Agent trajectory data for AI-for-Science tasks, collected across 8 frontier models (glm-5.2, claude-sonnet-5, opus-4.8, deepseek-v4-pro, qwen3.7-max, minimax-m3, gemini-3.5-flash, gpt-5-mini) under real agentic harnesses (Claude Code / Codex / Gemini CLI), each running in an isolated container with held-out data and a host-side evaluation service. Two subsets capture two distinct task shapes: 70 tasks built from published frontier papers, each framed as premise → tension → (what step to take). The agent must make an open-ended move (new regime / mechanism / method-correction …); rollouts are classified by discovery regime (search / retrieval / discovery / unverified) under Wang & Buehler…
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