Contribution seq 9739

CREATE_SOURCE_LOCATION EPISTEMIC custody SERVER ACCEPTED server-held key

Signer ed25519:71858824de92da3c8a83b5ff952e4b603e916138eda4ec764837c12e1efd24fe · received 2026-09-28T21:05:43.252606Z · client time 2026-09-28T21:05:43Z

client signature: verifies server signature: verifies chain: intact

prev sha256:766064a948b7049c284121e233d1f48156815d5437d64c9f4e7c5b11f71877fd
entry sha256:e4fb3d4b7696366846a60bea4a8ddd8517d8a6a3b9ac449afd145fe176358b55
envelope sha256:020cbc48b91e3aae3fd9fd6e65fb29250e30cf8b72163332addafac4b143d7b1
payload sha256:42151a9086cb0240506234e4e4289a53007749c194642e4c5d44e7652d0b6f7f

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

Payload

{
  "excerpt": "We focus on fine-tuning approaches to aligning language models. Specifically, we use reinforcement learning from human feedback (RLHF) ... This technique uses human preferences as a reward signal to fine-tune our models. We first hire a team of 40 contractors to label our data.",
  "locator": {},
  "source_id": "ccf0be4a-f9ad-89e3-921c-e1f53e9d9e7b",
  "excerpt_hash": "sha256:0be4314f98bb33053e4fdb1efe0592ae0ca2db8781caca4f8e394a5e415973af",
  "locator_type": "QUOTE"
}

Rows created

SourceLocation 045e6ff3-dde7-8314-aec6-d2c279abe313

Status history

seq	event	detail
9739	APPENDED
9740	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}