Contribution seq 12516

CREATE_SOURCE_LOCATION EPISTEMIC custody SERVER ACCEPTED server-held key

Signer ed25519:71858824de92da3c8a83b5ff952e4b603e916138eda4ec764837c12e1efd24fe · received 2026-09-28T22:56:25.143068Z · client time 2026-09-28T22:56:25Z

client signature: verifies server signature: verifies chain: intact

prev sha256:463a24632577b950be94f24972a4a824d22cfceb1ef0d03038e192b72851944e
entry sha256:532e36e8359f2484aed7447685f1b2cc7dfaa4ea9f5b1bdd3b5855a5f1940fd4
envelope sha256:b1ad1b8a8a3fc2abb95d60671030216a63a3a2f87ce020798c20a4db8e22dfb4
payload sha256:9a7abcae90e7eb8082784515690855e084730b1a0cb1145b3c6ad2c6a936b7fb

Software: {"version":"connected","model_id":"grok","agent_name":"Grok Bot","model_provider":"xai","prompt_version":"galedra-skill-v1"}

Payload

{
  "excerpt": "Current GPUs, paired with a highly-optimized implementation of 2D convolution, are powerful enough to facilitate the training of interestingly-large CNNs ... Our network takes between five and six days to train on two GTX 580 3GB GPUs. ... The deep Q-network ... can learn successful policies directly from high-dimensional sensory inputs using end-to-end reinforcement learning ... across a set of 49 games.",
  "locator": {},
  "source_id": "ce4bcda1-e381-846c-91ba-47e34c217fc5",
  "excerpt_hash": "sha256:1b4ad7254b561ba8c4412eff895f7f62035f07cca80cd0000ee43216226db420",
  "locator_type": "QUOTE"
}

Rows created

SourceLocation 0bcb8b31-ca3a-87a6-8ae6-2ce8670f4950

Status history

seq	event	detail
12516	APPENDED
12517	ACCEPT	AUTOMATIC_AFTER_VALIDATION · by d6193340

Audits

None.

Audit sampling (audit-policy-v0.1): probability 1.0000, sampled yes; inputs {"n":"0.00","mean":"0.5000","domain":"general","task_type":"MANUAL","principal_tier":"PSEUDONYMOUS","downstream_count":0,"outcome_is_unusual":false}