Training demo
Turn reviewed work into a signed training corpus.
Follow the data path from accepted reviewer decisions through policy filtering, failure feedback, manifest review, and governed export.
Corpus pipeline
clinical-note-v18
1
Reviewed work
Workforce + Annotation
42k accepted labels
2
Policy filter
consent, PHI, retention
1,128 exclusions
3
De-dupe
semantic near-match
3.8% removed
4
Slice
8 domains
clinical-note-v18
5
Signed export
checksums attached
jsonl + parquet
Failure feedback loop
Evaluation Studio
source
Hallucinated dosage
rewrite pair
219
Regression Bank
source
Old failure resurfaced
hard negative
37
AuraQC
source
Reviewer conflict
adjudicated preference
82
Manifest drilldown
run
train_2026_04_clinical_v18
reviewer coverage
94% · 19 certs
excluded records
1,128 · consent/PHI
checksums
dataset sha256:a91f · weights sha256:c03d
formats
jsonl · parquet · evidence packet
Dataset governance
Every slice carries source, exclusion, and reviewer coverage state.
Policy-bound export
Exports are blocked until exclusions, retention, and consent pass.
Model proof attached
Weights and evidence leave together so the tuned model stays reviewable.