[M0-R TRACKER] Canonical Scientific Baseline

[andreazedda]

Milestone objective

Establish one canonical, reproducible, and epistemically coherent scientific baseline before producing new research results.

Work items

• [M0-R][CANONICALIZATION] Publish the validated Twin-lineage candidate and migrate the research database safely #11 Publish the validated Twin-lineage candidate and migrate the research database safely
• [M0-R][GOVERNANCE] Establish canonical intended use and remove prescriptive legacy outputs #12 Establish canonical intended use and remove prescriptive legacy outputs
• [M0-R][REPRODUCIBILITY] Lock dependencies and standardize Python quality tooling #15 Lock dependencies and standardize Python quality tooling
• [M0-R][REPRODUCIBILITY] Implement immutable run manifests, model registry, and typed scientific contracts #19 Implement immutable run manifests, model registry, and typed scientific contracts
• [M0-R][CI] Add mandatory scientific quality gates, PR workflow, and branch protection #13 Add mandatory scientific quality gates, PR workflow, and branch protection
• [M0-R][QA] Establish property, contract, migration, numerical, and security test gates #23 Establish property, contract, migration, numerical, and security test gates
• [M0-R][DOCUMENTATION] Rebuild documentation as a versioned single source of truth #14 Rebuild documentation as a versioned single source of truth

Exit definition

CANONICAL_GIT_STATE = true
TWIN_LINEAGE_AND_INPUT_IDENTITY = valid
INTENDED_USE = E1_research_prototype
PRESCRIPTIVE_RUNTIME_OUTPUTS = zero
DEPENDENCIES_LOCKED = true
MINIMAL_RUN_MANIFEST = mandatory
SCIENTIFIC_CI_AND_SAFETY_GATES = pass
PHI_IN_GIT = zero
DOCUMENTATION_SOURCE_OF_TRUTH = current

Evidence required

• canonical commit and migration identities;
• dataset, computational-input, model, config, and dependency hashes;
• CI and safety-gate evidence;
• typed run-manifest example;
• numerical and schema regression evidence;
• intended-use and claims scan;
• documentation inventory and current README.

Non-goals

This milestone does not complete the real-patient Research Loop, production deployment, external validation, or a new biological model.