This study assesses the speed and accuracy of a large language model (LLM) in extracting ecological data from scientific literature compared to a human reviewer. The LLM extracted data over 50 times faster, achieving >90% accuracy for discrete and categorical data but showing lower accuracy for quantitative data. The findings highlight the LLM's potential for creating large ecological databases but emphasize the need for quality assurance to maintain data integrity.
Publisher
npj Biodiversity
Published On
May 16, 2024
Authors
Andrew V. Gougherty, Hannah L. Clipp
Tags
large language model
ecological data
scientific literature
data extraction
accuracy
quality assurance
human reviewer
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