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Into the Unknown Direction Node Pass Rate

Science · 2026-10-13

Node-level direction-specific grading on the 15 Into the Unknown research problems. An agent receives a published paper with its code and data and a follow-up direction proposed by one of its authors, a scientist at or formerly at a US Department of Energy national laboratory, and must write the follow-up paper with code and logs. Submissions are graded by a GPT-6 Astra agentic judge, four times with per-node majority voting, against an integrity rubric and a direction-specific rubric built from the scientist's stated conditions. Fifteen problems per agent make it a diagnostic. The score is the percentage of direction-specific rubric nodes, covering required deliverables and the scientist's success conditions, that received their highest rating across the agent's submissions.

Top models (higher is better)

ModelScore
GPT-6 Astra83.6
Claude Opus 5.580.0
GPT-5.6 Sol74.9
Claude Fable 571.0
Claude Opus 566.8
Opus 4.860.1
Kimi K352.9
DeepSeek V4 Pro 081351.8
GLM-5.344.3
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