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Sprint projectSep 14, 2026Lincoln, NE

Project Warrant: On Evidentiary Channel Dependency in a Frontier AI Incident Record

Aruneem Bhowmick · Team Project Warrant

Submitted to AI Incident Response Sprint. Sprint projects are early-stage work by participants, not Apart Research publications.

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Report: Project Warrant: On Evidentiary Channel Dependency in a Frontier AI Incident Record

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Project Warrant audits which evidentiary channels the public record of the July 2026 OpenAI/Hugging Face agent-escape incident actually rests on, and finds that 78.4% of claims (47.2% uncorroborated) depend on channels likely to disappear, go unfaithful, or be forged next time. It ships a 125-row coded claim ledger, five reliability-checked metrics, a 14-clause forensic-adequacy standard (MRFM v0.1), and regulator-ready RFI questions to close the gap.

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  1. 1Negligible. No clear problem addressed, or no meaningful novelty.
  2. 2Limited. Addresses a real problem but with a generic or well-trodden approach. Incremental at best.
  3. 3Moderate. Clear problem with a reasonable approach; some novelty in framing or method beyond routine application of existing tools.
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  5. 5Exceptional. Tackles a critical AI safety problem with a genuinely novel approach, or opens a new research direction. Clear theory of change. You'd be excited to share this with researchers in the area.

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  2. 2Weak. Approach has significant gaps: missing validation, flawed experimental design, or incomplete implementation.
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  4. 4Well presented. Easy to follow, well-structured, appropriate level of detail. Target audience would get it quickly.
  5. 5Exceptionally clear. A pleasure to read. Complex ideas made accessible. Could serve as a model for how to present this type of work.
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  1. I think this work is relevant because it could inform what regulators should demand labs retain.

    To make this even more impactful consider extending the blind re-code from 25 rows to the full 125 and test whether the intent-collapse pattern replicates on a second incident.

1 judge declined to score this project.

Cite this project

@misc{bhowmick2026project,
  title = {{Project Warrant: On Evidentiary Channel Dependency in a Frontier AI Incident Record}},
  author = {Aruneem Bhowmick},
  year = {2026},
  month = sep,
  note = {Submitted to AI Incident Response Sprint, an Apart Research Sprint},
  howpublished = {\url{https://apartresearch.com/sprints/projects/project-warrant-on-evidentiary-channel-dependency-in-a-frontier-ai-incident-record-3nb8}},
  url = {https://apartresearch.com/sprints/projects/project-warrant-on-evidentiary-channel-dependency-in-a-frontier-ai-incident-record-3nb8}
}

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