2.0 KiB
Runtime model provenance remediation — 2026-08-23
Outcome and claim boundary
The active detection checkpoint can receive a truthful narrow runtime sidecar because its surviving training artifacts now establish an exact byte chain. This remediation binds model bytes, retained checkpoint, base model, dataset contract inputs and the surviving Ultralytics training receipts. It does not retroactively assert a missing historical code commit/container, signed human review, protected-test independence, national validity or a new promotion.
Recovered immutable evidence
| Artifact | SHA-256 |
|---|---|
active model and retained best.pt |
a9088b8491dfae36694b53e9e9406cb4e3511d334a5712fa34f75078a47759c1 |
| base model | a8a79cf5b0bdc19a0245acc322cf77232c335e222bd5f3c00a17d5f29402c196 |
training args.yaml |
2b482e6bbef26f433d4406e1acb5cbbf4ce63a63644b180a2d51b93f8c8f0dcb |
training results.csv |
6f83fdea2c59cfc5f3e4fe9673494e073c4e0054980b3020bad0289d0118b777 |
| training summary | 6d438308c923f50d885dc777d381f469fa215a0557f0f3e9d3facc2f75ce0b8e |
| dataset YAML | 3a2ea97c35a18072a1ab6738cd673c0ecec5344b19461c91d72a15e138d46e8d |
| dataset summary | 49b2a07d2105d08356431757b83eafc1498eaf1fb76965b1efe05b776824942a |
The checkpoint embeds an Ultralytics detection task, class mapping
0: building, framework version 8.4.93, 30 epochs, image size 640, seed 0
and deterministic mode. The dataset summary retains 198 tiles, 180 training
tiles, 18 validation tiles and 58,820 labels.
Guarded migration
scripts/migrate_runtime_model_provenance.py performs the migration. It fails
closed on any mismatched file or recorded checksum, is dry-run by default,
writes the sidecar atomically and reuses only an identical immutable database
snapshot. The production check then validates the sidecar against the
server-owned model registry and snapshot before model loading.
The operational source version is
sprint174-20260713-smallbld-minpx3-img640-ft30. This is a recovered runtime
artifact identity, not an accuracy or release-level claim.