Analysing the potential of ChatGPT to support plant disease risk forecasting systems

This study explores the potential of two versions of the ChatGPT large language model (GPT-3.5 Turbo and GPT-4) in supporting plant disease risk forecasting through the translation of model-based predictions into advisory messages. A dataset of 3125 messages, each referred to an artificially generat...

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Bibliografiska uppgifter

Huvudupphov:	Roberta Calone, Elisabetta Raparelli, Sofia Bajocco, Eugenio Rossi, Lorenzo Crecco, Danilo Morelli, Chiara Bassi, Rocchina Tiso, Riccardo Bugiani, Fabio Pietrangeli, Giovanna Cattaneo, Camilla Nigro, Marco Secondo Gerardi, Simone Bussotti, Angela Sanchioni, Danilo Tognetti, Mariangela Sandra, Irene De Lillo, Paolo Framarin, Sandra Di Ferdinando, Simone Bregaglio
Materialtyp:	Artigo
Språk:	Inglês
Utgiven:	Elsevier 2025-03-01
Serie:	Smart Agricultural Technology
Ämnen:	Large Language Models Integrated Pest Management Advisory Messages Stakeholders Engagement Lexical Analysis Sentiment Analysis
Länkar:	http://www.sciencedirect.com/science/article/pii/S2772375525000589
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