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PROJECT_README.md

@@ -35,11 +35,11 @@
 </p>
 
 
-**Ropedia Xperience-10M Task Suite** turns the public Xperience-10M sample into a readable embodied-AI benchmark surface. It keeps the evidence trail explicit: what is derived from the one public sample episode, what is evaluated on selected 128-episode held-out splits, what is mirrored to Hugging Face, and what still requires gated raw data or new model-specific evaluators.
+**Ropedia Xperience-10M Task Suite** is organized as two public result lines, not one blended benchmark. The 1-sample line is a fully inspectable task lab. The selected-128 line is the comparison surface for aligned baselines, Qwen3-Omni, and Cosmos branches. Every score points back to a source artifact and keeps direct-vs-proxy status visible.
 
 **Updated:** 2026-06-21.
 
-**Scope:** one public sample episode for the fully reproducible task suite; selected 128-episode public-safe artifacts for Qwen3-Omni, Cosmos3, metadata baselines, and raw-feature baselines. Raw Xperience-10M MP4/HDF5/RRD files, full Qwen weights, and gated data are not redistributed here.
+**Scope:** one public sample episode for raw-file inspection and reproducible task construction; selected 128-episode public-safe artifacts for same-split comparison and model-branch diagnostics. Raw Xperience-10M MP4/HDF5/RRD files, full Qwen weights, and gated data are not redistributed here.
 
 ## Contents
 
@@ -57,7 +57,7 @@
 
 ## How To Read This Project
 
-Use the first two tables to orient yourself, then jump to the evidence artifact that matches your question. The dashboard is the best visual overview; the GitHub repo is the source of truth for scripts and generated JSON; Hugging Face mirrors contain public-safe cards, metrics, figures, and model artifacts.
+Use the two evidence lines first, then choose the artifact that answers your question. The dashboard is the best visual overview; the GitHub repo is the source of truth for scripts and generated JSON; Hugging Face mirrors contain public-safe cards, metrics, figures, and model artifacts.
 
 The multilingual README files are reader guides. The canonical technical evidence is still the committed task contracts, result matrices, validation JSON, and public-safe result packages.
 
@@ -72,20 +72,24 @@ The multilingual README files are reader guides. The canonical technical evidenc
   </thead>
   <tbody>
     <tr>
-      <td><strong>20 task contracts</strong></td>
-      <td>Action, procedure, transition, trajectory, contact, objects, language, retrieval, reconstruction, order, sync, long-horizon forecasting, interaction text, action-object binding, sensor bridging, camera sync, and transition timing.</td>
+      <td><strong>Two result lines</strong></td>
+      <td><strong>1 sample episode</strong> for task construction and reproducibility. <strong>128 selected episodes</strong> for same-split baselines and model-branch comparison.</td>
     </tr>
     <tr>
       <td><strong>180 method-task records</strong></td>
-      <td>9 methods x 20 tasks. The current public matrix is complete at 180/180 scored records, with proxy flags kept visible where a compact substitute target is used.</td>
+      <td>9 methods x 20 tasks = 180/180 scored records. The ledger separates 174 direct scores from 6 compact-proxy scores.</td>
     </tr>
     <tr>
-      <td><strong>Public-sample baselines</strong></td>
-      <td>Minimal and Neural MLP baselines cover all 20 tasks on the one public sample episode.</td>
+      <td><strong>20 task contracts</strong></td>
+      <td>Action, procedure, transition, trajectory, contact, objects, language, retrieval, reconstruction, order, sync, long-horizon forecasting, interaction text, action-object binding, sensor bridging, camera sync, and transition timing.</td>
     </tr>
     <tr>
-      <td><strong>128-episode comparison layer</strong></td>
-      <td>Metadata/simple, metadata/NN, raw-feature simple, raw-feature NN, Qwen3-Omni, Cosmos3-Super, and Cosmos3-Nano branches are separated by evidence type.</td>
+      <td><strong>Line 1 methods</strong></td>
+      <td>Minimal and Neural MLP baselines cover all 20 tasks on the one public sample episode: 40/40 direct scores.</td>
+    </tr>
+    <tr>
+      <td><strong>Line 2 methods</strong></td>
+      <td>Metadata simple/NN, raw-feature simple/NN, Qwen3-Omni, Cosmos3-Super, and Cosmos3-Nano cover all 20 selected-128 task axes: 140/140 scores.</td>
     </tr>
     <tr>
       <td><strong>Foundation directions</strong></td>
@@ -100,30 +104,36 @@ The multilingual README files are reader guides. The canonical technical evidenc
 
 ## Two Evidence Lines
 
-The public suite is organized around two result lines. Keep them separate when
-reading metrics.
+The public suite is organized around two result lines. Keep them separate when reading metrics.
+
+<p align="center">
+  <img src="docs/assets/charts/two_evidence_line_map.svg" alt="Two evidence-line map: 1 sample episode and 128 selected episodes combine into 180 scored method-task records" width="100%">
+</p>
 
 <table>
   <thead>
     <tr>
       <th width="20%">Line</th>
-      <th width="26%">Data unit</th>
-      <th width="24%">Methods</th>
-      <th>Primary use</th>
+      <th width="24%">Data unit</th>
+      <th width="22%">Score statement</th>
+      <th width="20%">Valid claim</th>
+      <th>Do not claim</th>
     </tr>
   </thead>
   <tbody>
     <tr>
       <td><strong>1 sample episode</strong></td>
       <td>One public Xperience-10M sample episode: 5,821 frames, 1,161 aligned 20-frame windows, 8,546 feature dimensions.</td>
-      <td>Minimal heads and Neural MLP heads on all 20 tasks: 40/40 scored method-task records.</td>
-      <td>Inspect raw sample files, understand task definitions, rerun local baselines, and debug whether each task is well-posed.</td>
+      <td>40/40 direct scores from Minimal and Neural MLP heads.</td>
+      <td>Task construction, file inspection, local reproducibility, and controlled single-episode baselines.</td>
+      <td>Multi-episode generalization.</td>
     </tr>
     <tr>
       <td><strong>128 selected episodes</strong></td>
       <td>Selected held-out 96/16/16 split: 34,269 exported windows with public-safe processed features linked to official gated episode paths.</td>
-      <td>Metadata simple/NN, raw-feature simple/NN, Qwen3-Omni, Cosmos3-Super, and Cosmos3-Nano: 140/140 scored 128-line records.</td>
-      <td>Compare same-split baselines and model branches; use proxy flags where the public export lacks a direct raw target.</td>
+      <td>140/140 selected-128 scores: 134 direct + 6 compact-proxy.</td>
+      <td>Same-split comparison, model-branch diagnostics, and scale-up planning.</td>
+      <td>Reading proxy cells as direct raw-target measurements.</td>
     </tr>
   </tbody>
 </table>

README.de.md

@@ -49,6 +49,8 @@ Dieses Repository macht aus dem öffentlichen Xperience-10M-Sample eine prüfbar
 | 1 Sample-Episode | 5,821 Frames; 1,161 ausgerichtete 20-Frame-Fenster; 8,546 Dimensionen. | Minimal + Neural MLP auf 20 Aufgaben; 40/40 gescorte Einträge; alle sind direct scores. | Sample-Dateien, Aufgaben, reproduzierbare Baselines und Aufgabenqualität prüfen. |
 | 128 ausgewählte Episoden | 96/16/16 Split; 34,269 exportierte Fenster; public-safe Features mit offiziellen gated Episode-Pfaden. | Metadata simple/NN, raw-feature simple/NN, Qwen3-Omni, Cosmos3-Super und Cosmos3-Nano; 140/140 gescorte Einträge; 134 direct + 6 compact proxy. | Baselines und Modellzweige auf demselben Split vergleichen; Proxy-Targets bleiben sichtbar. |
 
+Formel: 2 Single-Episode-Methoden x 20 Aufgaben = 40; 7 128-Episode-Methoden x 20 Aufgaben = 140; öffentliche Gesamtmatrix = 180/180 gescorte Einträge.
+
 Einstieg: [`TWO_EVIDENCE_LINES.md`](TWO_EVIDENCE_LINES.md), [`two_evidence_lines.json`](docs/data/two_evidence_lines.json), [`task_method_20_result_matrix.json`](docs/data/task_method_20_result_matrix.json), [`two_evidence_line_result_summary.json`](docs/data/two_evidence_line_result_summary.json).
 
 ## Schneller Einstieg

README.es.md

@@ -49,6 +49,8 @@ Este repositorio convierte el episodio público de muestra de Xperience-10M en u
 | 1 episodio de muestra | 5,821 frames; 1,161 ventanas alineadas de 20 frames; 8,546 dimensiones. | Minimal + Neural MLP en 20 tareas; 40/40 registros con score; todos son direct scores. | Inspeccionar archivos de muestra, definiciones de tarea, baselines reproducibles y validez de tareas. |
 | 128 episodios seleccionados | Split 96/16/16; 34,269 ventanas exportadas; features public-safe ligadas a episode paths oficiales gated. | Metadata simple/NN, raw-feature simple/NN, Qwen3-Omni, Cosmos3-Super y Cosmos3-Nano; 140/140 registros con score; 134 direct + 6 compact proxy. | Comparar baselines y ramas de modelo en el mismo split; los proxy targets permanecen visibles. |
 
+Fórmula: 2 métodos de un episodio x 20 tareas = 40; 7 métodos de 128 episodios x 20 tareas = 140; matriz pública total = 180/180 registros con score.
+
 Entradas: [`TWO_EVIDENCE_LINES.md`](TWO_EVIDENCE_LINES.md), [`two_evidence_lines.json`](docs/data/two_evidence_lines.json), [`task_method_20_result_matrix.json`](docs/data/task_method_20_result_matrix.json), [`two_evidence_line_result_summary.json`](docs/data/two_evidence_line_result_summary.json).
 
 ## Ruta Rápida

README.fr.md

@@ -49,6 +49,8 @@ Ce dépôt transforme l'épisode public d'exemple Xperience-10M en laboratoire d
 | 1 épisode d'exemple | 5,821 frames; 1,161 fenêtres alignées de 20 frames; 8,546 dimensions. | Minimal + Neural MLP sur 20 tâches; 40/40 enregistrements scorés; tous sont des direct scores. | Inspecter les fichiers sample, les définitions de tâches, les baselines reproductibles et la validité des tâches. |
 | 128 épisodes sélectionnés | Split 96/16/16; 34,269 fenêtres exportées; features public-safe liées aux chemins gated officiels. | Metadata simple/NN, raw-feature simple/NN, Qwen3-Omni, Cosmos3-Super et Cosmos3-Nano; 140/140 enregistrements scorés; 134 direct + 6 compact proxy. | Comparer les baselines et branches de modèles sur le même split; les proxy targets restent visibles. |
 
+Formule : 2 méthodes sur 1 épisode x 20 tâches = 40; 7 méthodes sur 128 épisodes x 20 tâches = 140; matrice publique totale = 180/180 enregistrements scorés.
+
 Entrées : [`TWO_EVIDENCE_LINES.md`](TWO_EVIDENCE_LINES.md), [`two_evidence_lines.json`](docs/data/two_evidence_lines.json), [`task_method_20_result_matrix.json`](docs/data/task_method_20_result_matrix.json), [`two_evidence_line_result_summary.json`](docs/data/two_evidence_line_result_summary.json).
 
 ## Parcours Rapide

README.ja.md

@@ -49,6 +49,8 @@
 | 1 sample episode | 5,821 frames、1,161 aligned 20-frame windows、8,546 dimensions。 | Minimal + Neural MLP が 20 tasks を覆盖; 40/40 scored records; すべて direct scores。 | Raw sample files、task definitions、reproducible baselines、task validity を確認。 |
 | 128 selected episodes | 96/16/16 split、34,269 exported windows、public-safe features が official gated episode paths に対応。 | Metadata simple/NN、raw-feature simple/NN、Qwen3-Omni、Cosmos3-Super、Cosmos3-Nano; 140/140 scored records; 134 direct + 6 compact proxy。 | 同一 split の baselines と model branches を比較; proxy targets は明示。 |
 
+式: 1-episode methods 2 個 x 20 tasks = 40、128-episode methods 7 個 x 20 tasks = 140、公開 matrix 合計は 180/180 scored records。
+
 入口: [`TWO_EVIDENCE_LINES.md`](TWO_EVIDENCE_LINES.md)、[`two_evidence_lines.json`](docs/data/two_evidence_lines.json)、[`task_method_20_result_matrix.json`](docs/data/task_method_20_result_matrix.json)、[`two_evidence_line_result_summary.json`](docs/data/two_evidence_line_result_summary.json)。
 
 ## クイックルート

README.ko.md

@@ -49,6 +49,8 @@
 | 1 sample episode | 5,821 frames, 1,161 aligned 20-frame windows, 8,546 dimensions. | Minimal + Neural MLP가 20 tasks 전체를 평가; 40/40 scored records; 모두 direct scores. | Raw sample files, task definitions, reproducible baselines, task validity 확인. |
 | 128 selected episodes | 96/16/16 split, 34,269 exported windows, public-safe features가 official gated episode paths에 연결됨. | Metadata simple/NN, raw-feature simple/NN, Qwen3-Omni, Cosmos3-Super, Cosmos3-Nano; 140/140 scored records; 134 direct + 6 compact proxy. | 같은 split에서 baselines와 model branches 비교; proxy targets는 명시 유지. |
 
+공식: single-episode 방법 2개 x 20 tasks = 40; 128-episode 방법 7개 x 20 tasks = 140; 전체 공개 matrix = 180/180 scored records.
+
 입구: [`TWO_EVIDENCE_LINES.md`](TWO_EVIDENCE_LINES.md), [`two_evidence_lines.json`](docs/data/two_evidence_lines.json), [`task_method_20_result_matrix.json`](docs/data/task_method_20_result_matrix.json), [`two_evidence_line_result_summary.json`](docs/data/two_evidence_line_result_summary.json).
 
 ## 빠른 경로

README.md

@@ -66,7 +66,10 @@ The historical `tier2_task_suite` path is retained only for stable artifact
 links to tasks 13-20. The unified radar chart is published as
 `docs/assets/charts/unified_task_model_radar.svg` with values in
 `docs/data/unified_task_model_radar.json`; the 9-method by 20-task
-completion matrix is complete at `180/180` scored method-task records and is published in `docs/data/task_method_20_result_matrix.json`, with the explicit
+completion matrix is complete at `180/180` scored method-task records and is published in `docs/data/task_method_20_result_matrix.json`, with two-line summaries in
+`docs/assets/charts/two_evidence_line_map.svg`,
+`docs/data/two_evidence_lines.json`, and
+`docs/data/two_evidence_line_result_summary.json`, with the explicit
 audit in `docs/data/task_method_20_gap_audit.json` and source-value audit in
 `docs/data/task_method_20_source_audit.json`. Split radars are in
 `docs/assets/charts/single_episode_task_model_radar.svg` and

README.pt.md

@@ -49,6 +49,8 @@ Este repositório transforma o episódio público de amostra do Xperience-10M em
 | 1 episódio de amostra | 5,821 frames; 1,161 janelas alinhadas de 20 frames; 8,546 dimensões. | Minimal + Neural MLP em 20 tarefas; 40/40 registros com score; todos são direct scores. | Inspecionar arquivos da amostra, definições de tarefas, baselines reproduzíveis e validade das tarefas. |
 | 128 episódios selecionados | Split 96/16/16; 34,269 janelas exportadas; features public-safe ligadas aos caminhos oficiais gated. | Metadata simple/NN, raw-feature simple/NN, Qwen3-Omni, Cosmos3-Super e Cosmos3-Nano; 140/140 registros com score; 134 direct + 6 compact proxy. | Comparar baselines e ramos de modelo no mesmo split; proxy targets permanecem visíveis. |
 
+Fórmula: 2 métodos de um episódio x 20 tarefas = 40; 7 métodos de 128 episódios x 20 tarefas = 140; matriz pública total = 180/180 registros com score.
+
 Entradas: [`TWO_EVIDENCE_LINES.md`](TWO_EVIDENCE_LINES.md), [`two_evidence_lines.json`](docs/data/two_evidence_lines.json), [`task_method_20_result_matrix.json`](docs/data/task_method_20_result_matrix.json), [`two_evidence_line_result_summary.json`](docs/data/two_evidence_line_result_summary.json).
 
 ## Rota Rápida

README.zh.md

@@ -49,6 +49,8 @@
 | 1 sample episode | 5,821 帧；1,161 个 20-frame 对齐窗口；8,546 维特征。 | Minimal + Neural MLP；20 个任务全覆盖；40/40 scored records；全部为 direct scores。 | 检查原始 sample 文件、任务定义、可复现基线和每个任务是否成立。 |
 | 128 selected episodes | 96/16/16 split；34,269 个导出窗口；public-safe 特征链接到官方 gated episode path。 | Metadata simple/NN、raw-feature simple/NN、Qwen3-Omni、Cosmos3-Super、Cosmos3-Nano；140/140 scored records；134 direct + 6 compact proxy。 | 比较同一 split 上的基线和模型分支；proxy target 会显式标注。 |
 
+公式：2 个单 episode 方法 x 20 个任务 = 40；7 个 128-episode 方法 x 20 个任务 = 140；公开矩阵总计 180/180 scored records。
+
 入口：[`TWO_EVIDENCE_LINES.md`](TWO_EVIDENCE_LINES.md)、[`two_evidence_lines.json`](docs/data/two_evidence_lines.json)、[`task_method_20_result_matrix.json`](docs/data/task_method_20_result_matrix.json)、[`two_evidence_line_result_summary.json`](docs/data/two_evidence_line_result_summary.json)。
 
 ## 快速入口

TASK_METHOD_20_GAP_AUDIT.md

@@ -1,6 +1,6 @@
 # Task Method 20-Result Completion Audit
 
-Generated: `2026-06-21T07:36:39+00:00`
+Generated: `2026-06-21T08:38:20+00:00`
 
 This audit is the explicit completion ledger for the 9-method x 20-task result
 matrix. The current public matrix is complete at 180/180 scored records while

TWO_EVIDENCE_LINES.md

@@ -1,11 +1,15 @@
 # Two Evidence Lines
 
-The public Xperience-10M task suite has two result lines. Read them separately.
+The public Xperience-10M suite has two result lines. Read them separately.
 
-| Line | Data unit | Methods | Best use |
-| --- | --- | --- | --- |
-| 1 sample episode | One public sample episode; 5,821 frames; 1,161 aligned 20-frame windows; 8,546 feature dimensions. | Minimal heads and Neural MLP heads on all 20 tasks; 40/40 scored method-task records. | Inspect raw files, understand each task, rerun local baselines, and debug task quality. |
-| 128 selected episodes | Selected held-out 96/16/16 split; 34,269 exported windows; public-safe processed features linked to official gated episode paths. | Metadata simple/NN, raw-feature simple/NN, Qwen3-Omni, Cosmos3-Super, Cosmos3-Nano; 140/140 scored 128-line records: 134 direct + 6 compact-proxy scores. | Compare same-split baselines and model branches; keep proxy flags visible when direct raw targets are unavailable. |
+![Two evidence-line map](docs/assets/charts/two_evidence_line_map.svg)
+
+Score formula: 2 single-episode methods x 20 tasks = 40 records; 7 selected-128 methods x 20 tasks = 140 records; total public matrix = 180/180 scored records.
+
+| Line | Data unit | Score statement | Valid claim | Do not claim |
+| --- | --- | --- | --- | --- |
+| 1 sample episode | One public sample episode; 5,821 frames; 1,161 aligned 20-frame windows; 8,546 feature dimensions. | 40/40 direct scores from Minimal and Neural MLP heads. | Task construction, raw-file inspection, local reproducibility, and controlled single-episode baselines. | Multi-episode generalization. |
+| 128 selected episodes | Selected held-out 96/16/16 split; 34,269 exported windows; public-safe processed features linked to official gated episode paths. | 140/140 selected-128 scores: 134 direct + 6 compact-proxy. | Same-split baseline/model comparison, Qwen3/Cosmos diagnostics, and scale-up planning. | Reading compact-proxy cells as direct raw-target measurements. |
 
 ## Result Ledger
 
@@ -19,6 +23,7 @@ The public Xperience-10M task suite has two result lines. Read them separately.
 
 | Purpose | Artifact |
 | --- | --- |
+| Two-line map figure | [`docs/assets/charts/two_evidence_line_map.svg`](docs/assets/charts/two_evidence_line_map.svg) |
 | Unified 9-method x 20-task matrix | [`docs/data/task_method_20_result_matrix.json`](docs/data/task_method_20_result_matrix.json) |
 | Two-line result summary | [`docs/data/two_evidence_line_result_summary.json`](docs/data/two_evidence_line_result_summary.json) |
 | 1-episode radar data | [`docs/data/single_episode_task_model_radar.json`](docs/data/single_episode_task_model_radar.json) |
@@ -31,3 +36,10 @@ The public Xperience-10M task suite has two result lines. Read them separately.
 Use the 1-episode line for task construction and reproducibility claims.
 Use the 128-episode line for held-out comparison and model-branch claims.
 Do not mix those claims without naming the evidence line.
+
+## Reading Order
+
+1. Choose the evidence line.
+2. Open the matching radar.
+3. Inspect the matrix row for method, task, metric, source artifact, and proxy flag.
+4. Check compact-proxy cells before interpreting totals.

TWO_EVIDENCE_LINE_RESULT_SUMMARY.md

@@ -1,11 +1,22 @@
 # Two Evidence-Line Result Summary
 
-Generated: `2026-06-21T07:36:39+00:00`.
+Generated: `2026-06-21T08:38:20+00:00`.
 
 Source matrix: [`docs/data/task_method_20_result_matrix.json`](docs/data/task_method_20_result_matrix.json)
 
 Interpretation rule: Use the 1-episode line for task construction and reproducibility claims. Use the 128-episode line for held-out comparison and model-branch claims.
 
+## Read This First
+
+The suite has two public result lines. Line 1 is the fully inspectable one-episode task lab. Line 2 is the 128-episode comparison surface for aligned baselines, Qwen3-Omni, and Cosmos branches. Do not mix the two when reading scores.
+
+Score formula: 2 single-episode methods x 20 tasks = 40 records; 7 selected-128 methods x 20 tasks = 140 records; total public matrix = 180/180 scored records.
+
+| Line | What the scores mean | Valid claim | Do not claim |
+| --- | --- | --- | --- |
+| 1 sample episode | 40/40 direct scores from Minimal and Neural MLP heads on the same 20 task contracts. | Supports task construction, file inspection, local reproducibility, and controlled single-episode baseline claims. | Do not use this line as evidence of multi-episode generalization. |
+| 128 selected episodes | 140/140 selected-128 scores across seven method branches: 134 direct scores plus 6 documented compact-proxy scores. | Supports same-split comparison, model-branch diagnostics, and scale-up planning on public-safe processed artifacts. | Do not read compact-proxy cells as direct raw-target measurements. |
+
 ## Public Score Totals
 
 - Lines: 2
@@ -13,14 +24,28 @@ Interpretation rule: Use the 1-episode line for task construction and reproducib
 - Methods: 9
 - Scored records: 180/180
 - Direct scores: 174
-- Compact-proxy scores: 6
+- Compact-proxy scores: 6 documented cells
 
-## Line Ledger
+## Line Ledger And Entry Points
 
-| Line | Methods | Tasks | Scored records | Direct scores | Proxy scores | Method families |
-| --- | --- | --- | --- | --- | --- | --- |
-| 1 sample episode | 2 | 20 | 40/40 | 40 | 0 | Minimal, Neural MLP |
-| 128 selected episodes | 7 | 20 | 140/140 | 134 | 6 | 128ep Aligned Simple, 128ep Aligned NN, 128ep Raw Simple, 128ep Raw NN, Qwen3-Omni v6 LoRA, Cosmos3-Super Reasoner, Cosmos3-Nano Future Window |
+| Line | Methods | Tasks | Scored records | Direct scores | Proxy scores | Primary visuals | Source artifacts |
+| --- | --- | --- | --- | --- | --- | --- | --- |
+| 1 sample episode | 2 | 20 | 40/40 | 40 | 0 | docs/assets/charts/two_evidence_line_map.svg<br>docs/assets/charts/single_episode_task_model_radar.svg | docs/data/single_episode_task_model_radar.json<br>docs/data/two_evidence_line_result_summary.json<br>results/episode_task_suite/summary_report.json<br>results/episode_task_suite/feature_manifest.json<br>docs/single_episode_explorer.html |
+| 128 selected episodes | 7 | 20 | 140/140 | 134 | 6 | docs/assets/charts/two_evidence_line_map.svg<br>docs/assets/charts/episode128_task_model_radar.svg<br>docs/assets/charts/unified_task_model_radar.svg | docs/data/episode128_task_model_radar.json<br>docs/data/two_evidence_line_result_summary.json<br>docs/data/xperience10m_128_episode_feature_index.json<br>docs/data/omni_model_comparison.json<br>docs/data/task_method_20_gap_audit.json |
+
+## Method Detail By Line
+
+| Line | Method | Method detail | Scored records | Direct scores | Proxy scores |
+| --- | --- | --- | --- | --- | --- |
+| 1 sample episode | Minimal | Single-episode simple heads over the public sample split. | 20/20 | 20 | 0 |
+| 1 sample episode | Neural MLP | Single-episode compact PyTorch MLP heads on the same 20 task contracts. | 20/20 | 20 | 0 |
+| 128 selected episodes | 128ep Aligned Simple | 128-episode aligned simple baselines: JSONL metadata/text tasks plus staged sensor-block tasks where the processed target exists. | 20/20 | 19 | 1 |
+| 128 selected episodes | 128ep Aligned NN | 128-episode aligned MLP baselines: JSONL metadata/text tasks plus staged sensor-block tasks where the processed target exists. | 20/20 | 19 | 1 |
+| 128 selected episodes | 128ep Raw Simple | 128-episode 4430-dim sensor NPZ simple heads; tasks 15/19 use compact proxies. | 20/20 | 18 | 2 |
+| 128 selected episodes | 128ep Raw NN | 128-episode 4430-dim sensor NPZ MLP heads; tasks 15/19 use compact proxies. | 20/20 | 18 | 2 |
+| 128 selected episodes | Qwen3-Omni v6 LoRA | Verified held-out Qwen3-Omni v6 LoRA metrics, plus task 16 and any completed private-GPU future/retrieval/sensor-target probes scored from task-specific JSON. | 20/20 | 20 | 0 |
+| 128 selected episodes | Cosmos3-Super Reasoner | Verified Cosmos3-Super base-weight Reasoner JSON-task evaluation, plus task 5/8/9/10/11/12/13/14/16/17/18/19/20 probes where public metrics exist. | 20/20 | 20 | 0 |
+| 128 selected episodes | Cosmos3-Nano Future Window | Verified Cosmos3-Nano future-window compatibility metrics, plus model-output probes for tasks 2/5/7/8/10/11/12/13/14/15/16/17/18/19 and a derived task-20 boundary timing probe scored from held-out future-window artifacts. | 20/20 | 20 | 0 |
 
 ## Proxy-Scored Cells
 
@@ -33,6 +58,15 @@ Interpretation rule: Use the 1-episode line for task construction and reproducib
 | 19 | Camera-View Synchronization Retrieval | 128ep Raw Simple | mrr | documented compact proxy completion for this raw128 task axis |
 | 19 | Camera-View Synchronization Retrieval | 128ep Raw NN | mrr | documented compact proxy completion for this raw128 task axis |
 
+## Reading Order
+
+| Step | Reason |
+| --- | --- |
+| Choose the evidence line | Line 1 answers task-lab and reproducibility questions; line 2 answers selected-128 comparison questions. |
+| Open the matching radar | Use the 1-episode radar for Minimal-vs-Neural behavior and the 128-episode radar for baseline/model-branch comparison. |
+| Inspect the matrix row | Every numeric score is tied to a method, task, metric key, source artifact, and proxy flag. |
+| Check proxy cells before interpreting totals | The six compact-proxy cells are numeric but are not direct raw-target measurements. |
+
 ## Reader Policy
 
 - 1 sample episode: Use for task construction, raw-file inspection, local reproducibility, and controlled Minimal-vs-Neural baseline behavior.

data/artifact_index.json

@@ -1,8 +1,8 @@
 {
   "title": "Ropedia Xperience-10M Task Suite Artifact Index",
-  "generated_at_utc": "2026-06-20T21:45:18+00:00",
+  "generated_at_utc": "2026-06-21T08:41:38+00:00",
   "status": "pass",
-  "artifact_count": 225,
+  "artifact_count": 226,
   "missing": [],
   "by_kind": {
     "project_path": 18,
@@ -16,7 +16,7 @@
     "source_alignment": 5,
     "evaluation_protocol": 9,
     "website_data": 11,
-    "generated_figure": 7,
+    "generated_figure": 8,
     "visualization_builder": 1,
     "model_result": 5,
     "result_interpretation": 5,
@@ -610,7 +610,7 @@
       "shows": "Machine-readable source-alignment pass/fail check for repo, website, and HF surfaces.",
       "exists": true,
       "bytes": 4432,
-      "sha256": "a9a554c87ed0135db7ddf428d216488f37791002b699ffe01f1624bf00bee489"
+      "sha256": "7e921c5225389e3481f6133e6c3a1afb7f7f79ea5cdc4638ed3d1bfde48c63cf"
     },
     {
       "id": "source_alignment_validator",
@@ -730,8 +730,8 @@
       "surface": "website_hf",
       "shows": "Stores normalized 20-axis radar values, raw task metrics, Qwen3/Cosmos overlay mappings, branch-card caveats, proxy flags, and source artifacts.",
       "exists": true,
-      "bytes": 228799,
-      "sha256": "c9c708f64963dac10e764eaae8e1b14c7161a938afa5ef5723fe59dc4ce764af"
+      "bytes": 228805,
+      "sha256": "e947ff0579014d5f2c928f689077958d94304a3ac9d978d8475ce5b799e03df8"
     },
     {
       "id": "single_episode_task_model_radar_json",
@@ -742,7 +742,7 @@
       "shows": "Machine-readable split radar for the one-episode Minimal and Neural MLP baselines, both scored on all 20 task contracts.",
       "exists": true,
       "bytes": 51097,
-      "sha256": "d5e882120633f4d3ae90f1491682701c7593a42fc09e39b83fc5f375258e76e7"
+      "sha256": "f4975e8a1d02dd3a168660827fc92257257d18107887abc83ca225950fb283d7"
     },
     {
       "id": "episode128_task_model_radar_json",
@@ -753,7 +753,7 @@
       "shows": "Machine-readable split radar for selected 128-episode metadata/raw baselines and verified Qwen3/Cosmos branches, now complete at 140/140 scored rows with proxy notes retained.",
       "exists": true,
       "bytes": 184945,
-      "sha256": "8d4ef9c4cf1cf334fd41417d40fa0687ceefa964da9f8338c82f8cc6d36a3e76"
+      "sha256": "36d500a4f64614a88ed80af88594289adf06753ea85a2273b9bdaf6cb8ca7f44"
     },
     {
       "id": "task_method_20_result_matrix_json",
@@ -764,7 +764,7 @@
       "shows": "Machine-readable 9-method by 20-task matrix where every method has 20 records and the current release is complete at 180/180 scored rows.",
       "exists": true,
       "bytes": 128509,
-      "sha256": "382e538dff284c5e2cf19fe2b3eb014d1b48fb33082bb2ece532ce3de6c1e9bb"
+      "sha256": "5b02cd11edffe2e8f6f9d882bf5b895c308b8686cb6672e5df3c88e8e17a9ddd"
     },
     {
       "id": "task_method_20_result_matrix",
@@ -786,7 +786,7 @@
       "shows": "Machine-readable 180-record completion ledger with numeric scores, proxy flags, explicit status reasons, and source artifacts.",
       "exists": true,
       "bytes": 8500,
-      "sha256": "9cfd2ce8c4eb3bbe7e2af3f41df3b3ab74db9db08d9ea2e4f569f612358470dd"
+      "sha256": "5743354519dfae924d973ffca90a5d1ef4b0c316cf201b3ac443f6b5d4600de5"
     },
     {
       "id": "task_method_20_gap_audit",
@@ -797,7 +797,7 @@
       "shows": "Reader-facing ledger confirming 180/180 scored method-task cells and listing the six compact-proxy records separately.",
       "exists": true,
       "bytes": 3417,
-      "sha256": "3afc5db9803b6419ce4f40d6fb0dd5380ae182fb85b4f7b0f6ea6a46ae065c63"
+      "sha256": "01f47c74db965887e55f17b674e1617e396dd01a51fdc7bf9a9c7612f5596b2c"
     },
     {
       "id": "task_method_20_source_audit_json",
@@ -808,7 +808,7 @@
       "shows": "Machine-readable check that scored JSON-backed matrix cells match their declared metric source values.",
       "exists": true,
       "bytes": 561,
-      "sha256": "c3fd20cf992b70b53063001a8e71556c6f3aa320066d4f67a82554d192a87d88"
+      "sha256": "a2c684b7c6a60dc5868b796eec41adbc3a1eb37235d357271f3171b20f85c28f"
     },
     {
       "id": "task_method_20_source_audit",
@@ -819,7 +819,18 @@
       "shows": "Reader-facing source-value audit for the 180-result matrix.",
       "exists": true,
       "bytes": 447,
-      "sha256": "d21dcf00117db5f3466c981259f2c073f026bcde88b636d7ad0a43b6157a90a2"
+      "sha256": "0b1bc352200143957a177947b197cab6ee46602cda338b94bfc81922568ee9ea"
+    },
+    {
+      "id": "two_evidence_line_map_chart",
+      "title": "Two evidence-line map",
+      "path": "docs/assets/charts/two_evidence_line_map.svg",
+      "kind": "generated_figure",
+      "surface": "website_hf",
+      "shows": "Explains the public result organization: one sample-episode task-lab line, one selected-128 comparison line, and the combined 180/180 scored method-task ledger.",
+      "exists": true,
+      "bytes": 5323,
+      "sha256": "bd4161cc259b263a8858c8f77ecc2fe12c77526ac6896a9fabf26077b950f659"
     },
     {
       "id": "unified_task_model_radar_chart",
@@ -829,8 +840,8 @@
       "surface": "website_hf",
       "shows": "Compares minimal and neural MLP baselines across all 20 tasks, with Qwen3/Cosmos task-aligned model overlays.",
       "exists": true,
-      "bytes": 57937,
-      "sha256": "6d6fd9f83401ae49494560c27a0e3c5af0f350b4e74c4b1dc91326dae7ef1d47"
+      "bytes": 57938,
+      "sha256": "bb83b80b47fe679ebdce2c99378a4548120f1c8cc2d725b88e409d8c386dcbf8"
     },
     {
       "id": "single_episode_task_model_radar_chart",
@@ -840,8 +851,8 @@
       "surface": "website_hf",
       "shows": "Separates the one-episode Minimal and Neural MLP 20/20 scored baselines into a clean two-polygon radar.",
       "exists": true,
-      "bytes": 35232,
-      "sha256": "81fbda592ae9a79e80c50ff787b405899fec8c249f2def6bf67b6bff132cdc92"
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+      "sha256": "e5516268336fd7289f38c0b80937d40080f3b1c804e82a409405d60e6eab03b0"
     },
     {
       "id": "episode128_task_model_radar_chart",
@@ -851,8 +862,8 @@
       "surface": "website_hf",
       "shows": "Separates the selected 128-episode methods: raw-feature simple/NN as complete 20/20 scored polygons and metadata/Qwen/Cosmos as task-aligned overlays.",
       "exists": true,
-      "bytes": 51907,
-      "sha256": "9be33ccc103317e7e053b1d135b61e69a875c5404413e7caf428c83c605721d6"
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+      "sha256": "03e78b45fc91bab4c88e54bd0c3dc03afda4d55ef1f96569d7aedb2506d99065"
     },
     {
       "id": "unified_task_model_radar_builder",
@@ -862,8 +873,8 @@
       "surface": "repo_hf",
       "shows": "Regenerates the direction-aware radar chart and machine-readable metric overlay JSON.",
       "exists": true,
-      "bytes": 68542,
-      "sha256": "470b4c8acc437114b51d96987cd6324b9bf1d2ca16e9721d7fb00708aa58b383"
+      "bytes": 68555,
+      "sha256": "e7cf9d1d3e25117ccd0a2b93c69850d4201cd34bda97bf294fb3b037fc1aa351"
     },
     {
       "id": "task_method_20_gap_audit_builder",
@@ -1149,7 +1160,7 @@
       "shows": "Machine-readable release-check summary for validators, mirrors, and public project surfaces.",
       "exists": true,
       "bytes": 8640,
-      "sha256": "02b9408ac096e7444ff54ea69f478dac31c14c644d42a73f3f297bed89e034e7"
+      "sha256": "1046f75bd4529244290822c67fde137ae1465a3b65e6308b75acb856e4bee191"
     },
     {
       "id": "public_surface_qa",
@@ -1193,7 +1204,7 @@
       "volatile": true,
       "shows": "Machine-readable report for SEO/social metadata, accessible tab semantics, public links, project links, and clear project presentation.",
       "exists": true,
-      "bytes": 7208,
+      "bytes": 7363,
       "hash_policy": "existence_and_size_only"
     },
     {
@@ -1204,8 +1215,8 @@
       "surface": "repo_hf",
       "shows": "Regenerates the public presentation report before release.",
       "exists": true,
-      "bytes": 14863,
-      "sha256": "a0f7ff659de9f7c46c65f859c0c7595a5e42c54007858c21b89b13ef670c79f3"
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+      "sha256": "324a7332481f8065c7942659307994429f505d2ffd4a1c8169891ec017be68c2"
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     {
       "id": "task_surface_integrity",
@@ -1274,7 +1285,7 @@
       "volatile": true,
       "shows": "Records the last live GitHub/HF URL verification after upload.",
       "exists": true,
-      "bytes": 184670,
+      "bytes": 184684,
       "hash_policy": "existence_and_size_only"
     },
     {
@@ -1318,8 +1329,8 @@
       "surface": "repo_hf",
       "shows": "Generates the selective artifact catalog from local files.",
       "exists": true,
-      "bytes": 67105,
-      "sha256": "8fc1a2b5d4a50d49ff5738ec1e5e91088dbfa514c9f0485d3afe708add6d94a1"
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+      "sha256": "eae86845582f2551782fa7a81837bc3b30d67a050aced1a5f5158644ea0e6512"
     },
     {
       "id": "publication_audit",
@@ -1330,7 +1341,7 @@
       "volatile": true,
       "shows": "Confirms public bundles exclude raw data, caches, heavy archives, and credential text.",
       "exists": true,
-      "bytes": 10662,
+      "bytes": 10877,
       "hash_policy": "existence_and_size_only"
     },
     {
@@ -1354,7 +1365,7 @@
       "volatile": true,
       "shows": "Confirms prepared GitHub/HF Space/artifact/model mirrors share the same critical data, figure, website HTML, and validator files.",
       "exists": true,
-      "bytes": 1407249,
+      "bytes": 1413010,
       "hash_policy": "existence_and_size_only"
     },
     {
@@ -1366,7 +1377,7 @@
       "volatile": true,
       "shows": "Confirms local website links, anchors, JSON data files, and referenced images resolve.",
       "exists": true,
-      "bytes": 20141,
+      "bytes": 20542,
       "hash_policy": "existence_and_size_only"
     },
     {

data/episode128_task_model_radar.json

@@ -1,7 +1,7 @@
 {
   "title": "128-Episode 20-Task Radar",
   "status": "pass",
-  "generated_at_utc": "2026-06-20T20:38:21+00:00",
+  "generated_at_utc": "2026-06-21T08:37:32+00:00",
   "description": "Selected 128-episode metadata/raw baselines plus verified Qwen3/Cosmos branches. Every method has 20 records; numeric scores appear only where the public artifact produced that task target.",
   "task_count": 20,
   "method_count": 7,

data/mirror_parity.json

@@ -1,6 +1,6 @@
 {
   "status": "pass",
-  "generated_at_utc": "2026-06-21T08:16:26+00:00",
+  "generated_at_utc": "2026-06-21T08:46:12+00:00",
   "hf_root": "hf_publish",
   "summary": {
     "group_count": 1252,
@@ -138,45 +138,45 @@
       "local": {
         "path": "repo:docs/data/artifact_index.json",
         "exists": true,
-        "bytes": 122823,
-        "sha256": "e31a9d76c21ad4add92af1c5696bfb7efed51981cec6b2e0b9c67226a53a573b"
+        "bytes": 123351,
+        "sha256": "c926754b9fe708e83839e0601cc99d74d3974ca970cd32ab110b8fe8f3415256"
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       "mirrors": {
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           "exists": true,
-          "bytes": 122823,
-          "sha256": "e31a9d76c21ad4add92af1c5696bfb7efed51981cec6b2e0b9c67226a53a573b"
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           "path": "hf_artifacts:data/artifact_index.json",
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-          "bytes": 122823,
-          "sha256": "e31a9d76c21ad4add92af1c5696bfb7efed51981cec6b2e0b9c67226a53a573b"
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+          "sha256": "c926754b9fe708e83839e0601cc99d74d3974ca970cd32ab110b8fe8f3415256"
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           "path": "hf_artifacts:docs/data/artifact_index.json",
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-          "bytes": 122823,
-          "sha256": "e31a9d76c21ad4add92af1c5696bfb7efed51981cec6b2e0b9c67226a53a573b"
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-          "bytes": 122823,
-          "sha256": "e31a9d76c21ad4add92af1c5696bfb7efed51981cec6b2e0b9c67226a53a573b"
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           "path": "hf_model:docs/data/artifact_index.json",
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-          "bytes": 122823,
-          "sha256": "e31a9d76c21ad4add92af1c5696bfb7efed51981cec6b2e0b9c67226a53a573b"
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+          "sha256": "c926754b9fe708e83839e0601cc99d74d3974ca970cd32ab110b8fe8f3415256"
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         "hf_model": {
           "path": "hf_model:metrics/artifact_index.json",
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-          "bytes": 122823,
-          "sha256": "e31a9d76c21ad4add92af1c5696bfb7efed51981cec6b2e0b9c67226a53a573b"
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         }
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       "failures": []
@@ -922,45 +922,45 @@
       "local": {
         "path": "repo:docs/data/publication_audit.json",
         "exists": true,
-        "bytes": 10819,
-        "sha256": "6d76c7452b7c47e10a8c933c69b8a98402d3fd3db0d44608f73b9b67e4d3f58c"
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-          "sha256": "6d76c7452b7c47e10a8c933c69b8a98402d3fd3db0d44608f73b9b67e4d3f58c"
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-          "sha256": "6d76c7452b7c47e10a8c933c69b8a98402d3fd3db0d44608f73b9b67e4d3f58c"
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+          "sha256": "6ab67eb9df6e1a2422d13618aca557b8f78bcc745a98007e5c93af2259364c6f"
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-          "sha256": "6d76c7452b7c47e10a8c933c69b8a98402d3fd3db0d44608f73b9b67e4d3f58c"
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-          "sha256": "6d76c7452b7c47e10a8c933c69b8a98402d3fd3db0d44608f73b9b67e4d3f58c"
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+          "sha256": "6ab67eb9df6e1a2422d13618aca557b8f78bcc745a98007e5c93af2259364c6f"
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         "hf_model_docs_data": {
           "path": "hf_model:docs/data/publication_audit.json",
           "exists": true,
-          "bytes": 10819,
-          "sha256": "6d76c7452b7c47e10a8c933c69b8a98402d3fd3db0d44608f73b9b67e4d3f58c"
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         "hf_model": {
           "path": "hf_model:metrics/publication_audit.json",
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-          "bytes": 10819,
-          "sha256": "6d76c7452b7c47e10a8c933c69b8a98402d3fd3db0d44608f73b9b67e4d3f58c"
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@@ -971,45 +971,45 @@
       "local": {
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         "exists": true,
-        "bytes": 7208,
-        "sha256": "213bde8d5df28c2e4af0458bba400f6cb1c460250981bb125c62d627485840c0"
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           "exists": true,
-          "bytes": 7208,
-          "sha256": "213bde8d5df28c2e4af0458bba400f6cb1c460250981bb125c62d627485840c0"
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           "path": "hf_artifacts:data/public_surface_qa.json",
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-          "bytes": 7208,
-          "sha256": "213bde8d5df28c2e4af0458bba400f6cb1c460250981bb125c62d627485840c0"
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           "path": "hf_model:docs/data/public_surface_qa.json",
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-          "bytes": 7208,
-          "sha256": "213bde8d5df28c2e4af0458bba400f6cb1c460250981bb125c62d627485840c0"
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@@ -1119,44 +1119,44 @@
         "path": "repo:docs/data/quality_gates.json",
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@@ -31302,26 +31302,26 @@
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data/public_surface_qa.json

@@ -1,7 +1,7 @@
 {
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   "status": "pass",
-  "generated_at_utc": "2026-06-21T08:13:59+00:00",
+  "generated_at_utc": "2026-06-21T08:41:37+00:00",
   "scope": "Repo README, GitHub Pages HTML, Hugging Face Space card, artifact dataset card, and model card.",
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@@ -18,7 +18,7 @@
         "website_integrity": {
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           "status": "pass",
-          "generated_at_utc": "2026-06-21T08:12:52+00:00"
+          "generated_at_utc": "2026-06-21T08:38:53+00:00"
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@@ -28,27 +28,27 @@
         "task_surface_integrity": {
           "exists": true,
           "status": "pass",
-          "generated_at_utc": "2026-06-21T07:37:47+00:00"
+          "generated_at_utc": "2026-06-21T08:38:50+00:00"
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           "status": "pass",
-          "generated_at_utc": "2026-06-21T07:38:04+00:00"
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           "exists": true,
           "status": "pass",
-          "generated_at_utc": "2026-06-21T07:37:51+00:00"
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         "publication_package": {
           "exists": true,
           "status": "pass",
-          "generated_at_utc": "2026-06-21T07:43:11+00:00"
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           "status": "pass",
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@@ -95,10 +95,10 @@
       "status": "pass",
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-        "Ropedia Xperience-10M Task Suite": 19,
-        "Xperience-10M": 169,
-        "20-task": 72,
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+        "Ropedia Xperience-10M Task Suite": 20,
+        "Xperience-10M": 166,
+        "20-task": 71,
+        "Qwen3-Omni": 154,
         "128-episode pilot": 1
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@@ -132,12 +132,15 @@
         "data/research_roadmap.json": 15,
         "data/task_suite_enhancement_128.json": 22,
         "data/task_suite_20.json": 34,
+        "data/two_evidence_lines.json": 5,
+        "data/two_evidence_line_result_summary.json": 10,
         "data/unified_task_model_radar.json": 21,
         "data/single_episode_task_model_radar.json": 16,
         "data/episode128_task_model_radar.json": 16,
         "data/task_method_20_result_matrix.json": 24,
         "data/task_method_20_gap_audit.json": 21,
         "data/language_versions.json": 3,
+        "assets/charts/two_evidence_line_map.svg": 5,
         "assets/charts/unified_task_model_radar.svg": 17,
         "assets/charts/single_episode_task_model_radar.svg": 19,
         "assets/charts/episode128_task_model_radar.svg": 19,

data/publication_audit.json

@@ -1,6 +1,6 @@
 {
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-  "generated_at_utc": "2026-06-21T08:15:07+00:00",
+  "generated_at_utc": "2026-06-21T08:46:15+00:00",
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@@ -128,6 +128,7 @@
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     "docs/assets/brand/xperience10m-logo-social-card.png": true,
     "docs/assets/task_suite_infographic.png": true,
+    "docs/assets/charts/two_evidence_line_map.svg": true,
     "docs/assets/charts/unified_task_model_radar.svg": true,
     "docs/assets/charts/single_episode_task_model_radar.svg": true,
     "docs/assets/charts/episode128_task_model_radar.svg": true,
@@ -232,8 +233,8 @@
     "github_repo": {
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-      "text_file_count": 1257,
+      "file_count": 1519,
+      "text_file_count": 1258,
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         "bytes": 73057076
@@ -254,7 +255,7 @@
     "hf_artifact_bundle": {
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       "exists": true,
-      "file_count": 4489,
+      "file_count": 3037,
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@@ -265,7 +266,7 @@
     "hf_model_bundle": {
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+      "file_count": 3519,
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data/quality_gates.json

@@ -1,7 +1,7 @@
 {
   "title": "Ropedia Xperience-10M Release Checks",
   "status": "pass",
-  "generated_at_utc": "2026-06-21T08:13:59+00:00",
+  "generated_at_utc": "2026-06-21T08:38:50+00:00",
   "rule": "A release is current when the automated reports pass and the live GitHub/Hugging Face mirrors are verified after publishing.",
   "automated_gates": [
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data/scope_claims_audit.json

@@ -1,6 +1,6 @@
 {
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-  "generated_at_utc": "2026-06-21T08:14:02+00:00",
+  "generated_at_utc": "2026-06-21T08:38:55+00:00",
   "summary": {
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     "dataset_manifest_num_episodes": 119,

data/single_episode_task_model_radar.json

@@ -1,7 +1,7 @@
 {
   "title": "Single-Episode 20-Task Radar",
   "status": "pass",
-  "generated_at_utc": "2026-06-20T20:38:21+00:00",
+  "generated_at_utc": "2026-06-21T08:37:32+00:00",
   "description": "Minimal and Neural MLP baselines on the one public sample episode, both scored on all 20 task contracts.",
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data/source_alignment_audit.json

@@ -1,7 +1,7 @@
 {
   "title": "Ropedia Xperience-10M Source Alignment Note",
   "status": "pass",
-  "generated_at_utc": "2026-06-21T08:14:17+00:00",
+  "generated_at_utc": "2026-06-21T08:38:50+00:00",
   "alignment_json": "docs/data/xperience10m_dataset_card_alignment.json",
   "alignment_summary": {
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data/task_method_20_gap_audit.json

@@ -1,5 +1,5 @@
 {
-  "generated_at_utc": "2026-06-21T07:36:39+00:00",
+  "generated_at_utc": "2026-06-21T08:38:20+00:00",
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data/task_method_20_result_matrix.json

@@ -1,7 +1,7 @@
 {
   "title": "Task Method 20-Result Matrix",
   "status": "pass",
-  "generated_at_utc": "2026-06-20T20:38:21+00:00",
+  "generated_at_utc": "2026-06-21T08:37:32+00:00",
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   "method_task_record_count": 180,

data/task_method_20_source_audit.json

@@ -2,7 +2,7 @@
   "checked_json_metric_count": 180,
   "failure_count": 0,
   "failures": [],
-  "generated_at_utc": "2026-06-20T20:48:41+00:00",
+  "generated_at_utc": "2026-06-21T08:39:17+00:00",
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   "rule": "Every scored row that declares a JSON metric source must have the same numeric value under that row's metric_key.",
   "scored_method_task_count": 180,

data/task_surface_integrity.json

@@ -1,6 +1,6 @@
 {
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-  "generated_at_utc": "2026-06-21T08:13:59+00:00",
+  "generated_at_utc": "2026-06-21T08:38:50+00:00",
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     "expected_original_walkthrough_task_count": 12,

data/two_evidence_line_result_summary.json

@@ -1,5 +1,5 @@
 {
-  "generated_at_utc": "2026-06-21T07:36:39+00:00",
+  "generated_at_utc": "2026-06-21T08:38:20+00:00",
   "interpretation_rule": "Use the 1-episode line for task construction and reproducibility claims. Use the 128-episode line for held-out comparison and model-branch claims.",
   "lines": [
     {
@@ -10,6 +10,7 @@
         "results/episode_task_suite/feature_manifest.json",
         "docs/single_episode_explorer.html"
       ],
+      "claim_boundary": "Supports task construction, file inspection, local reproducibility, and controlled single-episode baseline claims.",
       "data_unit": "One public Xperience-10M sample episode",
       "direct_scored_method_task_count": 40,
       "id": "single_public_sample_episode",
@@ -44,9 +45,16 @@
           }
         }
       ],
+      "not_for": "Do not use this line as evidence of multi-episode generalization.",
       "primary_use": "Inspect raw files, understand each task, rerun local baselines, and debug task quality.",
+      "primary_visuals": [
+        "docs/assets/charts/two_evidence_line_map.svg",
+        "docs/assets/charts/single_episode_task_model_radar.svg"
+      ],
       "proxy_scored_method_task_count": 0,
+      "result_statement": "40/40 direct scores from Minimal and Neural MLP heads on the same 20 task contracts.",
       "scored_method_task_count": 40,
+      "short_label": "Line 1",
       "task_count": 20
     },
     {
@@ -57,6 +65,7 @@
         "docs/data/omni_model_comparison.json",
         "docs/data/task_method_20_gap_audit.json"
       ],
+      "claim_boundary": "Supports same-split comparison, model-branch diagnostics, and scale-up planning on public-safe processed artifacts.",
       "data_unit": "Selected held-out 96/16/16 split with public-safe processed features linked to official gated episode paths",
       "direct_scored_method_task_count": 134,
       "id": "selected_128_episode_surface",
@@ -160,9 +169,17 @@
           }
         }
       ],
+      "not_for": "Do not read compact-proxy cells as direct raw-target measurements.",
       "primary_use": "Compare same-split baselines and model branches while keeping evidence type explicit.",
+      "primary_visuals": [
+        "docs/assets/charts/two_evidence_line_map.svg",
+        "docs/assets/charts/episode128_task_model_radar.svg",
+        "docs/assets/charts/unified_task_model_radar.svg"
+      ],
       "proxy_scored_method_task_count": 6,
+      "result_statement": "140/140 selected-128 scores across seven method branches: 134 direct scores plus 6 documented compact-proxy scores.",
       "scored_method_task_count": 140,
+      "short_label": "Line 2",
       "task_count": 20
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@@ -239,6 +256,26 @@
     "selected_128_episode_surface": "Use for held-out comparison, metadata/raw-feature baselines, Qwen3/Cosmos branches, and scale-up decisions.",
     "single_public_sample_episode": "Use for task construction, raw-file inspection, local reproducibility, and controlled Minimal-vs-Neural baseline behavior."
   },
+  "reader_summary": "The suite has two public result lines. Line 1 is the fully inspectable one-episode task lab. Line 2 is the 128-episode comparison surface for aligned baselines, Qwen3-Omni, and Cosmos branches. Do not mix the two when reading scores.",
+  "reading_order": [
+    {
+      "reason": "Line 1 answers task-lab and reproducibility questions; line 2 answers selected-128 comparison questions.",
+      "step": "Choose the evidence line"
+    },
+    {
+      "reason": "Use the 1-episode radar for Minimal-vs-Neural behavior and the 128-episode radar for baseline/model-branch comparison.",
+      "step": "Open the matching radar"
+    },
+    {
+      "reason": "Every numeric score is tied to a method, task, metric key, source artifact, and proxy flag.",
+      "step": "Inspect the matrix row"
+    },
+    {
+      "reason": "The six compact-proxy cells are numeric but are not direct raw-target measurements.",
+      "step": "Check proxy cells before interpreting totals"
+    }
+  ],
+  "score_formula": "2 single-episode methods x 20 tasks = 40 records; 7 selected-128 methods x 20 tasks = 140 records; total public matrix = 180/180 scored records.",
   "source_lines": "docs/data/two_evidence_lines.json",
   "source_matrix": "docs/data/task_method_20_result_matrix.json",
   "status": "pass",

data/two_evidence_lines.json

@@ -2,11 +2,17 @@
   "status": "current",
   "updated_utc": "2026-06-21T00:00:00Z",
   "interpretation_rule": "Use the 1-episode line for task construction and reproducibility claims. Use the 128-episode line for held-out comparison and model-branch claims.",
+  "reader_summary": "The suite has two public result lines. Line 1 is the fully inspectable one-episode task lab. Line 2 is the 128-episode comparison surface for aligned baselines, Qwen3-Omni, and Cosmos branches. Do not mix the two when reading scores.",
+  "score_formula": "2 single-episode methods x 20 tasks = 40 records; 7 selected-128 methods x 20 tasks = 140 records; total public matrix = 180/180 scored records.",
   "lines": [
     {
       "id": "single_public_sample_episode",
       "label": "1 sample episode",
+      "short_label": "Line 1",
       "data_unit": "One public Xperience-10M sample episode",
+      "result_statement": "40/40 direct scores from Minimal and Neural MLP heads on the same 20 task contracts.",
+      "claim_boundary": "Supports task construction, file inspection, local reproducibility, and controlled single-episode baseline claims.",
+      "not_for": "Do not use this line as evidence of multi-episode generalization.",
       "frames": 5821,
       "windows": 1161,
       "window_definition": "20-frame aligned windows with 5-frame stride",
@@ -21,6 +27,10 @@
       "direct_scored_records": 40,
       "proxy_scored_records": 0,
       "best_use": "Inspect raw files, understand each task, rerun local baselines, and debug task quality.",
+      "primary_visuals": [
+        "docs/assets/charts/two_evidence_line_map.svg",
+        "docs/assets/charts/single_episode_task_model_radar.svg"
+      ],
       "primary_artifacts": [
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         "docs/data/two_evidence_line_result_summary.json",
@@ -32,7 +42,11 @@
     {
       "id": "selected_128_episode_surface",
       "label": "128 selected episodes",
+      "short_label": "Line 2",
       "data_unit": "Selected held-out 96/16/16 split with public-safe processed features linked to official gated episode paths",
+      "result_statement": "140/140 selected-128 scores across seven method branches: 134 direct scores plus 6 documented compact-proxy scores.",
+      "claim_boundary": "Supports same-split comparison, model-branch diagnostics, and scale-up planning on public-safe processed artifacts.",
+      "not_for": "Do not read compact-proxy cells as direct raw-target measurements.",
       "episodes": 128,
       "split": {
         "train": 96,
@@ -56,6 +70,11 @@
       "proxy_scored_records": 6,
       "proxy_policy": "Proxy flags remain visible where the public export lacks a direct raw target.",
       "best_use": "Compare same-split baselines and model branches while keeping evidence type explicit.",
+      "primary_visuals": [
+        "docs/assets/charts/two_evidence_line_map.svg",
+        "docs/assets/charts/episode128_task_model_radar.svg",
+        "docs/assets/charts/unified_task_model_radar.svg"
+      ],
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data/unified_task_model_radar.json

@@ -1,7 +1,7 @@
 {
   "title": "Unified 20-Task Model Radar",
   "status": "pass",
-  "generated_at_utc": "2026-06-20T20:38:21+00:00",
+  "generated_at_utc": "2026-06-21T08:37:32+00:00",
   "task_count": 20,
   "method_count": 9,
   "method_task_record_count": 180,
@@ -2471,7 +2471,7 @@
       "id": "raw128_simple",
       "title": "128ep Raw Simple",
       "status": "a100_raw20_complete_with_documented_proxies",
-      "coverage": "20 records / 20 scored axes; 18 direct + 2 proxy",
+      "coverage": "20 records / 20 scored records; 18 direct + 2 proxy",
       "headline": "34,269 windows; centroid/ridge heads over 4430-dim sensor blocks",
       "source": "results/omni_finetune/a100_128_raw20_task_baselines_complete20_proxy_20260616T091500Z/run_summary_all.json"
     },
@@ -2479,7 +2479,7 @@
       "id": "raw128_neural_mlp",
       "title": "128ep Raw NN",
       "status": "a100_raw20_complete_with_documented_proxies",
-      "coverage": "20 records / 20 scored axes; 18 direct + 2 proxy",
+      "coverage": "20 records / 20 scored records; 18 direct + 2 proxy",
       "headline": "MLP heads over staged features; tasks 15/19 use compact proxies",
       "source": "results/omni_finetune/a100_128_raw20_task_baselines_complete20_proxy_20260616T091500Z/run_summary_all.json"
     },

data/website_integrity.json

@@ -1,14 +1,14 @@
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-  "generated_at_utc": "2026-06-21T08:12:52+00:00",
+  "generated_at_utc": "2026-06-21T08:45:59+00:00",
   "docs_root": "docs",
   "site_base": "/ropedia-xperience-10m-task-suite/",
   "summary": {
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-    "local_references": 240,
+    "local_references": 241,
     "external_reference_count": 152,
     "json_files": 53,
-    "image_assets_referenced": 28,
+    "image_assets_referenced": 29,
     "failure_count": 0
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@@ -80,8 +80,8 @@
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       "status": "pass",
       "reason": "The project overview should appear before the deeper progress ledger.",
-      "overview_index": 112836,
-      "evidence_index": 152914
+      "overview_index": 115050,
+      "evidence_index": 155360
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@@ -159,9 +159,9 @@
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       "reason": "The evaluation protocol should appear before the deeper evidence ledger.",
-      "overview_index": 112836,
-      "protocol_index": 149095,
-      "evidence_index": 152914
+      "overview_index": 115050,
+      "protocol_index": 151541,
+      "evidence_index": 155360
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     {
       "name": "evaluation_protocol_links_json",
@@ -277,8 +277,8 @@
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       "path": "index.html",
       "id_count": 95,
-      "reference_count": 212,
-      "image_count": 34
+      "reference_count": 213,
+      "image_count": 35
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       "path": "research_roadmap.html",
@@ -301,7 +301,7 @@
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@@ -396,12 +396,12 @@
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@@ -531,22 +531,22 @@
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@@ -586,7 +586,7 @@
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-      "bytes": 51907,
+      "bytes": 51905,
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@@ -642,7 +642,7 @@
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       "exists": true,
-      "bytes": 35232,
+      "bytes": 35230,
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@@ -653,10 +653,17 @@
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       "has_viewbox": true
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+      "exists": true,
+      "bytes": 5323,
+      "format": "SVG",
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docs/data/mirror_parity.json

@@ -1,6 +1,6 @@
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-  "generated_at_utc": "2026-06-21T08:16:26+00:00",
+  "generated_at_utc": "2026-06-21T08:46:12+00:00",
   "hf_root": "hf_publish",
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@@ -138,45 +138,45 @@
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docs/index.html

@@ -4,7 +4,7 @@
   <meta charset="utf-8">
   <meta name="viewport" content="width=device-width, initial-scale=1">
   <title>Ropedia Xperience-10M Task Suite</title>
-  <meta name="description" content="A research-development task lab for Ropedia Xperience-10M: multimodal sample exploration, 20 embodied-AI tasks, baseline models, and a multi-episode fine-tuning path.">
+  <meta name="description" content="Ropedia Xperience-10M Task Suite organized into two evidence lines: one public sample episode for reproducible task construction and 128 selected episodes for aligned baselines plus Qwen3/Cosmos comparison.">
   <meta name="theme-color" content="#020502">
   <meta name="robots" content="index, follow">
   <link rel="canonical" href="https://chaoyue0307.github.io/ropedia-xperience-10m-task-suite/">
@@ -12,7 +12,7 @@
   <link rel="apple-touch-icon" href="apple-touch-icon.png">
   <link rel="manifest" href="site.webmanifest">
   <meta property="og:title" content="Ropedia Xperience-10M Task Suite">
-  <meta property="og:description" content="A Ropedia Xperience-10M research task lab with multimodal sample exploration, 20 task contracts, minimal and neural baselines, metrics, diagrams, and a scale-up plan.">
+  <meta property="og:description" content="A two-line Ropedia Xperience-10M public suite: 1 sample episode for task construction, 128 selected episodes for same-split baselines and Qwen3/Cosmos comparison.">
   <meta property="og:type" content="website">
   <meta property="og:url" content="https://chaoyue0307.github.io/ropedia-xperience-10m-task-suite/">
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@@ -20,7 +20,7 @@
   <meta property="og:image:height" content="630">
   <meta name="twitter:card" content="summary_large_image">
   <meta name="twitter:title" content="Ropedia Xperience-10M Task Suite">
-  <meta name="twitter:description" content="Xperience-10M research task lab with multimodal sample exploration, 20 task contracts, and minimal plus neural baselines.">
+  <meta name="twitter:description" content="Two evidence lines for Xperience-10M: 1 public sample episode and 128 selected episodes, with 180/180 scored method-task records.">
   <meta name="twitter:image" content="https://chaoyue0307.github.io/ropedia-xperience-10m-task-suite/assets/brand/xperience10m-logo-social-card.png?v=xperience10m-logo-v4">
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@@ -1006,6 +1006,30 @@
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       .line-table,
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@@ -3681,14 +3753,14 @@
   <header class="hero" id="top">
     <div class="wrap hero-inner">
       <div>
-        <div class="eyebrow">public sample episode / multimodal task lab</div>
+        <div class="eyebrow">two evidence lines / 180 scored records</div>
         <h1>Ropedia Xperience-10M Task Suite.</h1>
         <p class="hero-copy">
-          A public research surface for physical 4D intelligence: sample-to-task
-          contracts, multimodal baselines, verified multi-episode Qwen3-Omni
-          results, and a clear path toward Xperience-native foundation models.
-          Public raw-data boundaries stay explicit while staged derived
-          artifacts keep the latest model evidence recoverable.
+          The public suite has two result lines. Line 1 uses one public sample
+          episode to make the 20-task lab inspectable and reproducible. Line 2
+          uses 128 selected episodes to compare aligned baselines, Qwen3-Omni,
+          and Cosmos branches. The public matrix is complete at 180/180 scored
+          method-task records, with six compact-proxy cells explicitly marked.
         </p>
         <div class="hero-actions">
           <a class="button primary" href="#reader-map">Start guided path</a>
@@ -3699,23 +3771,31 @@
         <div class="suite-lines" aria-label="Two evidence lines">
           <article class="suite-line-card">
             <small>line 1 / public sample</small>
-            <h3>1 episode: task construction and reproducible baselines</h3>
-            <p>Use this line to inspect one full sample, understand each file, and rerun Minimal and Neural MLP task heads locally.</p>
+            <h3>1 sample episode: task lab</h3>
+            <p>One public episode becomes aligned windows, task targets, Minimal heads, and Neural MLP heads.</p>
+            <div class="line-claim">
+              <div><span>valid claim</span><p>Task construction, file inspection, and local reproducibility.</p></div>
+              <div><span>do not claim</span><p>Multi-episode generalization.</p></div>
+            </div>
             <div class="suite-line-facts">
               <span><strong>5,821</strong>frames</span>
               <span><strong>1,161</strong>20-frame windows</span>
-              <span><strong>40/40</strong>Minimal + NN task scores</span>
+              <span><strong>40/40</strong>direct task scores</span>
             </div>
             <a href="#raw-sample">Open sample line</a>
           </article>
           <article class="suite-line-card">
-            <small>line 2 / selected held-out suite</small>
-            <h3>128 episodes: aligned baselines and model branches</h3>
-            <p>Use this line to compare same-split metadata/raw baselines, Qwen3-Omni, and Cosmos diagnostics on the 20-task surface.</p>
+            <small>line 2 / 128 selected episodes</small>
+            <h3>128 selected episodes: comparison layer</h3>
+            <p>Seven method branches share the selected-episode surface and the same 20 task axes.</p>
+            <div class="line-claim">
+              <div><span>valid claim</span><p>Same-split baseline/model comparison and scale-up planning.</p></div>
+              <div><span>do not claim</span><p>Proxy cells as direct raw-target measurements.</p></div>
+            </div>
             <div class="suite-line-facts">
               <span><strong>128</strong>selected episodes</span>
               <span><strong>34,269</strong>exported windows</span>
-              <span><strong>140/140</strong>128-line task scores</span>
+              <span><strong>140/140</strong>134 direct + 6 proxy</span>
             </div>
             <a href="#suite">Open 128-episode line</a>
           </article>
@@ -3752,25 +3832,25 @@
       <div class="hero-radar-panel" aria-label="Unified 20-task radar comparison">
         <div class="hero-radar-top">
           <strong>home radar comparison</strong>
-          <span>180 method-task records / 180 scored axes / metadata+raw128 complete with documented proxy axes</span>
+          <span>two evidence lines / 180 scored records / 174 direct + 6 compact-proxy</span>
         </div>
         <div class="hero-radar-layout">
           <a class="hero-radar-frame" href="#suite" aria-label="Open full unified 20-task model radar">
-            <img src="assets/charts/unified_task_model_radar.svg?v=xperience10m-20task-radar-v6" alt="Unified 20-task model radar with full task-name key, method legend, 20-record counts, scored-axis counts, and raw128 proxy notes">
+            <img src="assets/charts/unified_task_model_radar.svg?v=xperience10m-20task-radar-v6" alt="Unified 20-task model radar with full task-name key, method legend, 20-record counts, score counts, and raw128 proxy notes">
           </a>
           <div class="hero-radar-copy">
-            <h2>Model comparison uses explicit task names and method contracts.</h2>
-            <p>The full SVG names every axis and keeps 20-result records, scored-axis counts, raw metric sources, and proxy notes attached to the same comparison view.</p>
+            <h2>Model comparison is split by evidence line.</h2>
+            <p>The full SVG names every task axis and keeps method records, source artifacts, and proxy notes attached to the same comparison view.</p>
             <div class="hero-radar-stats" aria-label="Radar coverage summary">
               <div class="hero-radar-stat"><strong>180</strong><span>method-task records</span></div>
-              <div class="hero-radar-stat"><strong>180</strong><span>scored axes</span></div>
-              <div class="hero-radar-stat"><strong>80/80</strong><span>metadata+raw pass</span></div>
+              <div class="hero-radar-stat"><strong>174</strong><span>direct scores</span></div>
+              <div class="hero-radar-stat"><strong>6</strong><span>compact-proxy scores</span></div>
               <div class="hero-radar-stat"><strong>34,269</strong><span>128ep windows</span></div>
             </div>
             <div class="hero-method-list" aria-label="Method families shown in the radar">
-              <div class="hero-method" style="--method-color:#67e8d1"><strong>Minimal + Neural MLP</strong><span>Single public-sample episode, full 20-task filled polygons.</span></div>
-              <div class="hero-method" style="--method-color:#f59e0b"><strong>128ep Metadata + Raw Baselines</strong><span>Every method has 20 records; metadata and raw NPZ heads now score all 20 axes, with compact proxy notes attached where the paired raw target is absent.</span></div>
-              <div class="hero-method" style="--method-color:#9bb8ff"><strong>Qwen3-Omni + Cosmos</strong><span>Verified held-out branches carry 20 records; Qwen3, Cosmos3-Super, and Cosmos3-Nano are now represented as 20/20 scored task rows with source/proxy notes attached in the matrix.</span></div>
+              <div class="hero-method" style="--method-color:#67e8d1"><strong>Line 1: Minimal + Neural MLP</strong><span>Single public-sample episode; 40/40 direct task scores.</span></div>
+              <div class="hero-method" style="--method-color:#f59e0b"><strong>Line 2: metadata + raw baselines</strong><span>Same selected-128 split; all four baseline rows have 20 records, with proxy notes where direct raw targets are absent.</span></div>
+              <div class="hero-method" style="--method-color:#9bb8ff"><strong>Line 2: Qwen3-Omni + Cosmos</strong><span>Qwen3, Cosmos3-Super, and Cosmos3-Nano are represented as selected-128 method rows with source notes in the matrix.</span></div>
             </div>
             <div class="hero-task-strip" aria-label="Radar task axis examples">
               <span>01 Action Recognition</span>
@@ -3837,15 +3917,19 @@
       <div class="wrap">
         <div class="section-head">
           <h2>Two evidence lines: 1 episode and 128 episodes.</h2>
-          <p>The project has two public reading paths. The 1-episode line is the fully inspectable task lab. The 128-episode line is the aligned comparison layer for same-split baselines and model branches. Keep them separate when interpreting results.</p>
+          <p>Read the suite as two lines. Line 1 proves the task lab is inspectable and reproducible. Line 2 compares selected-128 baselines and model branches. Keep the lines separate when interpreting scores.</p>
         </div>
+        <figure class="line-map-figure">
+          <img src="assets/charts/two_evidence_line_map.svg?v=two-line-map-v1" alt="Two evidence-line map showing 1 sample episode, 128 selected episodes, and the combined 180 scored method-task records">
+        </figure>
         <table class="line-table" aria-label="Two evidence-line comparison">
           <thead>
             <tr>
               <th>Line</th>
               <th>Data unit</th>
-              <th>Methods shown</th>
-              <th>Use this line for</th>
+              <th>Score statement</th>
+              <th>Valid claim</th>
+              <th>Do not claim</th>
               <th>Start here</th>
             </tr>
           </thead>
@@ -3853,15 +3937,17 @@
             <tr>
               <td>1 sample episode</td>
               <td>One public Xperience-10M sample episode; 5,821 frames; 1,161 aligned 20-frame windows; 8,546-dimensional feature contract.</td>
-              <td>Minimal heads and Neural MLP heads. Both cover all 20 task contracts, for 40/40 scored method-task records.</td>
+              <td>40/40 direct scores from Minimal and Neural MLP heads.</td>
               <td>Raw sample inspection, file organization, task definitions, local reproducibility, and controlled baseline behavior.</td>
+              <td>Multi-episode generalization.</td>
               <td><a href="#raw-sample">Raw browser</a><br><a href="data/single_episode_task_model_radar.json">1-episode radar JSON</a><br><a href="data/two_evidence_line_result_summary.json">result summary JSON</a><br><a href="data/two_evidence_lines.json">line JSON</a></td>
             </tr>
             <tr>
               <td>128 selected episodes</td>
               <td>Selected held-out 96/16/16 split; 34,269 exported windows; public-safe metadata/raw-feature artifacts linked to official gated episode paths.</td>
-              <td>Metadata simple/NN, raw-feature simple/NN, Qwen3-Omni, Cosmos3-Super, and Cosmos3-Nano. Together they form 140/140 scored 128-line method-task records.</td>
-              <td>Same-split comparison, model-branch diagnostics, Qwen/Cosmos evidence, and the next scale-up decisions.</td>
+              <td>140/140 selected-128 scores: 134 direct + 6 compact-proxy.</td>
+              <td>Same-split comparison, model-branch diagnostics, Qwen/Cosmos evidence, and scale-up decisions.</td>
+              <td>Reading compact-proxy cells as direct raw-target measurements.</td>
               <td><a href="data/episode128_task_model_radar.json">128-episode radar JSON</a><br><a href="data/xperience10m_128_episode_feature_index.json">feature index JSON</a><br><a href="data/two_evidence_line_result_summary.json">result summary JSON</a><br><a href="https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite/blob/main/TWO_EVIDENCE_LINES.md">line doc</a></td>
             </tr>
           </tbody>
@@ -4042,7 +4128,7 @@
           <article class="split-radar-card">
             <h3>128-Episode 20-Task Radar</h3>
             <p>Metadata, raw-feature, Qwen3-Omni, and Cosmos3 branches on the aligned 128-episode surface, with all 140 rows scored and proxy/evidence notes kept explicit.</p>
-            <img src="assets/charts/episode128_task_model_radar.svg?v=xperience10m-split-radar-v1" alt="128-episode 20-task radar comparing raw-feature baselines, metadata baselines, Qwen3-Omni, and Cosmos3 branches with explicit scored-axis counts">
+            <img src="assets/charts/episode128_task_model_radar.svg?v=xperience10m-split-radar-v1" alt="128-episode 20-task radar comparing raw-feature baselines, metadata baselines, Qwen3-Omni, and Cosmos3 branches with explicit score counts">
             <div class="split-radar-links">
               <a href="assets/charts/episode128_task_model_radar.svg">Open SVG</a>
               <a href="data/episode128_task_model_radar.json">Open JSON</a>
@@ -4685,10 +4771,10 @@
           </article>
           <article class="figure-brief-card">
             <h3>Score/proxy audit</h3>
-            <p>The matrix has 180 method-task records and 180 numeric scores. The audit records which artifacts support each score and marks compact-proxy axes where raw targets are absent.</p>
+            <p>The matrix has 180/180 scored method-task records: 174 direct scores and 6 compact-proxy scores. The audit records the source artifact, metric key, and proxy reason for each marked cell.</p>
           </article>
         </div>
-        <img class="chart" src="assets/charts/unified_task_model_radar.svg?v=xperience10m-20task-radar-v6" alt="Unified 20-task radar comparing Minimal, Neural MLP, 128-episode metadata/raw baselines, Qwen3-Omni, and Cosmos3 with task names, method details, 20-record counts, scored-axis counts, and proxy notes">
+        <img class="chart" src="assets/charts/unified_task_model_radar.svg?v=xperience10m-20task-radar-v6" alt="Unified 20-task radar comparing Minimal, Neural MLP, 128-episode metadata/raw baselines, Qwen3-Omni, and Cosmos3 with task names, method details, 20-record counts, score counts, and proxy notes">
         <div class="split-radar-grid" aria-label="Split 20-task radar comparisons">
           <article class="split-radar-card">
             <h3>1-Episode 20-Task Radar</h3>
@@ -4702,7 +4788,7 @@
           <article class="split-radar-card">
             <h3>128-Episode 20-Task Radar</h3>
             <p>Seven aligned 128-episode methods cover all 20 axes: metadata simple/NN, raw-feature simple/NN, Qwen3-Omni, Cosmos3-Super, and Cosmos3-Nano. Proxy axes stay labeled in the JSON.</p>
-            <img src="assets/charts/episode128_task_model_radar.svg?v=xperience10m-split-radar-v1" alt="128-episode 20-task radar comparing raw-feature baselines, metadata baselines, Qwen3-Omni, and Cosmos3 branches with explicit scored-axis counts">
+            <img src="assets/charts/episode128_task_model_radar.svg?v=xperience10m-split-radar-v1" alt="128-episode 20-task radar comparing raw-feature baselines, metadata baselines, Qwen3-Omni, and Cosmos3 branches with explicit score counts">
             <div class="split-radar-links">
               <a href="assets/charts/episode128_task_model_radar.svg">Open SVG</a>
               <a href="data/episode128_task_model_radar.json">Open JSON</a>
@@ -4795,13 +4881,38 @@
       <div class="wrap">
         <div class="section-head">
           <h2>Results by evidence line.</h2>
-          <p>Read the results as two layers. The 1-episode layer explains task behavior and reproducible baselines. The 128-episode layer compares aligned baselines and model branches, with proxy notes kept visible.</p>
+          <p>Read results in this order: choose the line, open the matching radar, inspect the matrix row, then check proxy flags before interpreting totals.</p>
+        </div>
+        <div class="result-reading-order" aria-label="How to read the result evidence">
+          <article class="result-reading-step">
+            <span>01</span>
+            <strong>Choose the line</strong>
+            <p>Use 1 episode for task-lab claims. Use 128 episodes for comparison claims.</p>
+          </article>
+          <article class="result-reading-step">
+            <span>02</span>
+            <strong>Open the radar</strong>
+            <p>Single-episode radar shows Minimal vs Neural MLP. 128 radar shows baseline and model branches.</p>
+          </article>
+          <article class="result-reading-step">
+            <span>03</span>
+            <strong>Inspect the matrix</strong>
+            <p>Each score keeps method, task, metric key, source artifact, and status.</p>
+          </article>
+          <article class="result-reading-step">
+            <span>04</span>
+            <strong>Check proxy cells</strong>
+            <p>Six selected-128 scores are compact proxies and stay marked in the audit.</p>
+          </article>
         </div>
         <div class="suite-lines" aria-label="Results split by evidence line">
           <article class="suite-line-card">
             <small>1 episode results</small>
             <h3>Task-lab evidence</h3>
             <p>Minimal and Neural MLP heads are both scored on all 20 public-sample task contracts. All 40 scores are direct task-target metrics.</p>
+            <div class="line-claim">
+              <div><span>best read as</span><p>A reproducible public task suite and baseline behavior check.</p></div>
+            </div>
             <div class="suite-line-facts">
               <span><strong>2</strong>methods</span>
               <span><strong>20</strong>task axes</span>
@@ -4813,6 +4924,9 @@
             <small>128 episode results</small>
             <h3>Scale-up evidence</h3>
             <p>Metadata/raw baselines and Qwen/Cosmos branches use the aligned 128-episode surface. It has 134 direct scores plus 6 compact-proxy scores.</p>
+            <div class="line-claim">
+              <div><span>best read as</span><p>A same-split comparison table with explicit source and proxy status.</p></div>
+            </div>
             <div class="suite-line-facts">
               <span><strong>7</strong>methods</span>
               <span><strong>20</strong>task axes</span>

index.html

@@ -4,7 +4,7 @@
   <meta charset="utf-8">
   <meta name="viewport" content="width=device-width, initial-scale=1">
   <title>Ropedia Xperience-10M Task Suite</title>
-  <meta name="description" content="A research-development task lab for Ropedia Xperience-10M: multimodal sample exploration, 20 embodied-AI tasks, baseline models, and a multi-episode fine-tuning path.">
+  <meta name="description" content="Ropedia Xperience-10M Task Suite organized into two evidence lines: one public sample episode for reproducible task construction and 128 selected episodes for aligned baselines plus Qwen3/Cosmos comparison.">
   <meta name="theme-color" content="#020502">
   <meta name="robots" content="index, follow">
   <link rel="canonical" href="https://chaoyue0307.github.io/ropedia-xperience-10m-task-suite/">
@@ -12,7 +12,7 @@
   <link rel="apple-touch-icon" href="apple-touch-icon.png">
   <link rel="manifest" href="site.webmanifest">
   <meta property="og:title" content="Ropedia Xperience-10M Task Suite">
-  <meta property="og:description" content="A Ropedia Xperience-10M research task lab with multimodal sample exploration, 20 task contracts, minimal and neural baselines, metrics, diagrams, and a scale-up plan.">
+  <meta property="og:description" content="A two-line Ropedia Xperience-10M public suite: 1 sample episode for task construction, 128 selected episodes for same-split baselines and Qwen3/Cosmos comparison.">
   <meta property="og:type" content="website">
   <meta property="og:url" content="https://chaoyue0307.github.io/ropedia-xperience-10m-task-suite/">
   <meta property="og:image" content="https://chaoyue0307.github.io/ropedia-xperience-10m-task-suite/assets/brand/xperience10m-logo-social-card.png?v=xperience10m-logo-v4">
@@ -20,7 +20,7 @@
   <meta property="og:image:height" content="630">
   <meta name="twitter:card" content="summary_large_image">
   <meta name="twitter:title" content="Ropedia Xperience-10M Task Suite">
-  <meta name="twitter:description" content="Xperience-10M research task lab with multimodal sample exploration, 20 task contracts, and minimal plus neural baselines.">
+  <meta name="twitter:description" content="Two evidence lines for Xperience-10M: 1 public sample episode and 128 selected episodes, with 180/180 scored method-task records.">
   <meta name="twitter:image" content="https://chaoyue0307.github.io/ropedia-xperience-10m-task-suite/assets/brand/xperience10m-logo-social-card.png?v=xperience10m-logo-v4">
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@@ -1006,6 +1006,30 @@
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@@ -1038,6 +1062,54 @@
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@@ -3308,7 +3380,7 @@
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-      .hero-stats, .models, .task-grid, .artifact-grid, .evidence-grid, .reading-grid, .snapshot-grid, .roadmap-grid, .brief-grid, .surface-map, .boundary-strip, .callout-row, .direction-grid, .baseline-strip, .extension-grid, .reader-journey, .resource-mode-grid, .suite-lines { grid-template-columns: repeat(2, minmax(0, 1fr)); }
+      .hero-stats, .models, .task-grid, .artifact-grid, .evidence-grid, .reading-grid, .snapshot-grid, .roadmap-grid, .brief-grid, .surface-map, .boundary-strip, .callout-row, .direction-grid, .baseline-strip, .extension-grid, .reader-journey, .resource-mode-grid, .suite-lines, .result-reading-order { grid-template-columns: repeat(2, minmax(0, 1fr)); }
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@@ -3492,7 +3564,7 @@
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+      .hero-stats, .models, .task-grid, .artifact-grid, .evidence-grid, .reading-grid, .snapshot-grid, .roadmap-grid, .brief-grid, .surface-map, .boundary-strip, .chart-grid, .callout-row, .direction-grid, .baseline-strip, .extension-grid, .walk-flow, .flow-steps, .storyboard-steps, .task-selector, .atlas-rows, .hero-paths, .reader-journey, .resource-mode-grid, .suite-lines, .suite-line-facts, .result-reading-order { grid-template-columns: 1fr; }
       .line-table,
       .line-table thead,
       .line-table tbody,
@@ -3681,14 +3753,14 @@
   <header class="hero" id="top">
     <div class="wrap hero-inner">
       <div>
-        <div class="eyebrow">public sample episode / multimodal task lab</div>
+        <div class="eyebrow">two evidence lines / 180 scored records</div>
         <h1>Ropedia Xperience-10M Task Suite.</h1>
         <p class="hero-copy">
-          A public research surface for physical 4D intelligence: sample-to-task
-          contracts, multimodal baselines, verified multi-episode Qwen3-Omni
-          results, and a clear path toward Xperience-native foundation models.
-          Public raw-data boundaries stay explicit while staged derived
-          artifacts keep the latest model evidence recoverable.
+          The public suite has two result lines. Line 1 uses one public sample
+          episode to make the 20-task lab inspectable and reproducible. Line 2
+          uses 128 selected episodes to compare aligned baselines, Qwen3-Omni,
+          and Cosmos branches. The public matrix is complete at 180/180 scored
+          method-task records, with six compact-proxy cells explicitly marked.
         </p>
         <div class="hero-actions">
           <a class="button primary" href="#reader-map">Start guided path</a>
@@ -3699,23 +3771,31 @@
         <div class="suite-lines" aria-label="Two evidence lines">
           <article class="suite-line-card">
             <small>line 1 / public sample</small>
-            <h3>1 episode: task construction and reproducible baselines</h3>
-            <p>Use this line to inspect one full sample, understand each file, and rerun Minimal and Neural MLP task heads locally.</p>
+            <h3>1 sample episode: task lab</h3>
+            <p>One public episode becomes aligned windows, task targets, Minimal heads, and Neural MLP heads.</p>
+            <div class="line-claim">
+              <div><span>valid claim</span><p>Task construction, file inspection, and local reproducibility.</p></div>
+              <div><span>do not claim</span><p>Multi-episode generalization.</p></div>
+            </div>
             <div class="suite-line-facts">
               <span><strong>5,821</strong>frames</span>
               <span><strong>1,161</strong>20-frame windows</span>
-              <span><strong>40/40</strong>Minimal + NN task scores</span>
+              <span><strong>40/40</strong>direct task scores</span>
             </div>
             <a href="#raw-sample">Open sample line</a>
           </article>
           <article class="suite-line-card">
-            <small>line 2 / selected held-out suite</small>
-            <h3>128 episodes: aligned baselines and model branches</h3>
-            <p>Use this line to compare same-split metadata/raw baselines, Qwen3-Omni, and Cosmos diagnostics on the 20-task surface.</p>
+            <small>line 2 / 128 selected episodes</small>
+            <h3>128 selected episodes: comparison layer</h3>
+            <p>Seven method branches share the selected-episode surface and the same 20 task axes.</p>
+            <div class="line-claim">
+              <div><span>valid claim</span><p>Same-split baseline/model comparison and scale-up planning.</p></div>
+              <div><span>do not claim</span><p>Proxy cells as direct raw-target measurements.</p></div>
+            </div>
             <div class="suite-line-facts">
               <span><strong>128</strong>selected episodes</span>
               <span><strong>34,269</strong>exported windows</span>
-              <span><strong>140/140</strong>128-line task scores</span>
+              <span><strong>140/140</strong>134 direct + 6 proxy</span>
             </div>
             <a href="#suite">Open 128-episode line</a>
           </article>
@@ -3752,25 +3832,25 @@
       <div class="hero-radar-panel" aria-label="Unified 20-task radar comparison">
         <div class="hero-radar-top">
           <strong>home radar comparison</strong>
-          <span>180 method-task records / 180 scored axes / metadata+raw128 complete with documented proxy axes</span>
+          <span>two evidence lines / 180 scored records / 174 direct + 6 compact-proxy</span>
         </div>
         <div class="hero-radar-layout">
           <a class="hero-radar-frame" href="#suite" aria-label="Open full unified 20-task model radar">
-            <img src="assets/charts/unified_task_model_radar.svg?v=xperience10m-20task-radar-v6" alt="Unified 20-task model radar with full task-name key, method legend, 20-record counts, scored-axis counts, and raw128 proxy notes">
+            <img src="assets/charts/unified_task_model_radar.svg?v=xperience10m-20task-radar-v6" alt="Unified 20-task model radar with full task-name key, method legend, 20-record counts, score counts, and raw128 proxy notes">
           </a>
           <div class="hero-radar-copy">
-            <h2>Model comparison uses explicit task names and method contracts.</h2>
-            <p>The full SVG names every axis and keeps 20-result records, scored-axis counts, raw metric sources, and proxy notes attached to the same comparison view.</p>
+            <h2>Model comparison is split by evidence line.</h2>
+            <p>The full SVG names every task axis and keeps method records, source artifacts, and proxy notes attached to the same comparison view.</p>
             <div class="hero-radar-stats" aria-label="Radar coverage summary">
               <div class="hero-radar-stat"><strong>180</strong><span>method-task records</span></div>
-              <div class="hero-radar-stat"><strong>180</strong><span>scored axes</span></div>
-              <div class="hero-radar-stat"><strong>80/80</strong><span>metadata+raw pass</span></div>
+              <div class="hero-radar-stat"><strong>174</strong><span>direct scores</span></div>
+              <div class="hero-radar-stat"><strong>6</strong><span>compact-proxy scores</span></div>
               <div class="hero-radar-stat"><strong>34,269</strong><span>128ep windows</span></div>
             </div>
             <div class="hero-method-list" aria-label="Method families shown in the radar">
-              <div class="hero-method" style="--method-color:#67e8d1"><strong>Minimal + Neural MLP</strong><span>Single public-sample episode, full 20-task filled polygons.</span></div>
-              <div class="hero-method" style="--method-color:#f59e0b"><strong>128ep Metadata + Raw Baselines</strong><span>Every method has 20 records; metadata and raw NPZ heads now score all 20 axes, with compact proxy notes attached where the paired raw target is absent.</span></div>
-              <div class="hero-method" style="--method-color:#9bb8ff"><strong>Qwen3-Omni + Cosmos</strong><span>Verified held-out branches carry 20 records; Qwen3, Cosmos3-Super, and Cosmos3-Nano are now represented as 20/20 scored task rows with source/proxy notes attached in the matrix.</span></div>
+              <div class="hero-method" style="--method-color:#67e8d1"><strong>Line 1: Minimal + Neural MLP</strong><span>Single public-sample episode; 40/40 direct task scores.</span></div>
+              <div class="hero-method" style="--method-color:#f59e0b"><strong>Line 2: metadata + raw baselines</strong><span>Same selected-128 split; all four baseline rows have 20 records, with proxy notes where direct raw targets are absent.</span></div>
+              <div class="hero-method" style="--method-color:#9bb8ff"><strong>Line 2: Qwen3-Omni + Cosmos</strong><span>Qwen3, Cosmos3-Super, and Cosmos3-Nano are represented as selected-128 method rows with source notes in the matrix.</span></div>
             </div>
             <div class="hero-task-strip" aria-label="Radar task axis examples">
               <span>01 Action Recognition</span>
@@ -3837,15 +3917,19 @@
       <div class="wrap">
         <div class="section-head">
           <h2>Two evidence lines: 1 episode and 128 episodes.</h2>
-          <p>The project has two public reading paths. The 1-episode line is the fully inspectable task lab. The 128-episode line is the aligned comparison layer for same-split baselines and model branches. Keep them separate when interpreting results.</p>
+          <p>Read the suite as two lines. Line 1 proves the task lab is inspectable and reproducible. Line 2 compares selected-128 baselines and model branches. Keep the lines separate when interpreting scores.</p>
         </div>
+        <figure class="line-map-figure">
+          <img src="assets/charts/two_evidence_line_map.svg?v=two-line-map-v1" alt="Two evidence-line map showing 1 sample episode, 128 selected episodes, and the combined 180 scored method-task records">
+        </figure>
         <table class="line-table" aria-label="Two evidence-line comparison">
           <thead>
             <tr>
               <th>Line</th>
               <th>Data unit</th>
-              <th>Methods shown</th>
-              <th>Use this line for</th>
+              <th>Score statement</th>
+              <th>Valid claim</th>
+              <th>Do not claim</th>
               <th>Start here</th>
             </tr>
           </thead>
@@ -3853,15 +3937,17 @@
             <tr>
               <td>1 sample episode</td>
               <td>One public Xperience-10M sample episode; 5,821 frames; 1,161 aligned 20-frame windows; 8,546-dimensional feature contract.</td>
-              <td>Minimal heads and Neural MLP heads. Both cover all 20 task contracts, for 40/40 scored method-task records.</td>
+              <td>40/40 direct scores from Minimal and Neural MLP heads.</td>
               <td>Raw sample inspection, file organization, task definitions, local reproducibility, and controlled baseline behavior.</td>
+              <td>Multi-episode generalization.</td>
               <td><a href="#raw-sample">Raw browser</a><br><a href="data/single_episode_task_model_radar.json">1-episode radar JSON</a><br><a href="data/two_evidence_line_result_summary.json">result summary JSON</a><br><a href="data/two_evidence_lines.json">line JSON</a></td>
             </tr>
             <tr>
               <td>128 selected episodes</td>
               <td>Selected held-out 96/16/16 split; 34,269 exported windows; public-safe metadata/raw-feature artifacts linked to official gated episode paths.</td>
-              <td>Metadata simple/NN, raw-feature simple/NN, Qwen3-Omni, Cosmos3-Super, and Cosmos3-Nano. Together they form 140/140 scored 128-line method-task records.</td>
-              <td>Same-split comparison, model-branch diagnostics, Qwen/Cosmos evidence, and the next scale-up decisions.</td>
+              <td>140/140 selected-128 scores: 134 direct + 6 compact-proxy.</td>
+              <td>Same-split comparison, model-branch diagnostics, Qwen/Cosmos evidence, and scale-up decisions.</td>
+              <td>Reading compact-proxy cells as direct raw-target measurements.</td>
               <td><a href="data/episode128_task_model_radar.json">128-episode radar JSON</a><br><a href="data/xperience10m_128_episode_feature_index.json">feature index JSON</a><br><a href="data/two_evidence_line_result_summary.json">result summary JSON</a><br><a href="https://github.com/ChaoYue0307/ropedia-xperience-10m-task-suite/blob/main/TWO_EVIDENCE_LINES.md">line doc</a></td>
             </tr>
           </tbody>
@@ -4042,7 +4128,7 @@
           <article class="split-radar-card">
             <h3>128-Episode 20-Task Radar</h3>
             <p>Metadata, raw-feature, Qwen3-Omni, and Cosmos3 branches on the aligned 128-episode surface, with all 140 rows scored and proxy/evidence notes kept explicit.</p>
-            <img src="assets/charts/episode128_task_model_radar.svg?v=xperience10m-split-radar-v1" alt="128-episode 20-task radar comparing raw-feature baselines, metadata baselines, Qwen3-Omni, and Cosmos3 branches with explicit scored-axis counts">
+            <img src="assets/charts/episode128_task_model_radar.svg?v=xperience10m-split-radar-v1" alt="128-episode 20-task radar comparing raw-feature baselines, metadata baselines, Qwen3-Omni, and Cosmos3 branches with explicit score counts">
             <div class="split-radar-links">
               <a href="assets/charts/episode128_task_model_radar.svg">Open SVG</a>
               <a href="data/episode128_task_model_radar.json">Open JSON</a>
@@ -4685,10 +4771,10 @@
           </article>
           <article class="figure-brief-card">
             <h3>Score/proxy audit</h3>
-            <p>The matrix has 180 method-task records and 180 numeric scores. The audit records which artifacts support each score and marks compact-proxy axes where raw targets are absent.</p>
+            <p>The matrix has 180/180 scored method-task records: 174 direct scores and 6 compact-proxy scores. The audit records the source artifact, metric key, and proxy reason for each marked cell.</p>
           </article>
         </div>
-        <img class="chart" src="assets/charts/unified_task_model_radar.svg?v=xperience10m-20task-radar-v6" alt="Unified 20-task radar comparing Minimal, Neural MLP, 128-episode metadata/raw baselines, Qwen3-Omni, and Cosmos3 with task names, method details, 20-record counts, scored-axis counts, and proxy notes">
+        <img class="chart" src="assets/charts/unified_task_model_radar.svg?v=xperience10m-20task-radar-v6" alt="Unified 20-task radar comparing Minimal, Neural MLP, 128-episode metadata/raw baselines, Qwen3-Omni, and Cosmos3 with task names, method details, 20-record counts, score counts, and proxy notes">
         <div class="split-radar-grid" aria-label="Split 20-task radar comparisons">
           <article class="split-radar-card">
             <h3>1-Episode 20-Task Radar</h3>
@@ -4702,7 +4788,7 @@
           <article class="split-radar-card">
             <h3>128-Episode 20-Task Radar</h3>
             <p>Seven aligned 128-episode methods cover all 20 axes: metadata simple/NN, raw-feature simple/NN, Qwen3-Omni, Cosmos3-Super, and Cosmos3-Nano. Proxy axes stay labeled in the JSON.</p>
-            <img src="assets/charts/episode128_task_model_radar.svg?v=xperience10m-split-radar-v1" alt="128-episode 20-task radar comparing raw-feature baselines, metadata baselines, Qwen3-Omni, and Cosmos3 branches with explicit scored-axis counts">
+            <img src="assets/charts/episode128_task_model_radar.svg?v=xperience10m-split-radar-v1" alt="128-episode 20-task radar comparing raw-feature baselines, metadata baselines, Qwen3-Omni, and Cosmos3 branches with explicit score counts">
             <div class="split-radar-links">
               <a href="assets/charts/episode128_task_model_radar.svg">Open SVG</a>
               <a href="data/episode128_task_model_radar.json">Open JSON</a>
@@ -4795,13 +4881,38 @@
       <div class="wrap">
         <div class="section-head">
           <h2>Results by evidence line.</h2>
-          <p>Read the results as two layers. The 1-episode layer explains task behavior and reproducible baselines. The 128-episode layer compares aligned baselines and model branches, with proxy notes kept visible.</p>
+          <p>Read results in this order: choose the line, open the matching radar, inspect the matrix row, then check proxy flags before interpreting totals.</p>
+        </div>
+        <div class="result-reading-order" aria-label="How to read the result evidence">
+          <article class="result-reading-step">
+            <span>01</span>
+            <strong>Choose the line</strong>
+            <p>Use 1 episode for task-lab claims. Use 128 episodes for comparison claims.</p>
+          </article>
+          <article class="result-reading-step">
+            <span>02</span>
+            <strong>Open the radar</strong>
+            <p>Single-episode radar shows Minimal vs Neural MLP. 128 radar shows baseline and model branches.</p>
+          </article>
+          <article class="result-reading-step">
+            <span>03</span>
+            <strong>Inspect the matrix</strong>
+            <p>Each score keeps method, task, metric key, source artifact, and status.</p>
+          </article>
+          <article class="result-reading-step">
+            <span>04</span>
+            <strong>Check proxy cells</strong>
+            <p>Six selected-128 scores are compact proxies and stay marked in the audit.</p>
+          </article>
         </div>
         <div class="suite-lines" aria-label="Results split by evidence line">
           <article class="suite-line-card">
             <small>1 episode results</small>
             <h3>Task-lab evidence</h3>
             <p>Minimal and Neural MLP heads are both scored on all 20 public-sample task contracts. All 40 scores are direct task-target metrics.</p>
+            <div class="line-claim">
+              <div><span>best read as</span><p>A reproducible public task suite and baseline behavior check.</p></div>
+            </div>
             <div class="suite-line-facts">
               <span><strong>2</strong>methods</span>
               <span><strong>20</strong>task axes</span>
@@ -4813,6 +4924,9 @@
             <small>128 episode results</small>
             <h3>Scale-up evidence</h3>
             <p>Metadata/raw baselines and Qwen/Cosmos branches use the aligned 128-episode surface. It has 134 direct scores plus 6 compact-proxy scores.</p>
+            <div class="line-claim">
+              <div><span>best read as</span><p>A same-split comparison table with explicit source and proxy status.</p></div>
+            </div>
             <div class="suite-line-facts">
               <span><strong>7</strong>methods</span>
               <span><strong>20</strong>task axes</span>

scripts/build_artifact_index.py

@@ -589,6 +589,14 @@ ARTIFACTS = [
         "surface": "repo_hf",
         "shows": "Reader-facing source-value audit for the 180-result matrix.",
     },
+    {
+        "id": "two_evidence_line_map_chart",
+        "title": "Two evidence-line map",
+        "path": "docs/assets/charts/two_evidence_line_map.svg",
+        "kind": "generated_figure",
+        "surface": "website_hf",
+        "shows": "Explains the public result organization: one sample-episode task-lab line, one selected-128 comparison line, and the combined 180/180 scored method-task ledger.",
+    },
     {
         "id": "unified_task_model_radar_chart",
         "title": "Unified 20-task model radar",

scripts/build_multilingual_public_readmes.py

@@ -67,11 +67,11 @@ ENGLISH_TOP = f"""{hero(
     "en",
 )}
 
-**Ropedia Xperience-10M Task Suite** turns the public Xperience-10M sample into a readable embodied-AI benchmark surface. It keeps the evidence trail explicit: what is derived from the one public sample episode, what is evaluated on selected 128-episode held-out splits, what is mirrored to Hugging Face, and what still requires gated raw data or new model-specific evaluators.
+**Ropedia Xperience-10M Task Suite** is organized as two public result lines, not one blended benchmark. The 1-sample line is a fully inspectable task lab. The selected-128 line is the comparison surface for aligned baselines, Qwen3-Omni, and Cosmos branches. Every score points back to a source artifact and keeps direct-vs-proxy status visible.
 
 **Updated:** {UPDATED}.
 
-**Scope:** one public sample episode for the fully reproducible task suite; selected 128-episode public-safe artifacts for Qwen3-Omni, Cosmos3, metadata baselines, and raw-feature baselines. Raw Xperience-10M MP4/HDF5/RRD files, full Qwen weights, and gated data are not redistributed here.
+**Scope:** one public sample episode for raw-file inspection and reproducible task construction; selected 128-episode public-safe artifacts for same-split comparison and model-branch diagnostics. Raw Xperience-10M MP4/HDF5/RRD files, full Qwen weights, and gated data are not redistributed here.
 
 ## Contents
 
@@ -89,7 +89,7 @@ ENGLISH_TOP = f"""{hero(
 
 ## How To Read This Project
 
-Use the first two tables to orient yourself, then jump to the evidence artifact that matches your question. The dashboard is the best visual overview; the GitHub repo is the source of truth for scripts and generated JSON; Hugging Face mirrors contain public-safe cards, metrics, figures, and model artifacts.
+Use the two evidence lines first, then choose the artifact that answers your question. The dashboard is the best visual overview; the GitHub repo is the source of truth for scripts and generated JSON; Hugging Face mirrors contain public-safe cards, metrics, figures, and model artifacts.
 
 The multilingual README files are reader guides. The canonical technical evidence is still the committed task contracts, result matrices, validation JSON, and public-safe result packages.
 
@@ -104,20 +104,24 @@ The multilingual README files are reader guides. The canonical technical evidenc
   </thead>
   <tbody>
     <tr>
-      <td><strong>20 task contracts</strong></td>
-      <td>Action, procedure, transition, trajectory, contact, objects, language, retrieval, reconstruction, order, sync, long-horizon forecasting, interaction text, action-object binding, sensor bridging, camera sync, and transition timing.</td>
+      <td><strong>Two result lines</strong></td>
+      <td><strong>1 sample episode</strong> for task construction and reproducibility. <strong>128 selected episodes</strong> for same-split baselines and model-branch comparison.</td>
     </tr>
     <tr>
       <td><strong>180 method-task records</strong></td>
-      <td>9 methods x 20 tasks. The current public matrix is complete at 180/180 scored records, with proxy flags kept visible where a compact substitute target is used.</td>
+      <td>9 methods x 20 tasks = 180/180 scored records. The ledger separates 174 direct scores from 6 compact-proxy scores.</td>
+    </tr>
+    <tr>
+      <td><strong>20 task contracts</strong></td>
+      <td>Action, procedure, transition, trajectory, contact, objects, language, retrieval, reconstruction, order, sync, long-horizon forecasting, interaction text, action-object binding, sensor bridging, camera sync, and transition timing.</td>
     </tr>
     <tr>
-      <td><strong>Public-sample baselines</strong></td>
-      <td>Minimal and Neural MLP baselines cover all 20 tasks on the one public sample episode.</td>
+      <td><strong>Line 1 methods</strong></td>
+      <td>Minimal and Neural MLP baselines cover all 20 tasks on the one public sample episode: 40/40 direct scores.</td>
     </tr>
     <tr>
-      <td><strong>128-episode comparison layer</strong></td>
-      <td>Metadata/simple, metadata/NN, raw-feature simple, raw-feature NN, Qwen3-Omni, Cosmos3-Super, and Cosmos3-Nano branches are separated by evidence type.</td>
+      <td><strong>Line 2 methods</strong></td>
+      <td>Metadata simple/NN, raw-feature simple/NN, Qwen3-Omni, Cosmos3-Super, and Cosmos3-Nano cover all 20 selected-128 task axes: 140/140 scores.</td>
     </tr>
     <tr>
       <td><strong>Foundation directions</strong></td>
@@ -132,30 +136,36 @@ The multilingual README files are reader guides. The canonical technical evidenc
 
 ## Two Evidence Lines
 
-The public suite is organized around two result lines. Keep them separate when
-reading metrics.
+The public suite is organized around two result lines. Keep them separate when reading metrics.
+
+<p align="center">
+  <img src="docs/assets/charts/two_evidence_line_map.svg" alt="Two evidence-line map: 1 sample episode and 128 selected episodes combine into 180 scored method-task records" width="100%">
+</p>
 
 <table>
   <thead>
     <tr>
       <th width="20%">Line</th>
-      <th width="26%">Data unit</th>
-      <th width="24%">Methods</th>
-      <th>Primary use</th>
+      <th width="24%">Data unit</th>
+      <th width="22%">Score statement</th>
+      <th width="20%">Valid claim</th>
+      <th>Do not claim</th>
     </tr>
   </thead>
   <tbody>
     <tr>
       <td><strong>1 sample episode</strong></td>
       <td>One public Xperience-10M sample episode: 5,821 frames, 1,161 aligned 20-frame windows, 8,546 feature dimensions.</td>
-      <td>Minimal heads and Neural MLP heads on all 20 tasks: 40/40 scored method-task records.</td>
-      <td>Inspect raw sample files, understand task definitions, rerun local baselines, and debug whether each task is well-posed.</td>
+      <td>40/40 direct scores from Minimal and Neural MLP heads.</td>
+      <td>Task construction, file inspection, local reproducibility, and controlled single-episode baselines.</td>
+      <td>Multi-episode generalization.</td>
     </tr>
     <tr>
       <td><strong>128 selected episodes</strong></td>
       <td>Selected held-out 96/16/16 split: 34,269 exported windows with public-safe processed features linked to official gated episode paths.</td>
-      <td>Metadata simple/NN, raw-feature simple/NN, Qwen3-Omni, Cosmos3-Super, and Cosmos3-Nano: 140/140 scored 128-line records.</td>
-      <td>Compare same-split baselines and model branches; use proxy flags where the public export lacks a direct raw target.</td>
+      <td>140/140 selected-128 scores: 134 direct + 6 compact-proxy.</td>
+      <td>Same-split comparison, model-branch diagnostics, and scale-up planning.</td>
+      <td>Reading proxy cells as direct raw-target measurements.</td>
     </tr>
   </tbody>
 </table>
@@ -281,6 +291,8 @@ LANGUAGE_GUIDES = {
 | 1 sample episode | 5,821 帧；1,161 个 20-frame 对齐窗口；8,546 维特征。 | Minimal + Neural MLP；20 个任务全覆盖；40/40 scored records；全部为 direct scores。 | 检查原始 sample 文件、任务定义、可复现基线和每个任务是否成立。 |
 | 128 selected episodes | 96/16/16 split；34,269 个导出窗口；public-safe 特征链接到官方 gated episode path。 | Metadata simple/NN、raw-feature simple/NN、Qwen3-Omni、Cosmos3-Super、Cosmos3-Nano；140/140 scored records；134 direct + 6 compact proxy。 | 比较同一 split 上的基线和模型分支；proxy target 会显式标注。 |
 
+公式：2 个单 episode 方法 x 20 个任务 = 40；7 个 128-episode 方法 x 20 个任务 = 140；公开矩阵总计 180/180 scored records。
+
 入口：[`TWO_EVIDENCE_LINES.md`](TWO_EVIDENCE_LINES.md)、[`two_evidence_lines.json`](docs/data/two_evidence_lines.json)、[`task_method_20_result_matrix.json`](docs/data/task_method_20_result_matrix.json)、[`two_evidence_line_result_summary.json`](docs/data/two_evidence_line_result_summary.json)。
 
 ## 快速入口
@@ -325,6 +337,8 @@ Este repositorio convierte el episodio público de muestra de Xperience-10M en u
 | 1 episodio de muestra | 5,821 frames; 1,161 ventanas alineadas de 20 frames; 8,546 dimensiones. | Minimal + Neural MLP en 20 tareas; 40/40 registros con score; todos son direct scores. | Inspeccionar archivos de muestra, definiciones de tarea, baselines reproducibles y validez de tareas. |
 | 128 episodios seleccionados | Split 96/16/16; 34,269 ventanas exportadas; features public-safe ligadas a episode paths oficiales gated. | Metadata simple/NN, raw-feature simple/NN, Qwen3-Omni, Cosmos3-Super y Cosmos3-Nano; 140/140 registros con score; 134 direct + 6 compact proxy. | Comparar baselines y ramas de modelo en el mismo split; los proxy targets permanecen visibles. |
 
+Fórmula: 2 métodos de un episodio x 20 tareas = 40; 7 métodos de 128 episodios x 20 tareas = 140; matriz pública total = 180/180 registros con score.
+
 Entradas: [`TWO_EVIDENCE_LINES.md`](TWO_EVIDENCE_LINES.md), [`two_evidence_lines.json`](docs/data/two_evidence_lines.json), [`task_method_20_result_matrix.json`](docs/data/task_method_20_result_matrix.json), [`two_evidence_line_result_summary.json`](docs/data/two_evidence_line_result_summary.json).
 
 ## Ruta Rápida
@@ -369,6 +383,8 @@ Ce dépôt transforme l'épisode public d'exemple Xperience-10M en laboratoire d
 | 1 épisode d'exemple | 5,821 frames; 1,161 fenêtres alignées de 20 frames; 8,546 dimensions. | Minimal + Neural MLP sur 20 tâches; 40/40 enregistrements scorés; tous sont des direct scores. | Inspecter les fichiers sample, les définitions de tâches, les baselines reproductibles et la validité des tâches. |
 | 128 épisodes sélectionnés | Split 96/16/16; 34,269 fenêtres exportées; features public-safe liées aux chemins gated officiels. | Metadata simple/NN, raw-feature simple/NN, Qwen3-Omni, Cosmos3-Super et Cosmos3-Nano; 140/140 enregistrements scorés; 134 direct + 6 compact proxy. | Comparer les baselines et branches de modèles sur le même split; les proxy targets restent visibles. |
 
+Formule : 2 méthodes sur 1 épisode x 20 tâches = 40; 7 méthodes sur 128 épisodes x 20 tâches = 140; matrice publique totale = 180/180 enregistrements scorés.
+
 Entrées : [`TWO_EVIDENCE_LINES.md`](TWO_EVIDENCE_LINES.md), [`two_evidence_lines.json`](docs/data/two_evidence_lines.json), [`task_method_20_result_matrix.json`](docs/data/task_method_20_result_matrix.json), [`two_evidence_line_result_summary.json`](docs/data/two_evidence_line_result_summary.json).
 
 ## Parcours Rapide
@@ -413,6 +429,8 @@ Dieses Repository macht aus dem öffentlichen Xperience-10M-Sample eine prüfbar
 | 1 Sample-Episode | 5,821 Frames; 1,161 ausgerichtete 20-Frame-Fenster; 8,546 Dimensionen. | Minimal + Neural MLP auf 20 Aufgaben; 40/40 gescorte Einträge; alle sind direct scores. | Sample-Dateien, Aufgaben, reproduzierbare Baselines und Aufgabenqualität prüfen. |
 | 128 ausgewählte Episoden | 96/16/16 Split; 34,269 exportierte Fenster; public-safe Features mit offiziellen gated Episode-Pfaden. | Metadata simple/NN, raw-feature simple/NN, Qwen3-Omni, Cosmos3-Super und Cosmos3-Nano; 140/140 gescorte Einträge; 134 direct + 6 compact proxy. | Baselines und Modellzweige auf demselben Split vergleichen; Proxy-Targets bleiben sichtbar. |
 
+Formel: 2 Single-Episode-Methoden x 20 Aufgaben = 40; 7 128-Episode-Methoden x 20 Aufgaben = 140; öffentliche Gesamtmatrix = 180/180 gescorte Einträge.
+
 Einstieg: [`TWO_EVIDENCE_LINES.md`](TWO_EVIDENCE_LINES.md), [`two_evidence_lines.json`](docs/data/two_evidence_lines.json), [`task_method_20_result_matrix.json`](docs/data/task_method_20_result_matrix.json), [`two_evidence_line_result_summary.json`](docs/data/two_evidence_line_result_summary.json).
 
 ## Schneller Einstieg
@@ -457,6 +475,8 @@ Dieses Projekt veröffentlicht nur abgeleitete Artefakte, Metriken, Figuren, Kar
 | 1 sample episode | 5,821 frames、1,161 aligned 20-frame windows、8,546 dimensions。 | Minimal + Neural MLP が 20 tasks を覆盖; 40/40 scored records; すべて direct scores。 | Raw sample files、task definitions、reproducible baselines、task validity を確認。 |
 | 128 selected episodes | 96/16/16 split、34,269 exported windows、public-safe features が official gated episode paths に対応。 | Metadata simple/NN、raw-feature simple/NN、Qwen3-Omni、Cosmos3-Super、Cosmos3-Nano; 140/140 scored records; 134 direct + 6 compact proxy。 | 同一 split の baselines と model branches を比較; proxy targets は明示。 |
 
+式: 1-episode methods 2 個 x 20 tasks = 40、128-episode methods 7 個 x 20 tasks = 140、公開 matrix 合計は 180/180 scored records。
+
 入口: [`TWO_EVIDENCE_LINES.md`](TWO_EVIDENCE_LINES.md)、[`two_evidence_lines.json`](docs/data/two_evidence_lines.json)、[`task_method_20_result_matrix.json`](docs/data/task_method_20_result_matrix.json)、[`two_evidence_line_result_summary.json`](docs/data/two_evidence_line_result_summary.json)。
 
 ## クイックルート
@@ -501,6 +521,8 @@ Dieses Projekt veröffentlicht nur abgeleitete Artefakte, Metriken, Figuren, Kar
 | 1 sample episode | 5,821 frames, 1,161 aligned 20-frame windows, 8,546 dimensions. | Minimal + Neural MLP가 20 tasks 전체를 평가; 40/40 scored records; 모두 direct scores. | Raw sample files, task definitions, reproducible baselines, task validity 확인. |
 | 128 selected episodes | 96/16/16 split, 34,269 exported windows, public-safe features가 official gated episode paths에 연결됨. | Metadata simple/NN, raw-feature simple/NN, Qwen3-Omni, Cosmos3-Super, Cosmos3-Nano; 140/140 scored records; 134 direct + 6 compact proxy. | 같은 split에서 baselines와 model branches 비교; proxy targets는 명시 유지. |
 
+공식: single-episode 방법 2개 x 20 tasks = 40; 128-episode 방법 7개 x 20 tasks = 140; 전체 공개 matrix = 180/180 scored records.
+
 입구: [`TWO_EVIDENCE_LINES.md`](TWO_EVIDENCE_LINES.md), [`two_evidence_lines.json`](docs/data/two_evidence_lines.json), [`task_method_20_result_matrix.json`](docs/data/task_method_20_result_matrix.json), [`two_evidence_line_result_summary.json`](docs/data/two_evidence_line_result_summary.json).
 
 ## 빠른 경로
@@ -545,6 +567,8 @@ Este repositório transforma o episódio público de amostra do Xperience-10M em
 | 1 episódio de amostra | 5,821 frames; 1,161 janelas alinhadas de 20 frames; 8,546 dimensões. | Minimal + Neural MLP em 20 tarefas; 40/40 registros com score; todos são direct scores. | Inspecionar arquivos da amostra, definições de tarefas, baselines reproduzíveis e validade das tarefas. |
 | 128 episódios selecionados | Split 96/16/16; 34,269 janelas exportadas; features public-safe ligadas aos caminhos oficiais gated. | Metadata simple/NN, raw-feature simple/NN, Qwen3-Omni, Cosmos3-Super e Cosmos3-Nano; 140/140 registros com score; 134 direct + 6 compact proxy. | Comparar baselines e ramos de modelo no mesmo split; proxy targets permanecem visíveis. |
 
+Fórmula: 2 métodos de um episódio x 20 tarefas = 40; 7 métodos de 128 episódios x 20 tarefas = 140; matriz pública total = 180/180 registros com score.
+
 Entradas: [`TWO_EVIDENCE_LINES.md`](TWO_EVIDENCE_LINES.md), [`two_evidence_lines.json`](docs/data/two_evidence_lines.json), [`task_method_20_result_matrix.json`](docs/data/task_method_20_result_matrix.json), [`two_evidence_line_result_summary.json`](docs/data/two_evidence_line_result_summary.json).
 
 ## Rota Rápida

scripts/build_public_surface_qa.py

@@ -204,12 +204,15 @@ def build_report() -> dict:
         "data/research_roadmap.json",
         "data/task_suite_enhancement_128.json",
         "data/task_suite_20.json",
+        "data/two_evidence_lines.json",
+        "data/two_evidence_line_result_summary.json",
         "data/unified_task_model_radar.json",
         "data/single_episode_task_model_radar.json",
         "data/episode128_task_model_radar.json",
         "data/task_method_20_result_matrix.json",
         "data/task_method_20_gap_audit.json",
         "data/language_versions.json",
+        "assets/charts/two_evidence_line_map.svg",
         "assets/charts/unified_task_model_radar.svg",
         "assets/charts/single_episode_task_model_radar.svg",
         "assets/charts/episode128_task_model_radar.svg",

scripts/build_unified_task_model_radar.py

@@ -1051,7 +1051,7 @@ def build_payload() -> dict[str, Any]:
                 "id": "raw128_simple",
                 "title": "128ep Raw Simple",
                 "status": "a100_raw20_complete_with_documented_proxies",
-                "coverage": f"20 records / {next(item for item in series_records if item['id'] == 'raw128_simple')['scored_task_count']} scored axes; 18 direct + 2 proxy",
+                "coverage": f"20 records / {next(item for item in series_records if item['id'] == 'raw128_simple')['scored_task_count']} scored records; 18 direct + 2 proxy",
                 "headline": "34,269 windows; centroid/ridge heads over 4430-dim sensor blocks",
                 "source": str((RAW128_BASELINE_DIR / "run_summary_all.json").relative_to(ROOT)),
             },
@@ -1059,7 +1059,7 @@ def build_payload() -> dict[str, Any]:
                 "id": "raw128_neural_mlp",
                 "title": "128ep Raw NN",
                 "status": "a100_raw20_complete_with_documented_proxies",
-                "coverage": f"20 records / {next(item for item in series_records if item['id'] == 'raw128_neural_mlp')['scored_task_count']} scored axes; 18 direct + 2 proxy",
+                "coverage": f"20 records / {next(item for item in series_records if item['id'] == 'raw128_neural_mlp')['scored_task_count']} scored records; 18 direct + 2 proxy",
                 "headline": "MLP heads over staged features; tasks 15/19 use compact proxies",
                 "source": str((RAW128_BASELINE_DIR / "run_summary_all.json").relative_to(ROOT)),
             },
@@ -1155,9 +1155,9 @@ def render_svg(
         chip_specs = [
             ("20 task axes", "#ccffa0"),
             (f"{payload['method_task_record_count']} method-task records", "#67e8d1"),
-            (f"{payload['scored_method_task_count']} scored axes", "#22d3ee"),
+            (f"{payload['scored_method_task_count']} scored records", "#22d3ee"),
             ("40/40 raw128 pass", "#f59e0b"),
-            ("2 compact proxy axes", "#f472b6"),
+            ("2 compact proxy records", "#f472b6"),
         ]
     chip_x = 70
     for label, color in chip_specs:
@@ -1214,7 +1214,7 @@ def render_svg(
     legend_x, legend_y = 1315, 178
     parts.append(f'<rect x="{legend_x - 30}" y="{legend_y - 38}" width="1000" height="560" rx="14" fill="#020502" fill-opacity="0.58" stroke="#ccffa0" stroke-opacity="0.20"/>')
     parts.append(svg_text(legend_x, legend_y, "Methods compared", size=25, weight=800))
-    parts.append(svg_text(legend_x, legend_y + 30, "Each method has 20 records; scored axes, proxy flags, and sources stay in the JSON matrix.", size=13, fill="#a5afa2", weight=560))
+    parts.append(svg_text(legend_x, legend_y + 30, "Each method has 20 records; scores, proxy flags, and sources stay in the JSON matrix.", size=13, fill="#a5afa2", weight=560))
 
     cursor = legend_y + 74
     for record in series_records:
@@ -1314,7 +1314,7 @@ def main() -> int:
             chip_specs=[
                 ("20 task axes", "#ccffa0"),
                 ("40 method-task records", "#67e8d1"),
-                ("40 scored axes", "#22d3ee"),
+                ("40 scored records", "#22d3ee"),
                 ("2 filled baseline polygons", "#f472b6"),
             ],
             reading_rules=(
@@ -1336,7 +1336,7 @@ def main() -> int:
             chip_specs=[
                 ("20 task axes", "#ccffa0"),
                 ("140 method-task records", "#67e8d1"),
-                (f"{episode128_payload['scored_method_task_count']} scored axes", "#22d3ee"),
+                (f"{episode128_payload['scored_method_task_count']} scored records", "#22d3ee"),
                 ("40/40 raw128 pass", "#f59e0b"),
                 ("0 scoreless", "#f472b6"),
             ],

scripts/sync_hf_publish_mirrors.py

@@ -51,14 +51,21 @@ The public-sample task surface is now one unified 20-task suite in
 original sample tasks; Tasks 13-20 reuse the same 20-frame windows, 5-frame
 stride, feature manifest, chronological split, and minimal/neural head pattern.
 The historical `tier2_task_suite` path is retained only for stable artifact
-links to tasks 13-20. The unified radar chart is published as
+links to tasks 13-20. Results are organized as two evidence lines:
+one public sample episode for task construction and reproducibility, and
+128 selected episodes for same-split baselines plus Qwen3/Cosmos comparison.
+The line map is published as `docs/assets/charts/two_evidence_line_map.svg`
+with machine-readable summaries in `docs/data/two_evidence_lines.json` and
+`docs/data/two_evidence_line_result_summary.json`.
+
+The unified radar chart is published as
 `docs/assets/charts/unified_task_model_radar.svg` with values in
 `docs/data/unified_task_model_radar.json`; the 9-method by 20-task completion
 matrix is complete at `180/180` scored method-task records and is published in
 `docs/data/task_method_20_result_matrix.json`, with the explicit audit in
 `docs/data/task_method_20_gap_audit.json` and source-value audit in
-`docs/data/task_method_20_source_audit.json`. Split radars for
-the one-episode baselines and selected 128-episode methods are published as
+`docs/data/task_method_20_source_audit.json`. Split radars for the one-episode
+baselines and selected 128-episode methods are published as
 `docs/assets/charts/single_episode_task_model_radar.svg` and
 `docs/assets/charts/episode128_task_model_radar.svg`.
 """
@@ -214,7 +221,14 @@ def ensure_tier2_card_links(hf_root: Path, *, dry_run: bool) -> list[str]:
         if "docs/data/unified_task_model_radar.json" not in text:
             text = text.replace(
                 "links to tasks 13-20.\n",
-                "links to tasks 13-20. The unified radar chart is published as\n"
+                "links to tasks 13-20. Results are organized as two evidence lines:\n"
+                "one public sample episode for task construction and reproducibility,\n"
+                "and 128 selected episodes for same-split baselines plus Qwen3/Cosmos\n"
+                "comparison. The line map is published as\n"
+                "`docs/assets/charts/two_evidence_line_map.svg` with summaries in\n"
+                "`docs/data/two_evidence_lines.json` and\n"
+                "`docs/data/two_evidence_line_result_summary.json`.\n\n"
+                "The unified radar chart is published as\n"
                 "`docs/assets/charts/unified_task_model_radar.svg` with values in\n"
                 "`docs/data/unified_task_model_radar.json`; the 9-method by\n"
                 "20-task completion matrix is complete at `180/180` scored\n"
@@ -237,6 +251,18 @@ def ensure_tier2_card_links(hf_root: Path, *, dry_run: bool) -> list[str]:
                 "with the explicit score/proxy audit in `docs/data/task_method_20_gap_audit.json`\n"
                 "and source-value audit in `docs/data/task_method_20_source_audit.json`.",
             )
+        if (
+            "docs/data/task_method_20_result_matrix.json" in text
+            and "docs/assets/charts/two_evidence_line_map.svg" not in text
+        ):
+            text = text.replace(
+                "`docs/data/task_method_20_result_matrix.json`,",
+                "`docs/data/task_method_20_result_matrix.json`, with two-line summaries in\n"
+                "`docs/assets/charts/two_evidence_line_map.svg`,\n"
+                "`docs/data/two_evidence_lines.json`, and\n"
+                "`docs/data/two_evidence_line_result_summary.json`,",
+                1,
+            )
         if "completion matrix is in `docs/data/task_method_20_result_matrix.json`" in text:
             text = text.replace(
                 "completion matrix is in `docs/data/task_method_20_result_matrix.json`, "

scripts/validate_publication_package.py

@@ -345,6 +345,7 @@ def required_assets(root: Path) -> dict[str, bool]:
         "docs/assets/brand/xperience10m-logo-mark-512.png",
         "docs/assets/brand/xperience10m-logo-social-card.png",
         "docs/assets/task_suite_infographic.png",
+        "docs/assets/charts/two_evidence_line_map.svg",
         "docs/assets/charts/unified_task_model_radar.svg",
         "docs/assets/charts/single_episode_task_model_radar.svg",
         "docs/assets/charts/episode128_task_model_radar.svg",