Article

Large Language Models (LLMs) for Evidence Synthesis: An Exploratory Evaluation and A New Approach for Automated Data Extraction and Validation

2026-06-04

Abstract excerpt

<p>Data extraction and coding are among one of the most labor-intensive and error-prone stages of evidence synthesis (ES), yet they directly affect the validity of meta-analytic conclusions. Automating this step could alleviate these constraints, but must first demonstrate accurate and reliable extraction. This study investigates whether generative large language models (LLMs) can meet this standard by improving t...

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Literature Corpus work: d8e56b29-6aef-5492-957a-f3ebc7a19f90
DOI: 10.31234/osf.io/udysp_v2

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