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)
| Model | Score |
|---|---|
| GPT-6 Astra | 83.6 |
| Claude Opus 5.5 | 80.0 |
| GPT-5.6 Sol | 74.9 |
| Claude Fable 5 | 71.0 |
| Claude Opus 5 | 66.8 |
| Opus 4.8 | 60.1 |
| Kimi K3 | 52.9 |
| DeepSeek V4 Pro 0813 | 51.8 |
| GLM-5.3 | 44.3 |