This portable snapshot supports developmental assurance claims. It is not a clinical validation package.
formal_models contains bounded models and controls; agent_specification contains frozen prompts, advisory schemas and the bounded orchestrator; executable_governance contains Rego, SHACL/OWL, mappings and conformance tests; evaluation_protocol contains rubrics and labels; data_availability contains complete synthetic data and MAUDE identifiers/digests only; results contains stored auditable summaries, including the ten-model RQ2/RQ4 matched campaign (raw per-arm traces and paired_results.json), the two-series scaling sweep and retained single-series qwen2.5 sweep, the field-provenance/redundancy audit, the qwen2.5 natural-output raw inputs in results/qwen25_natural_output_raw/, and the SHACL-informed in-loop revision campaigns (qwen2.5:3b frozen baseline plus the qwen3.5:9b/gemma3:12b cross-series extension). Mock fallback runs are not empirical evidence.
From biodevops_rag, use Python 3.10+, install requirements.txt, build the vector index with scripts/ingest_corpus.py, then run python -m unittest tests/test_bounded_agent.py tests/test_transition_matrix.py tests/test_planner_contract.py tests/test_inloop_revision.py tests/test_governance_conformance.py. Use local Ollama for real inference and record model digest, seed, and source in every trace. The matched development and held-out bounded-agent campaigns (agent_specification/matched_agentic_campaign/), the RQ2 ten-model campaign, and the in-loop revision campaigns under results/ are frozen, hash-authorized, one-shot runs; do not rerun them to "reproduce" a table --- rerun the table-regeneration scripts against the stored raw outputs instead (rq2_multimodel_cluster_ci.py, build_scaling_summary_table.py, redundancy_audit.py, inloop_revision_cross_series_20260806/aggregate_inloop_cross_series.py, inloop_revision_cross_series_20260806/verify_rq2_table.py). scripts/run_bounded_arm_inloop_revision.py is the runner that produced the in-loop revision campaigns and can be rerun on new scenarios or models under the same frozen protocol.
Synthetic scenarios are included and marked synthetic. FDA MAUDE narratives are not redistributed: maude_record_index.json provides FDA IDs, URLs and SHA-256 provenance. No license is asserted for third-party standards, ontologies, model weights, or FDA source text.