Individual skill
medtech-model-evidence-export
Exports sanitized metadata, parameters, reproducibility details, quality metrics, and optional review artifacts from Medical AI inference runs or evidence packs to MLflow. Use after inference, including NV-Generate runs; not for live training tracking, model registration, or clinical use.
skills/medtech-model-evidence-export/SKILL.md
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BENCHMARK.mddoc · 7,923 bytesSKILL.mdcore · 5,140 bytesSKILL.mdcore · 5,140 bytesSKILL.mdcore · 5,140 bytesSKILL.mdcore · 5,140 bytesSKILL.mdcore · 5,140 bytesSKILL.mdcore · 5,140 bytesSKILL.mdcore · 5,140 bytesSKILL.mdcore · 5,140 bytesevals/evals.jsonasset · 2,494 bytesfixtures/sample_pack/integrity_check.jsonasset · 62 bytesfixtures/sample_pack/manifest.jsonasset · 229 bytesfixtures/sample_pack/output.jsonasset · 1,555 bytesfixtures/sample_pack/runtime_profile.jsonasset · 108 bytesfixtures/sample_pack/validation_summary.jsonasset · 121 bytesfixtures/sample_result.jsonasset · 1,809 bytesscripts/export_evidence_pack.pyruns · 32,745 bytesskill-card.mddoc · 4,188 bytesskill.oms.sigasset · 7,085 bytesskill_manifest.yamlasset · 3,838 bytestests/test_export_evidence_pack.pyruns · 8,810 bytesvalidators/output_schema.jsonasset · 3,246 bytes
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# 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.