mask, idx, device) + nll = imputer.observed_nll(xs, observed).mean() + observed_scalars = sum(observed[:, :, m].sum(dim=1).float() * INPUT_DIMS[m] for m in range(len(MODALITIES))) + emission_penalty = sum(value.square().mean() for value in imputer.emissions()) + transition_penalty = imputer._transition().square().mean() + loss = nll / observed_scalars.mean().clamp_min(1.0) + loss = loss + LAMBDA_EMISSION * emission_penalty + LAMBDA_TRANSITION * transition_penalty + optimizer.zero_grad(set_to_none=True) + loss.backward() + torch.nn.utils.clip_grad_norm_(imputer.parameters(), 5.0) + optimizer.step() + losses.append(float(loss.detach().cpu())) + row = {"stage": "structured_imputer", "epoch": epoch, "train_observed_nll_per_scalar": float(np.mean(losses))} + history.append(row) + print(f"imputer {epoch}/{epochs}: observed_nll/scalar={row['train_observed_nll_per_scalar']:.4f}", flush=True) + imputer.eval() + for parameter in imputer.parameters(): + parameter.requires_grad_(False) + return history + + +def _make_variant( + name: str, + imputer: StructuredGaussianImputer, + reliability_hparams: tuple[float, float, float, float] = DEFAULT_RELIABILITY, +) -> CRG: + if name == "C1": + flags = dict(use_imputer=False, use_joint_draws=False, use_final_gate=False, use_source_attention=False, reliability_update=False, use_low_rank=False) + elif name == "C2": + flags = dict(use_imputer=True, use_joint_draws=False, use_final_gate=False, use_source_attention=False, reliability_update=False, use_low_rank=False) + elif name == "C3": + flags = dict(use_imputer=True, use_joint_draws=True, use_final_gate=True, use_source_attention=False, reliability_update=False, use_low_rank=False) + elif name == "C4": + flags = dict(use_imputer=True, use_joint_draws=True, use_final_gate=True, use_source_attention=True, reliability_update=False, use_low_rank=False) + else: + flags = dict(use_imputer=True, use_joint_draws=True, use_final_gate=True, use_source_attention=True, + reliability_update=True, use_low_rank=name == "C6" or name.startswith("C7")) + return CRG(copy.deepcopy(imputer), reliability_hparams=reliability_hparams, **flags) + + +def _set_reliability_hparams(model: CRG, values: tuple[float, float, float, float]) -> None: + rho_imp, lambda_u, lambda_gap, lambda_span = values + if not 0.0 < rho_imp < 1.0 or min(lambda_u, lambda_gap, lambda_span) < 0.0: + raise ValueError("invalid reliability hyperparameters") + with torch.no_grad(): + model.rho_imp.fill_(rho_imp) + model.rel_u.fill_(lambda_u) + model.rel_gap.fill_(lambda_gap) + model.rel_span.fill_(lambda_span) + + +def tune_reliability_hparams( + model: CRG, + arrays: dict[str, np.ndarray], + split: SplitData, + scenarios: dict[str, np.ndarray], + device: torch.device, + batch_size: int, + model_name: str, + seed: int = SEED + 551, + candidate_values: tuple[tuple[float, float, float, float], ...] = RELIABILITY_CANDIDATES, +) -> tuple[tuple[float, float, float, float], list[dict[str, Any]]]: + if not (model.use_final_gate or model.use_source_attention or model.reliability_update): + return DEFAULT_RELIABILITY, [{"model": model_name, "selected": True, + "rho_imp": DEFAULT_RELIABILITY[0], "lambda_u": DEFAULT_RELIABILITY[1], + "lambda_gap": DEFAULT_RELIABILITY[2], "lambda_span": DEFAULT_RELIABILITY[3], + "inner_selection_nll": float("nan"), "note": "not used by this ablation"}] + rows = [] + best_values, best_loss = DEFAULT_RELIABILITY, float("inf") + if not candidate_values: + raise ValueError("at least one reliability candidate is required") + for values in candidate_values: + _set_reliability_hparams(model, values) + scenario_losses: dict[str, float] = {} + for scenario, masks in scenarios.items(): + with fixed_torch_seed(_scenario_seed(seed, split.name, scenario), device): + metrics, _ = evaluate(model, arrays, split, device, batch_size, masks=masks) + scenario_losses[scenario] = float(metrics["selection_nll"]) + score = float(np.mean(list(scenario_losses.values()))) + row = {"model": model_name, "rho_imp": values[0], "lambda_u": values[1], + "lambda_gap": values[2], "lambda_span": values[3], "inner_selection_nll": score, + "scenario_selection_nll": json.dumps(scenario_losses, sort_keys=True), + "selected": False, "selection_split": split.name} + rows.append(row) + if score < best_loss: + best_loss, best_values = score, values + _set_reliability_hparams(model, best_values) + for row in rows: + row["selected"] = (row["rho_imp"], row["lambda_u"], row["lambda_gap"], row["lambda_span"]) == best_values + return best_values, rows + + +def tune_group_risk_model( + imputer: StructuredGaussianImputer, + train: SplitData, + valid: SplitData, + arrays: dict[str, dict[str, np.ndarray]], + reliability_validation: SplitData, + reliability_arrays: dict[str, np.ndarray], + reliability_scenarios: dict[str, np.ndarray], + device: torch.device, + epochs: int, + batch_size: int, + patience: int, + seed: int, +) -> tuple[CRG, list[dict[str, float]], list[dict[str, Any]], list[dict[str, Any]], tuple[float, float, float, float], tuple[float, float], float]: + candidates = [] + all_history: list[dict[str, float]] = [] + all_reliability_rows: list[dict[str, Any]] = [] + risk_rows: list[dict[str, Any]] = [] + for candidate_index, (group_lambda, group_temperature) in enumerate(GROUP_RISK_CANDIDATES): + candidate_name = f"C7_group_lambda{group_lambda:.2f}_tau{group_temperature:.2f}" + model = _make_variant("C7_group", imputer) + with fixed_torch_seed(seed + 303, device): + model, history = _fit_neural( + model, candidate_name, train, valid, arrays, device, epochs, batch_size, patience, + np.random.default_rng(seed + 303), use_group_risk=True, + group_lambda=group_lambda, group_temperature=group_temperature, + selection_split=reliability_validation, selection_arrays=reliability_arrays, + selection_scenarios=reliability_scenarios, + ) + all_history.extend(history) + selected_reliability, tuning_rows = tune_reliability_hparams( + model, reliability_arrays, reliability_validation, reliability_scenarios, + device, batch_size, candidate_name, seed=seed + 551, + ) + selected_row = next(row for row in tuning_rows if row.get("selected")) + inner_score = float(selected_row["inner_selection_nll"]) + for row in tuning_rows: + row["group_lambda"] = group_lambda + row["group_temperature"] = group_temperature + row["risk_candidate_selected"] = False + row["candidate"] = row["model"] + row["model"] = "C7_group" + all_reliability_rows.extend(tuning_rows) + candidates.append((inner_score, model, selected_reliability, (group_lambda, group_temperature), candidate_name)) + risk_rows.append({"model": "C7_group", "candidate": candidate_name, + "lambda_group": group_lambda, "group_temperature": group_temperature, + "selected_reliability": selected_reliability, + "inner_selection_nll": inner_score, "selected": False, + "selection_split": reliability_validation.name}) + best = min(candidates, key=lambda row: row[0]) + score, model, selected_reliability, selected_group, candidate_name = best + for row in all_reliability_rows: + row["risk_candidate_selected"] = row["candidate"] == candidate_name + row["selected"] = bool(row.get("selected") and row["risk_candidate_selected"]) + for row in risk_rows: + row["selected"] = row["candidate"] == candidate_name + if row["selected"]: + row["selected"] = True + return model, all_history, all_reliability_rows, risk_rows, selected_reliability, selected_group, score + + +def _fit_neural( + model: CRG, + name: str, + train: SplitData, + valid: SplitData, + arrays: dict[str, dict[str, np.ndarray]], + device: torch.device, + epochs: int, + batch_size: int, + patience: int, + rng: np.random.Generator, + *, + teacher: CRG | None = None, + use_group_risk: bool = False, + group_lambda: float = LAMBDA_GROUP, + group_temperature: float = GROUP_TEMPERATURE, + selection_split: SplitData | None = None, + selection_arrays: dict[str, np.ndarray] | None = None, + selection_scenarios: dict[str, np.ndarray] | None = None, + mask_kind: str = "continuous", + use_reconstruction: bool = True, +) -> tuple[CRG, list[dict[str, float]]]: + model.to(device) + model.imputer.eval() + for parameter in model.imputer.parameters(): + parameter.requires_grad_(False) + if teacher is not None: + teacher.eval() + for parameter in teacher.parameters(): + parameter.requires_grad_(False) + optimizer = torch.optim.AdamW([p for p in model.parameters() if p.requires_grad], lr=3e-4, weight_decay=1e-3) + best_loss, best_state, stale = float("inf"), None, 0 + history: list[dict[str, float]] = [] + rate_choices = np.asarray(MASK_RATES, dtype=np.float64) + pattern_choices = np.asarray(MASK_MODES, dtype=object) + for epoch in range(1, epochs + 1): + model.train() + order = rng.permutation(train.n) + epoch_losses = [] + for start in range(0, train.n, batch_size): + idx = order[start:start + batch_size] + xs, natural = to_device_batch(arrays["fit"], train.mask, idx, device) + if name == "teacher": + rates = np.zeros(len(idx), dtype=np.float64) + modes = ["none"] * len(idx) + else: + rates = rng.choice(rate_choices, size=len(idx), p=np.asarray([0.2] * 5)) + modes = rng.choice(pattern_choices, size=len(idx)).tolist() + masks_np = np.stack([ + continuous_mask(train.mask[int(i)], float(rate), str(mode), rng, kind=mask_kind) + for i, rate, mode in zip(idx, rates, modes) + ]) + current = torch.as_tensor(masks_np, device=device, dtype=torch.bool) + class_y = torch.as_tensor(train.class_y[idx], device=device, dtype=torch.long) + regression_y = torch.as_tensor(train.regression_y[idx], device=device, dtype=torch.float32) + output = model(xs, current, paths=4 if model.use_joint_draws else 1, joint_draws=model.use_joint_draws) + supervised, _ = supervised_loss_per_sample(output, class_y, regression_y) + hidden_np = train.mask[idx] & ~masks_np + hidden = torch.as_tensor(hidden_np, device=device, dtype=torch.bool) + reconstruction = reconstruction_loss_per_sample(output, xs, hidden) + per_sample = supervised + (LAMBDA_RECON * reconstruction if use_reconstruction else 0.0) + if teacher is not None: + with torch.no_grad(): + teacher_output = teacher(xs, natural, paths=4, joint_draws=True) + distill = _distillation_per_sample( output, teacher_output, train.mask[idx], masks_np) + per_sample = per_sample + LAMBDA_DISTILL * distill + if use_group_risk: + group_ids = _group_ids(train.mask[idx], masks_np) + loss = smooth_group_risk(per_sample, group_ids, group_lambda, group_temperature) + else: + loss = per_sample.mean() + optimizer.zero_grad(set_to_none=True) + loss.backward() + torch.nn.utils.clip_grad_norm_([p for p in model.parameters() if p.requires_grad], 1.0) + optimizer.step() + epoch_losses.append(float(loss.detach().cpu())) + if selection_split is not None and selection_arrays is not None and selection_scenarios: + selected_metrics = {} + for scenario, masks in selection_scenarios.items(): + scenario_metrics, _ = evaluate(model, selection_arrays, selection_split, device, batch_size, masks=masks) + selected_metrics[scenario] = scenario_metrics + val_loss = float(np.mean([metrics["selection_nll"] for metrics in selected_metrics.values()])) + natural_metrics = next((metrics for key, metrics in selected_metrics.items() + if key.startswith("0.0/") or key.endswith("natural")), + next(iter(selected_metrics.values()))) + selection_source = "group_disjoint_internal_scenarios" + else: + natural_metrics, _ = evaluate(model, arrays["valid"], valid, device, batch_size) + val_loss = float(natural_metrics["selection_nll"]) + selection_source = "official_valid_fallback" + row = {"stage": name, "epoch": epoch, "train_loss": float(np.mean(epoch_losses)), + "inner_selection_nll": val_loss, "inner_natural_accuracy": natural_metrics["accuracy"], + "inner_natural_macro_f1": natural_metrics["macro_f1"], + "inner_natural_mae": natural_metrics["regression_mae"], + "selection_source": selection_source} + history.append(row) + print(f"{name} {epoch}/{epochs}: train={row['train_loss']:.4f} innerNLL={val_loss:.4f} " + f"acc={row['inner_natural_accuracy']:.4f} macroF1={row['inner_natural_macro_f1']:.4f}", flush=True) + if val_loss < best_loss: + best_loss, best_state, stale = val_loss, copy.deepcopy(model.state_dict()), 0 + else: + stale += 1 + if stale >= patience: + break + if best_state is not None: + model.load_state_dict(best_state) + model.eval() + return model, history + + +def _sample_statistics( + split: SplitData, arrays: dict[str, np.ndarray], indices: np.ndarray, masks: np.ndarray | None = None, +) -> np.ndarray: + parts = [] + effective_mask = split.mask if masks is None else np.asarray(masks, dtype=bool) + for modality_index, modality in enumerate(MODALITIES): + x = arrays[modality][indices] + mask = effective_mask[indices, :, modality_index] + count = mask.sum(axis=1, keepdims=True) + mean = (x * mask[:, :, None]).sum(axis=1) / np.maximum(count, 1) + variance = (((x - mean[:, None, :]) ** 2) * mask[:, :, None]).sum(axis=1) / np.maximum(count, 1) + missing = 1.0 - mask.mean(axis=1, keepdims=True) + max_gap = [] + for row in mask: + longest = current = 0 + for visible in row: + current = 0 if visible else current + 1 + longest = max(longest, current) + max_gap.append(longest / max(1, len(row))) + parts.extend((mean, np.sqrt(variance), missing, np.asarray(max_gap, np.float32)[:, None])) + return np.concatenate(parts, axis=1).astype(np.float32) + + +def fit_c0( + train: SplitData, + valid: SplitData, + arrays: dict[str, dict[str, np.ndarray]], +) -> tuple[dict[str, Any], dict[str, Any]]: + train_x = _sample_statistics(train, arrays["fit"], np.arange(train.n)) + classifier = LogisticRegression(C=0.05, max_iter=2500, random_state=SEED) + classifier.fit(train_x, train.class_y) + regressor = Ridge(alpha=25.0) + regressor.fit(train_x, train.regression_y) + return {}, {"classifier": classifier, "regressor": regressor} + + +def calibrate_c0_interval( + state: dict[str, Any], + calibration: SplitData, + arrays: dict[str, np.ndarray], +) -> None: + features = _sample_statistics(calibration, arrays, np.arange(calibration.n)) + residual = calibration.regression_y - state["regressor"].predict(features) + state["residual_q05"], state["residual_q95"] = ( + float(np.quantile(residual, 0.05)), float(np.quantile(residual, 0.95)) + ) + + +def evaluate_c0( + state: dict[str, Any], split: SplitData, arrays: dict[str, np.ndarray], + temperature: float = 1.0, masks: np.ndarray | None = None, +) -> tuple[dict[str, Any], dict[str, np.ndarray]]: + features = _sample_statistics(split, arrays, np.arange(split.n), masks) + classifier, regressor = state["classifier"], state["regressor"] + raw = np.zeros((split.n, 3), np.float64) + raw[:, classifier.classes_] = classifier.predict_proba(features) + probs = _regularized_logits(raw, temperature) + maximum = probs.max(axis=1, keepdims=True) + ties = np.isclose(probs, maximum, rtol=0.0, atol=1e-12) + pred_class = np.asarray([next(c for c in (1, 0, 2) if row[c]) for row in ties], dtype=np.int64) + score = np.clip(regressor.predict(features), -3.0, 3.0) + interval_lower = np.clip(score + state["residual_q05"], -3.0, 3.0) + interval_upper = np.clip(score + state["residual_q95"], -3.0, 3.0) + metrics = calculate_metrics( + split.class_y, split.regression_y, probs, pred_class, score, + interval_lower=interval_lower, interval_upper=interval_upper, + ) + scaled_error = torch.as_tensor((split.regression_y - score) / 3.0, dtype=torch.float32) + metrics["selection_nll"] = metrics["classification_nll"] + float( + F.huber_loss(scaled_error, torch.zeros_like(scaled_error), delta=0.25) + ) + return metrics, {"probabilities": probs, "predicted_class": pred_class, "predicted_score": score, + "interval_lower": interval_lower, "interval_upper": interval_upper} + + +def controlled_c0( + state: dict[str, Any], split: SplitData, arrays: dict[str, np.ndarray], + scenarios: dict[str, np.ndarray], temperature: float, +) -> tuple[list[dict[str, Any]], dict[str, dict[str, np.ndarray]]]: + rows = [] + predictions = {} + for scenario, mask in scenarios.items(): + metrics, prediction = evaluate_c0(state, split, arrays, temperature, mask) + predictions[scenario] = prediction + rates = _missing_rate_summary(split.mask, mask) + additional_by_modality = np.nanmean(rates["additional_by_modality"], axis=0) + rate, mode = scenario.split("/", 1) + rows.append({"evaluation_split": split.name, "model": "C0", "rate_requested_per_selected_source": float(rate), + "mask_pattern": mode, "rate_realized_global": rates["additional_global"], + "rate_realized_additional_global": rates["additional_global"], + "rate_realized_additional_by_modality": json.dumps([None if not np.isfinite(x) else float(x) for x in additional_by_modality]), + "natural_missing_rate_global": rates["natural_global"], + "natural_missing_rate_by_modality": json.dumps(np.mean(rates["natural_by_modality"], axis=0).tolist()), + "rate_final_total_missing_global": rates["final_global"], + "rate_final_total_missing_by_modality": json.dumps(np.mean(rates["final_by_modality"], axis=0).tolist()), + "synchronous_no_observation_rate": float(np.mean(rates["synchronous_no_observation"])), **metrics}) + return rows, predictions + + +def write_csv(path: Path, rows: list[dict[str, Any]]) -> None: + if not rows: + return + path.parent.mkdir(parents=True, exist_ok=True) + with path.open("w", encoding="utf-8-sig", newline="") as stream: + fieldnames = list(dict.fromkeys(key for row in rows for key in row)) + writer = csv.DictWriter(stream, fieldnames=fieldnames, extrasaction="raise") + writer.writeheader() + writer.writerows(rows) + + +def mask_audit_rows(split: SplitData, scenarios: dict[str, np.ndarray], seed: int) -> list[dict[str, Any]]: + rows: list[dict[str, Any]] = [] + for scenario, masks in scenarios.items(): + requested_rate, pattern = scenario.split("/", 1) + for index, (sample_id, original, current) in enumerate(zip(split.ids, split.mask, masks)): + newly_hidden = np.asarray(original, dtype=bool) & ~np.asarray(current, dtype=bool) + intervals: dict[str, list[list[int]]] = {} + for modality_index, modality in enumerate(MODALITIES): + positions = np.flatnonzero(newly_hidden[:, modality_index]) + spans: list[list[int]] = [] + if len(positions): + start = previous = int(positions[0]) + for position in positions[1:]: + position = int(position) + if position != previous + 1: + spans.append([start, previous + 1]) + start = position + previous = position + spans.append([start, previous + 1]) + intervals[modality] = spans + rate_summary = _missing_rate_summary(original, current) + rows.append({ + "natural_missing_rate": rate_summary["natural_global"], + "natural_missing_rate_by_modality": json.dumps(rate_summary["natural_by_modality"].tolist()), + "realized_additional_rate": rate_summary["additional_global"], + "realized_additional_rate_by_modality": json.dumps([ + None if not np.isfinite(x) else float(x) + for x in rate_summary["additional_by_modality"] + ]), + "final_total_missing_rate": rate_summary["final_global"], + "final_total_missing_rate_by_modality": json.dumps(rate_summary["final_by_modality"].tolist()), + "synchronous_no_observation_rate": float(rate_summary["synchronous_no_observation"]), + "sample_id": sample_id, + "video_id": split.groups[index], + "scenario": scenario, + "requested_rate_per_selected_source": float(requested_rate), + "mask_pattern": pattern, + "mask_seed": _scenario_seed(seed, sample_id, scenario), + "selected_modalities": ",".join(m for m in MODALITIES if intervals[m]), + "newly_hidden_intervals_step_half_open": json.dumps(intervals, separators=(",", ":")), + "original_observed_steps": int(np.asarray(original, dtype=bool).sum()), + "newly_hidden_steps": int(newly_hidden.sum()), + }) + return rows + + +def group_bootstrap( + split: SplitData, prediction: dict[str, np.ndarray], reps: int = 1000, seed: int = SEED + 44, +) -> list[dict[str, Any]]: + rng = np.random.default_rng(seed) + groups = np.unique(split.groups) + group_indices = {g: np.flatnonzero(split.groups == g) for g in groups} + rows = {name: [] for name in ("accuracy", "macro_f1", "mae", "rmse", "pearson", "interval_90_coverage", "interval_90_mean_width")} + for _ in range(reps): + chosen = rng.choice(groups, size=len(groups), replace=True) + idx = np.concatenate([group_indices[g] for g in chosen]) + cls, score = prediction["predicted_class"][idx], prediction["predicted_score"][idx] + ycls, yreg = split.class_y[idx], split.regression_y[idx] + rows["accuracy"].append(accuracy_score(ycls, cls)) + rows["macro_f1"].append(f1_score(ycls, cls, labels=[0, 1, 2], average="macro", zero_division=0)) + rows["mae"].append(mean_absolute_error(yreg, score)) + rows["rmse"].append(np.sqrt(mean_squared_error(yreg, score))) + rows["pearson"].append(pearsonr(yreg, score).statistic if np.std(score) and np.std(yreg) else np.nan) + rows["interval_90_coverage"].append(np.mean((yreg >= prediction["interval_lower"][idx]) & (yreg <= prediction["interval_upper"][idx]))) + rows["interval_90_mean_width"].append(np.mean(prediction["interval_upper"][idx] - prediction["interval_lower"][idx])) + result = [] + for name, values in rows.items(): + values = np.asarray(values, dtype=np.float64) + result.append({"metric": name, "estimate": float(np.nanmedian(values)), + "ci_2_5": float(np.nanpercentile(values, 2.5)), + "ci_97_5": float(np.nanpercentile(values, 97.5)), + "replicates": reps, "unit": "source video group"}) + return result + + +def paired_group_bootstrap_deltas( + split: SplitData, + predictions: dict[str, dict[str, np.ndarray]], + reps: int = 1000, + seed: int = SEED + 88, +) -> list[dict[str, Any]]: + """Paired validation-set model deltas using one shared source-video resample.""" + groups = np.unique(split.groups) + group_indices = {group: np.flatnonzero(split.groups == group) for group in groups} + compare_models = [name for name in predictions if name != "C0"] + metrics = ("accuracy", "macro_f1", "mae", "rmse", "pearson", "interval_90_coverage", "interval_90_mean_width") + + def value(name: str, metric: str, indices: np.ndarray) -> float: + pred = predictions[name] + y_cls, y_reg = split.class_y[indices], split.regression_y[indices] + if metric == "accuracy": + return float(accuracy_score(y_cls, pred["predicted_class"][indices])) + if metric == "macro_f1": + return float(f1_score(y_cls, pred["predicted_class"][indices], labels=[0, 1, 2], average="macro", zero_division=0)) + if metric == "mae": + return float(mean_absolute_error(y_reg, pred["predicted_score"][indices])) + if metric == "rmse": + return float(np.sqrt(mean_squared_error(y_reg, pred["predicted_score"][indices]))) + if metric == "pearson": + estimate = pred["predicted_score"][indices] + return float(pearsonr(y_reg, estimate).statistic) if np.std(y_reg) and np.std(estimate) else float("nan") + if metric == "interval_90_coverage": + return float(np.mean((y_reg >= pred["interval_lower"][indices]) & (y_reg <= pred["interval_upper"][indices]))) + if metric == "interval_90_mean_width": + return float(np.mean(pred["interval_upper"][indices] - pred["interval_lower"][indices])) + raise ValueError(metric) + + point = { + (model, metric): value(model, metric, np.arange(split.n)) - value("C0", metric, np.arange(split.n)) + for model in compare_models for metric in metrics + } + draws = {key: [] for key in point} + rng = np.random.default_rng(seed) + for _ in range(reps): + chosen = rng.choice(groups, size=len(groups), replace=True) + indices = np.concatenate([group_indices[group] for group in chosen]) + baseline = {metric: value("C0", metric, indices) for metric in metrics} + for model in compare_models: + for metric in metrics: + draws[(model, metric)].append(value(model, metric, indices) - baseline[metric]) + rows = [] + for (model, metric), values in draws.items(): + values = np.asarray(values, dtype=np.float64) + rows.append({ + "model": model, "baseline": "C0", "metric": metric, + "point_delta": point[(model, metric)], + "bootstrap_median_delta": float(np.nanmedian(values)), + "ci_2_5": float(np.nanpercentile(values, 2.5)), + "ci_97_5": float(np.nanpercentile(values, 97.5)), + "replicates": reps, "unit": "paired source-video group resample", + }) + return rows + + +def controlled_metrics( + model: CRG, + split: SplitData, + arrays: dict[str, np.ndarray], + scenarios: dict[str, np.ndarray], + device: torch.device, + batch_size: int, + model_name: str, + temperature: float, + seed: int = SEED + 552, +) -> tuple[list[dict[str, Any]], dict[str, dict[str, np.ndarray]]]: + rows = [] + predictions = {} + for scenario, mask in scenarios.items(): + scenario_seed = _scenario_seed(seed, split.name, scenario) + with fixed_torch_seed(scenario_seed, device): + metrics, prediction = evaluate(model, arrays, split, device, batch_size, masks=mask, temperature=temperature) + predictions[scenario] = prediction + rates = _missing_rate_summary(split.mask, mask) + additional_by_modality = np.nanmean(rates["additional_by_modality"], axis=0) + rate, mode = scenario.split("/", 1) + rows.append({"evaluation_split": split.name, "model": model_name, "rate_requested_per_selected_source": float(rate), + "mask_pattern": mode, "rate_realized_global": rates["additional_global"], + "rate_realized_additional_global": rates["additional_global"], + "rate_realized_additional_by_modality": json.dumps([None if not np.isfinite(x) else float(x) for x in additional_by_modality]), + "natural_missing_rate_global": rates["natural_global"], + "natural_missing_rate_by_modality": json.dumps(np.mean(rates["natural_by_modality"], axis=0).tolist()), + "rate_final_total_missing_global": rates["final_global"], + "rate_final_total_missing_by_modality": json.dumps(np.mean(rates["final_by_modality"], axis=0).tolist()), + "synchronous_no_observation_rate": float(np.mean(rates["synchronous_no_observation"])), **metrics}) + print(f"validation mask {scenario}: additional={rates['additional_global']:.3f} final={rates['final_global']:.3f} " + f"macroF1={metrics['macro_f1']:.4f} MAE={metrics['regression_mae']:.4f}", flush=True) + return rows, predictions + + +def controlled_group_bootstrap( + split: SplitData, + predictions: dict[str, dict[str, dict[str, np.ndarray]]], + scenario_masks: dict[str, np.ndarray], + repeats: int, + seed: int, +) -> list[dict[str, Any]]: + """Paired source-video bootstrap for each fixed mask and the MAE-rate AURC.""" + if "C0" not in predictions: + raise ValueError("controlled bootstrap requires C0 predictions") + scenarios = list(predictions["C0"]) + if any(set(model_predictions) != set(scenarios) for model_predictions in predictions.values()): + raise ValueError("all models must use identical controlled-mask scenarios") + if set(scenario_masks) != set(scenarios): + raise ValueError("controlled-mask audit and model predictions must use identical scenarios") + groups = np.unique(split.groups) + group_indices = {group: np.flatnonzero(split.groups == group) for group in groups} + metric_names = ("accuracy", "macro_f1", "mae", "rmse", "pearson") + keys = [(model, scenario, metric) for model in predictions for scenario in scenarios for metric in metric_names] + point = {} + draws = {key: [] for key in keys} + delta_draws = {key: [] for key in keys if key[0] != "C0"} + + curve_modes = tuple(MASK_MODES) + curve_rates = np.asarray((0.0, 0.1, 0.3, 0.5, 0.7), dtype=np.float64) + curve_scenarios = { + mode: tuple("0.0/none" if rate == 0.0 else f"{rate:.1f}/{mode}" for rate in curve_rates) + for mode in curve_modes + } + for mode, curve in curve_scenarios.items(): + if any(scenario not in scenarios for scenario in curve): + raise ValueError(f"missing fixed rate-curve scenario for {mode}") + curve_point = {} + curve_draws = {} + curve_actual_rates: dict[tuple[str, str], np.ndarray] = {} + additional_rate_by_sample: dict[str, np.ndarray] = {} + for scenario, mask in scenario_masks.items(): + by_modality = _missing_rate_summary(split.mask, mask)["additional_by_modality"] + counts = np.isfinite(by_modality).sum(axis=1) + additional_rate_by_sample[scenario] = np.divide( + np.nansum(by_modality, axis=1), counts, + out=np.full(split.n, np.nan, dtype=np.float64), where=counts > 0, + ) + for model in predictions: + for mode, curve in curve_scenarios.items(): + key = (model, mode) + errors = [np.abs(split.regression_y - predictions[model][scenario]["predicted_score"]) for scenario in curve] + point_curve = np.asarray([float(error.mean()) for error in errors]) + actual_rates = np.asarray([ + 0.0 if scenario == "0.0/none" else float(np.nanmean(additional_rate_by_sample[scenario])) + for scenario in curve + ]) + curve_actual_rates[model, mode] = actual_rates + order = np.argsort(actual_rates, kind="stable") + x = actual_rates[order] + y = point_curve[order] + unique_x, inverse = np.unique(x, return_inverse=True) + unique_y = np.asarray([y[inverse == index].mean() for index in range(len(unique_x))]) + curve_point[key] = (float(np.trapezoid(unique_y, unique_x) / unique_x[-1]) + if len(unique_x) > 1 and unique_x[-1] > 0.0 else float(point_curve[0])) + curve_draws[key] = [] + + def metric_values(model: str, scenario: str, indices: np.ndarray) -> dict[str, float]: + prediction = predictions[model][scenario] + y_class, y_score = split.class_y[indices], split.regression_y[indices] + predicted_class = prediction["predicted_class"][indices] + predicted_score = prediction["predicted_score"][indices] + return { + "accuracy": float(accuracy_score(y_class, predicted_class)), + "macro_f1": float(f1_score(y_class, predicted_class, labels=[0, 1, 2], average="macro", zero_division=0)), + "mae": float(mean_absolute_error(y_score, predicted_score)), + "rmse": float(np.sqrt(mean_squared_error(y_score, predicted_score))), + "pearson": float(pearsonr(y_score, predicted_score).statistic) + if np.std(y_score) and np.std(predicted_score) else float("nan"), + } + + for model in predictions: + for scenario in scenarios: + values = metric_values(model, scenario, np.arange(split.n)) + for metric, value in values.items(): + point[(model, scenario, metric)] = value + + within_model_mae_delta_draws = { + (model, scenario): [] for model in predictions for scenario in scenarios if scenario != "0.0/none" + } + + rng = np.random.default_rng(seed) + for _ in range(repeats): + chosen = rng.choice(groups, size=len(groups), replace=True) + indices = np.concatenate([group_indices[group] for group in chosen]) + replicate_values = {} + for model in predictions: + for scenario in scenarios: + values = metric_values(model, scenario, indices) + for metric, value in values.items(): + key = (model, scenario, metric) + draws[key].append(value) + replicate_values[key] = value + for model in predictions: + if model == "C0": + continue + for scenario in scenarios: + for metric in metric_names: + key = (model, scenario, metric) + delta_draws[key].append(replicate_values[key] - replicate_values[("C0", scenario, metric)]) + for model in predictions: + natural_mae = replicate_values[(model, "0.0/none", "mae")] + for scenario in scenarios: + if scenario != "0.0/none": + within_model_mae_delta_draws[(model, scenario)].append( + replicate_values[(model, scenario, "mae")] - natural_mae + ) + for model in predictions: + for mode, curve in curve_scenarios.items(): + curve_mae = [replicate_values[(model, scenario, "mae")] for scenario in curve] + sample_rates = np.asarray([ + 0.0 if scenario == "0.0/none" else float(np.nanmean(additional_rate_by_sample[scenario][indices])) + for scenario in curve + ]) + order = np.argsort(sample_rates, kind="stable") + x = sample_rates[order] + y = np.asarray(curve_mae)[order] + unique_x, inverse = np.unique(x, return_inverse=True) + unique_y = np.asarray([y[inverse == index].mean() for index in range(len(unique_x))]) + auc = (float(np.trapezoid(unique_y, unique_x) / unique_x[-1]) + if len(unique_x) > 1 and unique_x[-1] > 0.0 else float(curve_mae[0])) + curve_draws[(model, mode)].append(auc) + + def interval(values: list[float]) -> tuple[float, float, float]: + samples = np.asarray(values, dtype=np.float64) + return float(np.nanmedian(samples)), float(np.nanpercentile(samples, 2.5)), float(np.nanpercentile(samples, 97.5)) + + rows = [] + for model, scenario, metric in keys: + median, lower, upper = interval(draws[(model, scenario, metric)]) + row = {"model": model, "scenario": scenario, "metric": metric, + "estimate": point[(model, scenario, metric)], "bootstrap_median": median, + "ci_2_5": lower, "ci_97_5": upper, "replicates": repeats, + "unit": "paired source-video group resample"} + if model != "C0": + delta_median, delta_lower, delta_upper = interval(delta_draws[(model, scenario, metric)]) + row.update({"baseline": "C0", "delta_estimate": point[(model, scenario, metric)] - point[("C0", scenario, metric)], + "delta_bootstrap_median": delta_median, "delta_ci_2_5": delta_lower, + "delta_ci_97_5": delta_upper}) + if scenario != "0.0/none" and metric == "mae": + natural = point[(model, "0.0/none", "mae")] + within_median, within_lower, within_upper = interval(within_model_mae_delta_draws[(model, scenario)]) + row.update({"delta_to_natural_mae": point[(model, scenario, "mae")] - natural, + "delta_to_natural_bootstrap_median": within_median, + "delta_to_natural_ci_2_5": within_lower, + "delta_to_natural_ci_97_5": within_upper}) + rows.append(row) + for model in predictions: + for mode in curve_modes: + median, lower, upper = interval(curve_draws[(model, mode)]) + row = {"model": model, "scenario": f"MAE_rate_curve/{mode}", "metric": "AURC_MAE", + "estimate": curve_point[(model, mode)], "bootstrap_median": median, + "ci_2_5": lower, "ci_97_5": upper, + "curve_additional_rates_realized": json.dumps(curve_actual_rates[(model, mode)].tolist()), + "replicates": repeats, "unit": "paired source-video group resample"} + if model != "C0": + baseline_values = curve_draws[("C0", mode)] + deltas = np.asarray(curve_draws[(model, mode)]) - np.asarray(baseline_values) + delta_median, delta_lower, delta_upper = interval(deltas.tolist()) + row.update({"baseline": "C0", "delta_estimate": curve_point[(model, mode)] - curve_point[("C0", mode)], + "delta_bootstrap_median": delta_median, "delta_ci_2_5": delta_lower, + "delta_ci_97_5": delta_upper}) + rows.append(row) + return rows + + +def reencode_attachment3(device: torch.device) -> tuple[list[dict[str, Any]], list[dict[str, Any]]]: + from data import restricted_load + + files = sorted(ATTACHMENT3_ALIGNED.glob("附件3_*.pkl"), key=lambda p: int(p.stem.split("_")[-1])) + if len(files) != 30: + raise FileNotFoundError(f"expected 30 aligned attachment-3 files, found {len(files)} under {ATTACHMENT3_ALIGNED}") + file_ids = [path.stem for path in files] + if len(set(file_ids)) != len(file_ids): + raise ValueError("attachment-3 input file IDs are not unique") + bert = AutoModel.from_pretrained(TEXT_MODEL_ID, local_files_only=True).to(device).eval() + cases, audit = [], [] + with torch.inference_mode(): + for path in files: + case = load_attachment3_case(path) + ids = torch.from_numpy(case["input_ids"][None]).to(device) + attention = torch.from_numpy(case["attention_mask"][None].astype(np.int64)).to(device) + segments = torch.from_numpy(case["token_type_ids"][None]).to(device) + text = bert(input_ids=ids, attention_mask=attention, token_type_ids=segments).last_hidden_state[0].float().cpu().numpy() + text[~case["attention_mask"]] = 0.0 + case_id = path.stem + cases.append({"case_id": case_id, "text": text, "audio": case["audio"], "vision": case["vision"], "text_mask": case["attention_mask"]}) + audio_mask = np.any(case["audio"] != 0, axis=1) + vision_mask = np.any(case["vision"] != 0, axis=1) + audit.append({"case_id": case_id, "source_file": path.name, + "text_visible_steps": int(case["attention_mask"].sum()), + "audio_visible_steps": int(audio_mask.sum()), "vision_visible_steps": int(vision_mask.sum()), + "audio_missing_fraction": float(1.0 - audio_mask.mean()), + "vision_missing_fraction": float(1.0 - vision_mask.mean()), + "unknown_quality_flag": True, "labels_available": False, + "input_note": "official aligned_50 only; unaligned rows and raw transcript are not used", + "source_sha256": sha256(path)}) + del bert + return cases, audit + + +def infer_attachment3( + model: CRG, + cases: list[dict[str, Any]], + fitted: dict[str, dict[str, np.ndarray]], + device: torch.device, + temperature: float, + prior_probs: np.ndarray, + magnitude_priors: np.ndarray, +) -> tuple[list[dict[str, Any]], list[dict[str, Any]]]: + model.eval() + predictions, audit = [], [] + for case in cases: + mask = np.stack((case["text_mask"], np.any(case["audio"] != 0, axis=1), np.any(case["vision"] != 0, axis=1)), axis=-1)[None] + xs_np = {} + for modality in MODALITIES: + values = case[modality].astype(np.float32) + values = np.clip((values - fitted[modality]["mean"]) / fitted[modality]["std"], -10.0, 10.0) + values[~mask[0, :, MODALITIES.index(modality)]] = 0.0 + xs_np[modality] = values[None] + low_information = not bool(mask.any()) + if low_information: + p = np.asarray(prior_probs, dtype=np.float64) + p = p / p.sum() + max_probability = float(p.max()) + predicted_class = next(c for c in (1, 0, 2) if math.isclose(float(p[c]), max_probability, rel_tol=0.0, abs_tol=1e-12)) + score = 0.0 + beta = np.full((1, 1, 2, 2), np.nan, np.float32) + if predicted_class != 1: + sign_index = 0 if predicted_class == 0 else 1 + magnitude = float(betaincinv(magnitude_priors[sign_index, 0], magnitude_priors[sign_index, 1], 0.5)) + score = (-3.0 if predicted_class == 0 else 3.0) * magnitude + beta[0, 0] = magnitude_priors + ppaths = p[None, None, :] + else: + arrays = {m: xs_np[m] for m in MODALITIES} + xs, observed = to_device_batch(arrays, mask, np.asarray([0]), device) + with torch.inference_mode(): + out = model(xs, observed, paths=16 if model.use_joint_draws else 1, joint_draws=model.use_joint_draws) + ppaths = out["class_probs_by_path"].cpu().numpy()[:, 0:1] + beta = out["beta_params"].cpu().numpy()[:, 0:1] + p, classes, scores = _decode_mixture(ppaths, beta, temperature) + p, predicted_class, score = p[0], int(classes[0]), float(scores[0]) + interval_temperature = 1.0 if low_information else temperature + interval_lower, interval_upper = _predictive_intervals(ppaths, beta, interval_temperature) + variance_components = _trajectory_variance_components(ppaths, beta) + calibrated_moments = _calibrated_mixture_moments(ppaths, beta, interval_temperature) + row = {"case_id": case["case_id"], "predicted_class": predicted_class, + "predicted_class_name": ("negative", "neutral", "positive")[predicted_class], + "predicted_sentiment": float(score), "p_negative": float(p[0]), + "p_neutral": float(p[1]), "p_positive": float(p[2]), + "interval_90_lower": float(interval_lower[0]), "interval_90_upper": float(interval_upper[0]), + "predictive_variance_mean_uncalibrated": float(variance_components[0][0]), + "within_trajectory_variance": float(variance_components[1][0]), + "between_trajectory_variance": float(variance_components[2][0]), + "predictive_mean_calibrated": float(calibrated_moments[0][0]), + "predictive_variance_calibrated": float(calibrated_moments[1][0]), + "beta_negative_alpha": float(beta[0, 0, 0, 0]), "beta_negative_beta": float(beta[0, 0, 0, 1]), + "beta_positive_alpha": float(beta[0, 0, 1, 0]), "beta_positive_beta": float(beta[0, 0, 1, 1]), + "low_information_prior_fallback": low_information, + "output_note": "unlabeled attachment-3 case; no accuracy/F1 is defined"} + predictions.append(row) + audit.append({"case_id": case["case_id"], "visible_text_steps": int(mask[0, :, 0].sum()), + "visible_audio_steps": int(mask[0, :, 1].sum()), "visible_vision_steps": int(mask[0, :, 2].sum()), + "low_information_prior_fallback": low_information, + "calibration_temperature": interval_temperature, + "interval_90_lower": float(interval_lower[0]), "interval_90_upper": float(interval_upper[0]), + "predictive_variance_mean_uncalibrated": float(variance_components[0][0]), + "predictive_variance_calibrated": float(calibrated_moments[1][0])}) + return predictions, audit + + +def validate_attachment3_predictions(expected_ids: list[str], predictions: list[dict[str, Any]]) -> None: + """Check the unlabeled submission contract and sign/strength consistency.""" + predicted_ids = [str(row["case_id"]) for row in predictions] + if len(predictions) != len(expected_ids) or len(set(expected_ids)) != len(expected_ids): + raise ValueError("attachment-3 prediction count differs from unique expected IDs") + if len(set(predicted_ids)) != len(predicted_ids) or set(predicted_ids) != set(expected_ids): + raise ValueError("attachment-3 predictions must contain every expected ID exactly once") + for row in predictions: + predicted_class = int(row["predicted_class"]) + score = float(row["predicted_sentiment"]) + probabilities = np.asarray([row["p_negative"], row["p_neutral"], row["p_positive"]], dtype=np.float64) + if predicted_class not in (0, 1, 2) or not np.isfinite(score) or not -3.0 <= score <= 3.0: + raise ValueError(f"invalid attachment-3 class/strength for {row['case_id']}") + if (predicted_class == 1 and score != 0.0) or (predicted_class == 0 and not score < 0.0) or ( + predicted_class == 2 and not score > 0.0 + ): + raise ValueError(f"attachment-3 class/strength polarity mismatch for {row['case_id']}") + if not np.isfinite(probabilities).all() or np.any(probabilities < 0.0) or not np.isclose(probabilities.sum(), 1.0, atol=1e-6): + raise ValueError(f"invalid attachment-3 class probabilities for {row['case_id']}") + low, high = float(row["interval_90_lower"]), float(row["interval_90_upper"]) + if not np.isfinite([low, high]).all() or low > high or low < -3.0 or high > 3.0: + raise ValueError(f"invalid attachment-3 prediction interval for {row['case_id']}") + + +def main() -> None: + global DELTA_U + parser = argparse.ArgumentParser() + parser.add_argument("--epochs", type=int, default=12) + parser.add_argument("--imputer-epochs", type=int, default=8) + parser.add_argument("--batch-size", type=int, default=64) + parser.add_argument("--patience", type=int, default=3) + parser.add_argument("--seed", type=int, default=SEED) + parser.add_argument("--device", default="cuda" if torch.cuda.is_available() else "cpu") + parser.add_argument("--bootstrap-repeats", type=int, default=1000) + parser.add_argument("--skip-attachment3", action="store_true") + args = parser.parse_args() + seed_everything(args.seed) + rng = np.random.default_rng(args.seed) + device = torch.device(args.device) + RESULTS.mkdir(parents=True, exist_ok=True) + if device.type == "cuda": + print(f"device={device} ({torch.cuda.get_device_name(device)})", flush=True) + + input_path = ROOT / "E题数据" / "附件2-数据集特征文件" / "aligned_50.pkl" + official = load_official_splits(input_path) + overlaps = assert_group_disjoint(official) + fit, heldout_train = split_calibration(official["train"], args.seed) + reliability_validation, temperature_calibration = split_calibration(heldout_train, args.seed + 1, fraction=0.5) + reliability_validation.name = "reliability_validation" + temperature_calibration.name = "temperature_calibration" + if (set(fit.groups) & set(reliability_validation.groups) + or set(fit.groups) & set(temperature_calibration.groups) + or set(reliability_validation.groups) & set(temperature_calibration.groups)): + raise AssertionError("fit, reliability-selection, and temperature-calibration videos must be disjoint") + DELTA_U = label_resolution_from_train(fit.regression_y) + magnitude_priors = fit_magnitude_priors(fit.regression_y) + class_counts_fit = np.bincount(fit.class_y, minlength=3).astype(np.float64) + class_prior_probs = (class_counts_fit + 1.0) / (class_counts_fit.sum() + 3.0) + # Freeze the exact validation masks before fitting any model. + validation_scenarios = make_scenarios(official["valid"], args.seed + 909) + reliability_scenarios = make_reliability_scenarios(reliability_validation, args.seed + 906) + print("official splits:", {k: (v.n, len(np.unique(v.groups))) for k, v in official.items()}, + "fit/reliability_validation/temperature_calibration:", + (fit.n, reliability_validation.n, temperature_calibration.n), "group_overlap:", overlaps, flush=True) + fitted = fit_preprocessor(fit) + transformed = {name: transform_split(split, fitted) for name, split in official.items()} + transformed["fit"] = transform_split(fit, fitted) + transformed["reliability_validation"] = transform_split(reliability_validation, fitted) + transformed["temperature_calibration"] = transform_split(temperature_calibration, fitted) + np.savez_compressed(RESULTS / "preprocessor.npz", **{f"{m}_{k}": v for m, stats in fitted.items() for k, v in stats.items()}) + + imputer = StructuredGaussianImputer(INPUT_DIMS).to(device) + imputer_history = fit_imputer(imputer, transformed["fit"], fit, device, args.imputer_epochs, args.batch_size, args.seed + 1) + torch.save({k: v.detach().cpu() for k, v in imputer.state_dict().items()}, RESULTS / "structured_imputer.pt") + + teacher = _make_variant("C6", imputer).to(device) + teacher, history_teacher = _fit_neural( + teacher, "teacher", fit, official["valid"], transformed, device, args.epochs, + args.batch_size, args.patience, np.random.default_rng(args.seed + 2), + selection_split=reliability_validation, selection_arrays=transformed["reliability_validation"], + selection_scenarios={"0.0/natural": reliability_validation.mask.copy()}, + ) + teacher_reliability, teacher_tuning_rows = tune_reliability_hparams( + teacher, transformed["reliability_validation"], reliability_validation, reliability_scenarios, + device, args.batch_size, "teacher", seed=args.seed + 551, + ) + torch.save({k: v.detach().cpu() for k, v in teacher.state_dict().items()}, RESULTS / "teacher.pt") + + ablation_rows: list[dict[str, Any]] = [] + history = list(imputer_history) + history_teacher + reliability_tuning_rows = list(teacher_tuning_rows) + group_risk_tuning_rows: list[dict[str, Any]] = [] + models: dict[str, CRG] = {} + _, c0_state = fit_c0(fit, official["valid"], transformed) + calibrate_c0_interval(c0_state, temperature_calibration, transformed["temperature_calibration"]) + _, c0_cal_pred = evaluate_c0(c0_state, temperature_calibration, transformed["temperature_calibration"]) + c0_temperature = fit_temperature(c0_cal_pred["probabilities"], temperature_calibration.class_y) + c0_metrics, c0_valid_pred = evaluate_c0(c0_state, official["valid"], transformed["valid"], c0_temperature) + c0_metrics["temperature"] = c0_temperature + ablation_rows.append({"model": "C0", **c0_metrics, "description": "observed mean/std + masks + maximum gap; logistic/ridge"}) + best_model_name: str | None = None + best_valid_loss = float("inf") + temperatures = {"C0": c0_temperature} + selected_group_risk: dict[str, tuple[float, float]] = {} + validation_predictions: dict[str, dict[str, np.ndarray]] = {"C0": c0_valid_pred} + + definitions = { + "C1": "masked BiGRU; no posterior imputation, explicit reliability or source gate", + "C2": "exact Gaussian posterior mean; no joint trajectory integral", + "C3": "joint trajectory integral plus final reliability/content fusion gate", + "C4": "C3 plus bounded cross-time source attention and null source", + "C5": "C4 plus reliability-modulated BiGRU update", + "C6": "C5 plus optional rank-4 CP residual", + "C6_no_distance": "C6 with uncertainty retained but both distance/span reliability penalties fixed to zero", + "C6_no_reconstruction": "C6 trained without the auxiliary hidden-feature reconstruction loss", + "C6_pointmask": "C6 trained with independent point masking instead of contiguous spans", + "C7_distill": "C6 plus entropy/retention-weighted teacher distillation only", + "C7_group": "C6 plus smooth worst-group risk only", + } + diagnostic_ablation_names = {"C6_no_distance", "C6_no_reconstruction", "C6_pointmask"} + model_names = ("C1", "C2", "C3", "C4", "C5", "C6", *sorted(diagnostic_ablation_names), "C7_distill", "C7_group") + no_distance_candidates = tuple(value for value in RELIABILITY_CANDIDATES if value[2] == 0.0 and value[3] == 0.0) + for name in model_names: + if name == "C7_group": + (variant, rows, reliability_rows, risk_rows, selected_reliability, + selected_risk, _) = tune_group_risk_model( + imputer, fit, official["valid"], transformed, + reliability_validation, transformed["reliability_validation"], reliability_scenarios, + device, args.epochs, args.batch_size, args.patience, args.seed + 303, + ) + reliability_tuning_rows.extend(reliability_rows) + group_risk_tuning_rows.extend(risk_rows) + selected_group_risk[name] = selected_risk + else: + base_name = "C6" if name in diagnostic_ablation_names else name + variant = _make_variant(base_name, imputer) + if name == "C6_no_distance": + _set_reliability_hparams(variant, (DEFAULT_RELIABILITY[0], DEFAULT_RELIABILITY[1], 0.0, 0.0)) + kd_teacher = teacher if name == "C7_distill" else None + mask_kind = "point" if name == "C6_pointmask" else "continuous" + variant, rows = _fit_neural( + variant, name, fit, official["valid"], transformed, device, args.epochs, + args.batch_size, args.patience, np.random.default_rng(args.seed + 303), + teacher=kd_teacher, + selection_split=reliability_validation, + selection_arrays=transformed["reliability_validation"], + selection_scenarios=reliability_scenarios, + mask_kind=mask_kind, + use_reconstruction=name != "C6_no_reconstruction", + ) + selected_reliability, tuning_rows = tune_reliability_hparams( + variant, transformed["reliability_validation"], reliability_validation, reliability_scenarios, + device, args.batch_size, name, seed=args.seed + 551, + candidate_values=no_distance_candidates if name == "C6_no_distance" else RELIABILITY_CANDIDATES, + ) + reliability_tuning_rows.extend(tuning_rows) + selected_group_risk[name] = (float("nan"), float("nan")) + history.extend(rows) + models[name] = variant + _, calibration_pred = evaluate(variant, transformed["temperature_calibration"], temperature_calibration, + device, args.batch_size) + model_temperature = fit_temperature(calibration_pred["probabilities"], temperature_calibration.class_y) + temperatures[name] = model_temperature + raw_metrics, _ = evaluate(variant, transformed["valid"], official["valid"], device, args.batch_size) + metrics, valid_prediction = evaluate(variant, transformed["valid"], official["valid"], device, args.batch_size, + temperature=model_temperature) + validation_predictions[name] = valid_prediction + metrics["validation_selection_loss"] = raw_metrics["selection_nll"] + metrics["temperature"] = model_temperature + metrics.update({"rho_imp": selected_reliability[0], "lambda_u": selected_reliability[1], + "lambda_gap": selected_reliability[2], "lambda_span": selected_reliability[3]}) + metrics["lambda_group"], metrics["group_temperature"] = selected_group_risk[name] + ablation_rows.append({"model": name, **metrics, "description": definitions[name]}) + if name not in diagnostic_ablation_names and raw_metrics["selection_nll"] < best_valid_loss: + best_valid_loss, best_model_name = raw_metrics["selection_nll"], name + write_csv(RESULTS / "ablation_validation.csv", ablation_rows) + write_csv(RESULTS / "reliability_hparam_tuning.csv", reliability_tuning_rows) + write_csv(RESULTS / "group_risk_tuning.csv", group_risk_tuning_rows) + write_csv(RESULTS / "validation_group_bootstrap_deltas.csv", + paired_group_bootstrap_deltas(official["valid"], validation_predictions, args.bootstrap_repeats, args.seed + 88)) + if best_model_name is None: + raise RuntimeError("no neural ablation candidate completed") + best_model = models[best_model_name] + + # Calibration is on a group-held-out slice of official training data, never on official test. + temperature = temperatures[best_model_name] + valid_metrics, valid_pred = evaluate(best_model, transformed["valid"], official["valid"], device, args.batch_size, temperature=temperature) + test_metrics, test_pred = evaluate( + best_model, transformed["test"], official["test"], device, args.batch_size, + temperature=temperature, collect_gate_diagnostics=True, + ) + torch.save({k: v.detach().cpu() for k, v in best_model.state_dict().items()}, RESULTS / "crg_student.pt") + (RESULTS / "validation_metrics.json").write_text(json.dumps({**valid_metrics, "selected_model": best_model_name, "temperature": temperature}, indent=2), encoding="utf-8") + (RESULTS / "test_metrics.json").write_text(json.dumps({**test_metrics, "selected_model": best_model_name, "temperature": temperature}, indent=2), encoding="utf-8") + + test_rows = [] + for i, sample_id in enumerate(official["test"].ids): + p = test_pred["probabilities"][i] + test_rows.append({"sample_id": sample_id, "source_video_id": official["test"].groups[i], + "true_class": int(official["test"].class_y[i]), "predicted_class": int(test_pred["predicted_class"][i]), + "true_sentiment": float(official["test"].regression_y[i]), "predicted_sentiment": float(test_pred["predicted_score"][i]), + "p_negative": float(p[0]), "p_neutral": float(p[1]), "p_positive": float(p[2]), + "interval_90_lower": float(test_pred["interval_lower"][i]), + "interval_90_upper": float(test_pred["interval_upper"][i]), + "predictive_variance_mean_uncalibrated": float(test_pred["predictive_variance_uncalibrated"][i]), + "within_trajectory_variance": float(test_pred["within_trajectory_variance"][i]), + "between_trajectory_variance": float(test_pred["between_trajectory_variance"][i])}) + write_csv(RESULTS / "test_predictions.csv", test_rows) + write_csv(RESULTS / "test_gate_diagnostics.csv", gate_diagnostic_rows(official["test"], test_pred)) + write_csv(RESULTS / "group_bootstrap_ci.csv", + group_bootstrap(official["test"], test_pred, args.bootstrap_repeats, args.seed + 44)) + + write_csv(RESULTS / "controlled_mask_audit.csv", + mask_audit_rows(official["valid"], validation_scenarios, args.seed + 909)) + controlled_rows, c0_scenario_predictions = controlled_c0( + c0_state, official["valid"], transformed["valid"], validation_scenarios, c0_temperature, + ) + controlled_predictions: dict[str, dict[str, dict[str, np.ndarray]]] = {"C0": c0_scenario_predictions} + for name, candidate in models.items(): + candidate_rows, candidate_predictions = controlled_metrics( + candidate, official["valid"], transformed["valid"], validation_scenarios, + device, args.batch_size, name, temperatures[name], seed=args.seed + 552, + ) + controlled_rows.extend(candidate_rows) + controlled_predictions[name] = candidate_predictions + write_csv(RESULTS / "controlled_missingness.csv", controlled_rows) + write_csv(RESULTS / "controlled_group_bootstrap.csv", + controlled_group_bootstrap(official["valid"], controlled_predictions, validation_scenarios, + args.bootstrap_repeats, args.seed + 553)) + write_csv(RESULTS / "training_history.csv", history) + + attachment_count = 0 + if not args.skip_attachment3: + cases, attachment_audit = reencode_attachment3(device) + attachment_predictions, inference_audit = infer_attachment3(best_model, cases, fitted, device, temperature, class_prior_probs, magnitude_priors) + validate_attachment3_predictions([case["case_id"] for case in cases], attachment_predictions) + write_csv(RESULTS / "attachment3_predictions.csv", attachment_predictions) + write_csv(RESULTS / "attachment3_audit.csv", [dict(a, **next(x for x in inference_audit if x["case_id"] == a["case_id"])) for a in attachment_audit]) + attachment_count = len(cases) + + manifest = { + "seed": args.seed, + "text_encoder": TEXT_MODEL_ID, + "training_configuration": {"student_epoch_limit": args.epochs, "imputer_epochs": args.imputer_epochs, + "batch_size": args.batch_size, "early_stopping_patience": args.patience, + "device": str(device), + "device_name": torch.cuda.get_device_name(device) if device.type == "cuda" else "CPU", + "optimizer": "AdamW", "student_learning_rate": 3e-4, + "student_weight_decay": 1e-3, "imputer_learning_rate": 3e-4, + "imputer_weight_decay": 1e-4, + "early_stopping_metric": "mean untempered selection_nll over fixed group-disjoint internal training scenarios", + "inner_selection_scenarios": list(reliability_scenarios), + "inner_selection_source_video_groups": int(len(np.unique(reliability_validation.groups)))}, + "training_input": str(input_path.relative_to(ROOT)), + "training_sha256": sha256(input_path), + "official_group_overlap": overlaps, + "official_splits": {name: {"n": split.n, "source_video_groups": int(len(np.unique(split.groups)))} for name, split in official.items()}, + "internal_train_holdouts": { + "fit": {"n": fit.n, "video_groups": int(len(np.unique(fit.groups)))}, + "reliability_selection": {"n": reliability_validation.n, "video_groups": int(len(np.unique(reliability_validation.groups)))}, + "temperature_calibration": {"n": temperature_calibration.n, "video_groups": int(len(np.unique(temperature_calibration.groups)))}, + "all_group_disjoint": True, + }, + "feature_standardization": "fit-only observed rows, per-dimension; fixed for valid/test/attachment3", + "missing_mask": "row-level all-zero convention; q*=1 only where currently visible, J_Q=0; hidden metadata is zeroed", + "observation_quality": {"quality_score_fields_present": False, "quality_available_flag_present": False, + "fallback": "q*=1 and J_Q=0 for visible rows; R_eff=R", + "quality_noise_mapping_ablation": "not identifiable on aligned_50 because no row quality score varies"}, + "imputer": {"type": "structured linear Gaussian shared-private state space", "state_dims": {"shared": 8, "private_each": 4}, + "posterior": "block-tridiagonal equivalent Kalman information filter + RTS smoother", + "sampling": "joint latent trajectories and missing emissions; observed features copied exactly", + "fit_objective": "train-only observed Gaussian marginal likelihood including log determinants", + "epochs": args.imputer_epochs, "frozen_before_teacher_student": True}, + "architecture": {"projection": 32, "bigru_hidden_each_direction": 16, "cross_source_layers": 1, + "cross_time_read": True, "rank": 4, "reliability_gru": "directional hidden decay; reset applied before candidate map; update gate multiplied by rho", + "final_gate": "rho times bounded content score plus positive null prior", + "output": "neutral point mass plus sign-specific Beta magnitudes; K-path probabilities mixed before decoding"}, + "reliability_hyperparameters": {"selected_per_model_on": "group-disjoint internal training reliability-validation slice", + "candidate_values": [list(v) for v in RELIABILITY_CANDIDATES], + "validation_scenarios": list(reliability_scenarios), + "selected_by_model": {row["model"]: [row["rho_imp"], row["lambda_u"], row["lambda_gap"], row["lambda_span"]] + for row in reliability_tuning_rows if row.get("selected")}}, + "group_risk_hyperparameters": { + "selection": "lambda_group and group_temperature jointly selected with reliability hyperparameters on fixed group-disjoint internal training scenarios", + "candidate_values": [list(v) for v in GROUP_RISK_CANDIDATES], + "selected": list(selected_group_risk["C7_group"]), + "selection_split": reliability_validation.name, + }, + "loss": {"supervision": "negative log mixture of Beta interval masses plus scaled Huber mean term", + "delta_u": DELTA_U, "delta_u_source": "half the minimum positive spacing of nonzero absolute labels in fit only", + "lambda_y": LAMBDA_Y, "lambda_distill": LAMBDA_DISTILL, + "lambda_reconstruction": LAMBDA_RECON, + "lambda_group_default": LAMBDA_GROUP, "group_temperature_default": GROUP_TEMPERATURE, + "selected_group_risk": list(selected_group_risk["C7_group"]), + "distill_temperature": DISTILL_TEMPERATURE, "distill_retention_exponent": 1.0, + "imputer_regularization": {"emission_l2": LAMBDA_EMISSION, "transition_l2": LAMBDA_TRANSITION}, + "group_and_distill_separate": True}, + "calibration": {"method": "temperature scaling on a group-disjoint internal official-train holdout, separated from reliability selection", + "temperature": temperature, "valid_used_for_selection": True, "test_used_for_selection_or_calibration": False}, + "selected_model": best_model_name, + "attachment3_low_information_priors": {"class_probability_method": "fit counts + one pseudocount per class", + "class_probability_values": class_prior_probs.tolist(), + "negative_beta": magnitude_priors[0].tolist(), + "positive_beta": magnitude_priors[1].tolist()}, + "ablation_definitions": definitions, + "masking": {"rates": MASK_RATES, "patterns": list(MASK_MODES), "preserve_at_least_fraction_per_selected_modality": 0.2, + "controlled_sweep_split": "official validation", "identical_masks_across_models": True, + "scenario_count": len(validation_scenarios), "scenario_seed": args.seed + 909, + "training_mask_rng_seed": args.seed + 303, + "reliability_scenario_seed": args.seed + 906, + "controlled_torch_sampling_seed": args.seed + 552, + "paired_control_bootstrap_seed": args.seed + 553, + "mask_audit_file": "controlled_mask_audit.csv", + "additional_one_factor_controls": ["modality T/A/V and combinations", "start/middle/end", "one-long/multiple-short", "sync/partial/async"], + "semantic_position_control": "not run: aligned_50 does not provide audited semantic boundary indices; raw text is prohibited in student inputs"}, + "final_test_metrics": test_metrics, + "test_gate_diagnostics_file": "test_gate_diagnostics.csv", + "attachment3_cases": attachment_count, + "attachment3_labeled_metrics": None, + "completed_utc": time.strftime("%Y-%m-%dT%H:%M:%SZ", time.gmtime()), + } + (RESULTS / "run_manifest.json").write_text(json.dumps(manifest, ensure_ascii=False, indent=2), encoding="utf-8") + print("Q2 complete:", json.dumps({"selected_model": best_model_name, "test_accuracy": test_metrics["accuracy"], + "test_macro_f1": test_metrics["macro_f1"], "test_mae": test_metrics["regression_mae"], + "temperature": temperature, "attachment3_cases": attachment_count}, ensure_ascii=False), flush=True) + + +if __name__ == "__main__": + main()