In a recent paper study posted to the arXiv preprint server, researchers developed and validated a large language model (LLM) based on the Generative Pre-trained Transformer 4 (GPT-4) framework. The model was designed to accept raw PDF scientific manuscripts as inputs and provide feedback on four key aspects of the publication review process: novelty and significance, reasons for acceptance, reasons for rejection, and improvement suggestions. Results of the large-scale systematic analysis showed that the model was comparable to human researchers in the feedback provided. A follow-up prospective user study found that more than 50% of researchers were happy with the feedback provided, and an extraordinary 82.4% found the GPT-4 feedback more useful than feedback received from human reviewers.
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