Fine-tuned LLMs using positive-unlabeled learning on a literature-mined MOF dataset achieve 91.4% accuracy in predicting synthesis scale-up potential.
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Predicting Scale-Up of Metal-Organic Framework Syntheses with Large Language Models
Fine-tuned LLMs using positive-unlabeled learning on a literature-mined MOF dataset achieve 91.4% accuracy in predicting synthesis scale-up potential.