An LLM-powered agent pipeline extracts ~9,000 structured concrete materials records from 278 publications with F1 scores up to 0.97, creating the largest open blended cement concrete database and demonstrating that larger, richer datasets improve ML prediction and generalization.
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Large language model-enabled automated data extraction for concrete materials informatics
An LLM-powered agent pipeline extracts ~9,000 structured concrete materials records from 278 publications with F1 scores up to 0.97, creating the largest open blended cement concrete database and demonstrating that larger, richer datasets improve ML prediction and generalization.