{
  "title": "Single-Episode 20-Task Radar",
  "status": "pass",
  "generated_at_utc": "2026-06-22T13:13:58+00:00",
  "description": "Minimal and Neural MLP baselines on the one public sample episode, both scored on all 20 task contracts.",
  "task_count": 20,
  "method_count": 2,
  "method_task_record_count": 40,
  "scored_method_task_count": 40,
  "normalization_policy": {
    "higher_is_better": "bounded metrics are plotted directly on 0-1 axes after clipping to [0, 1]",
    "lower_is_better": "lower-error metrics are converted to best_observed_value / raw_value within the same task",
    "raw_values": "raw metric values, metric keys, and sources are retained in this JSON; the SVG is an overview, not a replacement for the metric table",
    "radar_visual_radius": "SVG radar panels use sqrt(normalized_score) for radius so polygon area remains closer to the score and low-valued but real differences stay visible; the JSON and matrix retain exact linear normalized_score values",
    "result_record_policy": "every method has 20 task records; the current public release has 180/180 scored rows with proxy flags and reasons retained where compact substitute targets are used",
    "foundation_model_overlay": "Qwen3-Omni and Cosmos3 are grouped in the foundation-model radar panel. All current public model rows have 20 scored task records, with source paths retained for every metric.",
    "metadata_128_overlay": "128-episode aligned baselines are grouped in the metadata/text radar panel. Numeric scores come from JSONL metadata/text tasks plus staged sensor-block targets when the processed target exists.",
    "raw_128_overlay": "128-episode raw-feature baselines are grouped in the raw-feature radar panel. Eighteen axes use direct task targets; interaction text and camera-view sync are completed with documented compact proxies because raw interaction strings and paired video-view embeddings are absent from the 128 export."
  },
  "chart_design": {
    "mode": "grouped_small_multiples",
    "method_count": 2,
    "reason": "This split view has 2 methods and 40 method-task records; grouped radar panels keep related methods readable while retaining the unified source matrix.",
    "groups": [
      {
        "id": "single_episode",
        "title": "Single-episode sample",
        "series_ids": [
          "minimal",
          "neural_mlp"
        ]
      }
    ],
    "visual_radius_transform": "sqrt(normalized_score)",
    "exact_value_source": "docs/data/task_method_20_result_matrix.json"
  },
  "source_unified_radar": "docs/data/unified_task_model_radar.json",
  "source_result_matrix": "docs/data/task_method_20_result_matrix.json",
  "series": [
    {
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      "label": "Minimal",
      "short_label": "Min",
      "color": "#ccffa0",
      "kind": "full_20_task_baseline",
      "scope": "1 public sample episode",
      "stroke_dasharray": null,
      "method_detail": "Single-episode simple heads over the public sample split.",
      "plotted_as": "grouped small-multiple radar panel with direct legend and coverage badges",
      "result_record_count": 20,
      "scored_task_count": 20,
      "covered_task_count": 20,
      "proxy_scored_task_count": 0,
      "scoreless_task_count": 0,
      "unsupported_task_count": 0,
      "not_evaluated_task_count": 0,
      "status_counts": {
        "scored": 20
      },
      "coverage_fraction": 1.0,
      "result_record_fraction": 1.0
    },
    {
      "id": "neural_mlp",
      "label": "Neural MLP",
      "short_label": "NN",
      "color": "#67e8d1",
      "kind": "full_20_task_baseline",
      "scope": "1 public sample episode",
      "stroke_dasharray": null,
      "method_detail": "Single-episode compact PyTorch MLP heads on the same 20 task contracts.",
      "plotted_as": "grouped small-multiple radar panel with direct legend and coverage badges",
      "result_record_count": 20,
      "scored_task_count": 20,
      "covered_task_count": 20,
      "proxy_scored_task_count": 0,
      "scoreless_task_count": 0,
      "unsupported_task_count": 0,
      "not_evaluated_task_count": 0,
      "status_counts": {
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      },
      "coverage_fraction": 1.0,
      "result_record_fraction": 1.0
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  "tasks": [
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      "label": "Action Recognition",
      "axis_label": "01 Action Recognition",
      "short_label": "Action",
      "provenance_source": "walkthrough_backed_task_contract",
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      "metric_name": "macro-F1",
      "metric_direction": "higher",
      "raw128_proxy_axis": false,
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    },
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      "task_number": 2,
      "task_id": "timeline_subtask",
      "label": "Procedure Step Recognition",
      "axis_label": "02 Procedure Step Recognition",
      "short_label": "Step",
      "provenance_source": "walkthrough_backed_task_contract",
      "metric_key": "macro_f1",
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      "label": "Action Boundary Detection",
      "axis_label": "03 Action Boundary Detection",
      "short_label": "Boundary",
      "provenance_source": "walkthrough_backed_task_contract",
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    },
    {
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      "label": "Next-Action Prediction",
      "axis_label": "04 Next-Action Prediction",
      "short_label": "Next act",
      "provenance_source": "walkthrough_backed_task_contract",
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    },
    {
      "task_number": 5,
      "task_id": "hand_trajectory_forecast",
      "label": "Hand Trajectory Forecasting",
      "axis_label": "05 Hand Trajectory Forecasting",
      "short_label": "Hand traj",
      "provenance_source": "walkthrough_backed_task_contract",
      "metric_key": "mpjpe",
      "metric_name": "MPJPE",
      "metric_direction": "lower",
      "raw128_proxy_axis": false,
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    {
      "task_number": 6,
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      "label": "Contact State Prediction",
      "axis_label": "06 Contact State Prediction",
      "short_label": "Contact",
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      "task_number": 7,
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      "label": "Object Relevance Prediction",
      "axis_label": "07 Object Relevance Prediction",
      "short_label": "Objects",
      "provenance_source": "walkthrough_backed_task_contract",
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      "metric_name": "micro-F1",
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      "task_number": 8,
      "task_id": "caption_grounding",
      "label": "Language Grounding",
      "axis_label": "08 Language Grounding",
      "short_label": "Language",
      "provenance_source": "walkthrough_backed_task_contract",
      "metric_key": "mrr",
      "metric_name": "MRR",
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      "label": "Cross-Modal Retrieval",
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      "short_label": "X-modal",
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      "axis_label": "10 Cross-Modal Reconstruction",
      "short_label": "Recon",
      "provenance_source": "walkthrough_backed_task_contract",
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      "task_number": 11,
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      "label": "Temporal Order Verification",
      "axis_label": "11 Temporal Order Verification",
      "short_label": "Order",
      "provenance_source": "walkthrough_backed_task_contract",
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      "task_number": 12,
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      "label": "Multimodal Synchronization Detection",
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      "short_label": "Sync",
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      "axis_label": "13 Long-Horizon Next-Action Forecasting",
      "short_label": "Long act",
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      "label": "Long-Horizon Next-Subtask Forecasting",
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      "task_number": 15,
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      "label": "Interaction Text Prediction",
      "axis_label": "15 Interaction Text Prediction",
      "short_label": "Interact txt",
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      "task_number": 16,
      "task_id": "action_object_relation",
      "label": "Action-Object Relation Prediction",
      "axis_label": "16 Action-Object Relation Prediction",
      "short_label": "Act+obj",
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