Large language models for climate vulnerability assessment: a reproducible framework with uncertainty quantification

Climate vulnerability assessment faces significant challenges in integrating heterogeneous data sources while maintaining statistical rigor and methodological transparency. This study proposes a novel framework combining Large Language Models with conformal prediction for climate vulnerability asses...

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Autors principals:	Aihua Zhang, Hui Li
Format:	Artigo
Idioma:	Inglês
Publicat:	Frontiers Media S.A. 2026-04-01
Col·lecció:	Frontiers in Earth Science
Matèries:	climate vulnerability CMIP6 conformal prediction large language models uncertainty quantification
Accés en línia:	https://www.frontiersin.org/articles/10.3389/feart.2026.1792665/full
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