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Casey W. Dunn

2 papers indexed here

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Oct 2026

Extracting AI agent-accessible data from biodiversity literature with corpus.

Much of our shared knowledge about biodiversity, including data on species' traits, relationships, and occurrences, is stored in the published literature. This body of knowledge can span multiple centuries, languages, and publication formats, making it challenging to collect, compare, and synthesize data across entire...

Samuel H. Church, Maciej K. Mańko, Felipe Zapata et al. · 0 citations
Review Open access Sep 2026

Designing reproducible large-language-model-assisted scientific analyses

Summary Large language models (LLMs) increasingly write code, analyze data, and orchestrate scientific workflows. This can create reproducibility challenges because LLMs blur the boundary between how an analysis is built and what it depends on at run time. Guidelines for LLM-assisted science begin with a critical choic...

C. Dunn, Darrin T. Schultz, J. Musser · 0 citations

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