AI agents reproduce 72% of the human ideological gap in effect estimates from an immigration dataset and introduce the m-value plus Agentic Bootstrap to quantify a reported analysis's position in the multiverse of defensible paths.
Towards end-to-end automation of ai research.Nature, 651(8107):914–919
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Eywa enables language-based agentic AI systems to collaborate with specialized scientific foundation models for improved performance on structured data tasks.
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The Agentic Garden of Forking Paths
AI agents reproduce 72% of the human ideological gap in effect estimates from an immigration dataset and introduce the m-value plus Agentic Bootstrap to quantify a reported analysis's position in the multiverse of defensible paths.
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Heterogeneous Scientific Foundation Model Collaboration
Eywa enables language-based agentic AI systems to collaborate with specialized scientific foundation models for improved performance on structured data tasks.