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Evaluation of the impact of large language learning models on articles submitted to Orthopaedics & Traumatology: Surgery & Research (OTSR): A significant increase in the use of artificial intelligence in 2023 - 29/11/23

Doi : 10.1016/j.otsr.2023.103720 
Gaëlle Maroteau a, Jae-Sung An b, Jérome Murgier c, Christophe Hulet a, Matthieu Ollivier d, e, Alexandre Ferreira a,
a Unité Inserm Comète 1075, Department of Orthopaedics and Traumatology, Caen University Hospital, avenue Cote-de-Nacre, 14000 Caen, France 
b Tokyo Medical and Dental University, 1 Chome-5-45 Yushima, Bunkyo City, Tokyo 113-8510, Japan 
c Service de chirurgie orthopédique, clinique Aguiléra, 21, rue de l’Estagnas, 64200 Biarritz, France 
d Institute of Movement and Locomotion, Department of Orthopaedics and Traumatology, Sainte-Marguerite Hospital, BP 29, 270, boulevard Sainte-Marguerite, 13274 Marseille, France 
e Aix-Marseille Unit, Institute for Locomotion, Department of Orthopaedics and Traumatology, CNRS, ISM, Sainte-Marguerite Hospital, AP–HM, Marseille, France 

Corresponding author.

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Abstract

Introduction

There has been an unprecedented rise is the use of artificial intelligence (AI) amongst medical fields. Recently, a dialogue agent called ChatGPT (Generative Pre-trained Transformer) has grown in popularity through its use of large language models (LLM) to clearly and precisely generate text on demand. However, the impact of AI on the creation of scientific articles is remains unknown. A retrospective study was carried out with the aim of answering the following questions: identify the presence of text generated by LLM before and after the increased usage of ChatGPT in articles submitted in OTSR; determine if the type of article, the year of submission, and the country of origin, influenced the proportion of text generated, at least in part by AI.

Material and methods

A total of 390 English articles were submitted to OTSR in January, February and March 2022 (n=204) and over the same months of 2023 (n=186) were analyzed. All articles were analyzed using the ZeroGPT tool, which provides an assumed rate of AI use expressed as a percentage. A comparison of the average rate of AI use was carried out between the articles submitted in 2022 and 2023. This comparison was repeated keeping only the articles with the highest percentage of suspected AI use (greater than 10 and 20%). A secondary analysis was carried out to identify risk factors for AI use.

Results

The average percentage of suspected LLM use in the entire cohort was 11%±6, with 160 articles (41.0%) having a suspected AI rate greater than 10% and 61 (15.6%) with an assumed AI rate greater than 20%. A comparison between articles submitted in 2022 and 2023 revealed a significant increase in the use of these tools after the launch of ChatGPT 3.5 (9.4% in 2022 and 12.6% in 2023 [p=0.004]). The number of articles with suspected AI rates of greater than 10 and 20% were significantly higher in 2023: >10%: 71 articles (34.8%) versus 89 articles (47.8%) (p=0.008) and >20%: 21 articles (10.3%) versus 40 articles (21.5%) (p=0.002). A risk factor analysis for LLLM use, demonstrated that authors of Asian geographic origin, and the submission year 2023 were associated with a higher rate of suspected AI use. An AI rate >20% was associated to Asian geographical origin with an odds ratio of 1.79 (95% CI: 1.03–3.11) (p=0.029), while the year of submission being 2023 had an odds ratio of 1.7 (95% CI: 1.1–2.5) (p=0.02).

Conclusion

This study highlights a significant increase in the use of LLM in the writing of articles submitted to the OTSR journal after the launch of ChatGPT 3.5. The increasing use of these models raises questions about originality and plagiarism in scientific research. AI offers creative opportunities but also raises ethical and methodological challenges.

Level of evidence

III; case control study.

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Keywords : Artificial intelligence, ChatGPT, Large language learning models, Chatbot, Scientific article


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Vol 109 - N° 8

Article 103720- décembre 2023 Retour au numéro
Article précédent Article précédent
  • Scientific misconduct: Plagiarism and non-compliance with disclosure of interest: Retrospective analysis of 1 year's submissions to Orthopaedics & Traumatology: Surgery & Research
  • Henry Coudane, Rémi Kohler, Hervé Maisonneuve, Philippe Beaufils, Jennifer Bosi, Camille Gravelier, Jane-Laure Danan
| Article suivant Article suivant
  • What is the rate of text generated by artificial intelligence over a year of publication in Orthopedics & Traumatology: Surgery & Research? Analysis of 425 articles before versus after the launch of ChatGPT in November 2022
  • Théophile Bisi, Anthony Risser, Philippe Clavert, Henri Migaud, Julien Dartus

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