feat: ML-DSA-65, did:key, named hash algorithm, model provenance, log tiles and witnesses

- hashing.algorithm names the hash function in every document; a consumer refuses one it does not implement (doc.hash.algorithm) - ML-DSA-65 (FIPS 204) is an implemented signature scheme: pure-Python reference in tools/oracle/mldsa.py checked against NIST ACVP vectors, a receipt signed by the new roster key dana, and signature vectors for key generation and a deterministic signature - roster keys may carry a did:key, which the validator checks against the public key (doc.roster.did), and a witness purpose for parties that cosign log checkpoints - model provenance: a correction's author and an annotation's generator name the model with provider, version and the hashes of its weights, prompt and parameters, and where it ran - the transparency log gains the tlog-tiles static layout (fixtures/records/log/), a project settings.log with origin, witnesses and threshold, and an acceptance rule; the fixture checkpoint is cosigned by a witness - store.sql: roster_keys accepts cose and ml-dsa-65 and gains a did column - spec chapters 01, 08, 11, 18, 20 and 23, the rationale, glossary, fixture, vector and tool guides updated; stress harness covers ML-DSA Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
2026-10-15 04:39:12 -04:00
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+{"at":"2026-10-13T09:00:00Z","by":"dana","doc":"hale2026harmonic-damb","evidence":[{"by":"dana","kind":"person"}],"format":"scienting-receipt/1","id":"vbttn1qvxkx4s","level":"F2","nodes":[["kea5026","b836d5872ca37471fa996be04c538254a8b1e37ca12e8f1b4a40837b503afa33"],["rr20tev","76e06b4811a688357ac4b912172283463cfaf1b7a1f0795d274fc733a2309ba7"]],"rev":12,"root":"1529e715397aae9f44f1f17fb95c5ef8fbef008d901c2624413b899e8552b174","scope":"targeted:ml-dsa","signature":{"key":"dana","scheme":"ml-dsa-65","value":"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"}}
				`@@ -0,0 +1 @@`
				{"at":"2026-10-13T09:00:00Z","by":"dana","doc":"hale2026harmonic-damb","evidence":[{"by":"dana","kind":"person"}],"format":"scienting-receipt/1","id":"vbttn1qvxkx4s","level":"F2","nodes":[["kea5026","b836d5872ca37471fa996be04c538254a8b1e37ca12e8f1b4a40837b503afa33"],["rr20tev","76e06b4811a688357ac4b912172283463cfaf1b7a1f0795d274fc733a2309ba7"]],"rev":12,"root":"1529e715397aae9f44f1f17fb95c5ef8fbef008d901c2624413b899e8552b174","scope":"targeted:ml-dsa","signature":{"key":"dana","scheme":"ml-dsa-65","value":"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"}}