Medtech Model Evidence Export to MLflow

Purpose

Mirror an existing medical-inference result or evidence pack into MLflow after the run and emit the export_result JSON contract. Keep the original evidence pack as the source of truth. Training skills should add MLflow inside their training loops instead.

Instructions

1. Run scripts/export_evidence_pack.py in the default dry-run mode.
2. Inspect params, metrics, artifact_plan, and mlflow.note.content.
3. Choose --mode local or --mode databricks only after checking the target.
4. Keep --artifact-policy metadata unless the target is approved for images.
5. For preview or all in a live mode, also pass --confirm-medical-artifact-upload.
6. Keep --source-ref, --note, config filenames, and artifact filenames free of patient or secret identifiers; always review the dry-run output first.