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. 2025 Jun;18(2):e70046.
doi: 10.1111/jebm.70046.

Variability and Advancements in ChatGPT Risk of Bias Assessments: A Replication and Comparative Analysis

Jules Descamps  1   2   3 , Matthieu Resche-Rigon  1   2 , Guillaume Draznieks  4   5 , Cesar Quirino  5 , Rémy Nizard  3 , Pierre-Alban Bouché  1   2   3
Affiliations

Variability and Advancements in ChatGPT Risk of Bias Assessments: A Replication and Comparative Analysis

Jules Descamps et al. J Evid Based Med. 2025 Jun.
No abstract available

Keywords: data extraction; large language models (LLMs); risk of bias.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

FIGURE 1
FIGURE 1
Comparison of the categorization of risk of bias assessments in the five domains and overall between Gs: extracted assessments; 4o: ChatGPT‐4o from Kuitunen et al.; 4o‐new: ChatGPT‐4o from Descamps et al.; 4o‐fram: ChatGPT‐4o with DeepDocs framework; o1: ChatGPT‐o1; D1: bias arising from the randomization process; D2: bias due to deviations from the intended interventions; D3: bias due to missing outcome data; D4: bias in the measurement of the outcome; D5: bias in selection of the reported results.
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