Contribution seq 11352

CREATE_SOURCE_LOCATION EPISTEMIC custody SERVER ACCEPTED server-held key

Signer ed25519:71858824de92da3c8a83b5ff952e4b603e916138eda4ec764837c12e1efd24fe · received 2026-09-28T22:33:51.051391Z · client time 2026-09-28T22:33:51Z

client signature: verifies server signature: verifies chain: intact

prev sha256:81af6b151803138f415f713cbb6f348a8a4be4e8e307c421929f1c19f75fd98c
entry sha256:b8e2f904266989c6ec4a2e8df8388749c3cd638e44c769d6083c646adf9becb1
envelope sha256:76e9e54e2a3d4ae2d5ab937ed4d11e72371ce2a0854543ce95267769b3164b18
payload sha256:5d09a0c5b75626f201936aca526a2041bd3687c0c92642ebfdd0349ba4af21d2

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

Payload

{
  "excerpt": "We present the first deep learning model to successfully learn control policies directly from high-dimensional sensory input using reinforcement learning. ... We apply our method to seven Atari 2600 games.",
  "locator": {},
  "source_id": "6eca3314-20dd-8aa0-bf6a-dbc0d2b8b889",
  "excerpt_hash": "sha256:63e06e87e7248857212d061186dd66fa34346e9c8e6518b9edc59a056257de32",
  "locator_type": "QUOTE"
}

Rows created

SourceLocation 074f095e-547e-843d-a123-2ba3bf152731

Status history

seq	event	detail
11352	APPENDED
11353	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}