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评估已发表的骨科研究中基于人工智能的写作辅助工具:检测与未来解读趋势

Evaluating Artificial Intelligence-Based Writing Assistance Among Published Orthopaedic Studies: Detection and Trends for Future Interpretation.

作者信息

Callanan Tucker, Marquez Josue, Pisani Claire, Schmitt Phillip, Pietro John, Chen Miaoyan, Milner John, Daher Mohammad, Katz Luka, Liu Jonathan, Daniels Alan H

机构信息

Department of Orthopaedic Surgery, Brown University Health, Providence, Rhode Island.

Warren Alpert Medical School, Brown University, Providence, Rhode Island.

出版信息

J Bone Joint Surg Am. 2025 May 30;107(16):1887-1893. doi: 10.2106/JBJS.24.01462.

Abstract

BACKGROUND

The integration of artificial intelligence (AI), particularly large language models (LLMs), into scientific writing has led to questions about its ethics, prevalence, and impact in orthopaedic literature. While tools have been developed to detect AI-generated content, the interpretation of AI detection percentages and their clinical relevance remain unclear. The aim of this study was to quantify AI involvement in published orthopaedic manuscripts and to establish a statistical threshold for interpreting AI detection percentages.

METHODS

To establish a baseline, 300 manuscripts published in the year 2000 were analyzed for AI-generated content with use of ZeroGPT. This was followed by an analysis of 3,374 consecutive orthopaedic manuscripts published after the release of ChatGPT. A 95% confidence interval was calculated in order to set a threshold for significant AI involvement. Manuscripts with AI detection percentages above this threshold (32.875%) were considered to have significant AI involvement in their content generation.

RESULTS

Empirical analysis of the 300 pre-AI-era manuscripts revealed a mean AI detection percentage (and standard deviation [SD]) of 10.84% ± 11.02%. Among the 3,374 post-AI-era manuscripts analyzed, 16.7% exceeded the AI detection threshold of 32.875% (2 SDs above the baseline for the pre-AI era), indicating significant AI involvement. No significant difference was found between primary manuscripts and review studies (percentage with significant AI involvement, 16.4% and 18.2%, respectively; p = 0.40). Significant AI involvement varied significantly across journals, with rates ranging from 5.6% in The American Journal of Sports Medicine to 38.3% in The Journal of Bone & Joint Surgery (p < 0.001).

CONCLUSIONS

This study examined AI assistance in the writing of published orthopaedic manuscripts and provides the first evidence-based threshold for interpreting AI detection percentages. Our results revealed significant AI involvement in 16.7% of recently published orthopaedic literature. This finding highlights the importance of clear guidelines, ethical standards, responsible AI use, and improved detection tools to maintain the quality, authenticity, and integrity of orthopaedic research.

摘要

背景

人工智能(AI),尤其是大语言模型(LLMs)融入科学写作引发了有关其在骨科文献中的伦理、普及程度及影响的问题。虽然已开发出工具来检测人工智能生成的内容,但对人工智能检测百分比及其临床相关性的解读仍不明确。本研究的目的是量化人工智能在已发表的骨科手稿中的参与情况,并确定用于解释人工智能检测百分比的统计阈值。

方法

为建立基线,使用ZeroGPT对2000年发表的300篇手稿进行人工智能生成内容的分析。随后对ChatGPT发布后连续发表的3374篇骨科手稿进行分析。计算95%置信区间以设定人工智能显著参与的阈值。人工智能检测百分比高于此阈值(32.875%)的手稿被认为在其内容生成中有显著的人工智能参与。

结果

对300篇人工智能时代之前的手稿进行实证分析,发现人工智能检测百分比的均值(及标准差[SD])为10.84%±11.02%。在分析的3374篇人工智能时代之后的手稿中,16.7%超过了32.875%的人工智能检测阈值(比人工智能时代之前的基线高出2个标准差),表明有显著的人工智能参与。原创手稿和综述研究之间未发现显著差异(有显著人工智能参与的百分比分别为16.4%和18.2%;p = 0.40)。不同期刊的人工智能显著参与情况差异显著,比例从《美国运动医学杂志》的5.6%到《骨与关节外科杂志》的38.3%不等(p < 0.001)。

结论

本研究考察了人工智能在已发表的骨科手稿写作中的辅助情况,并提供了首个基于证据的解释人工智能检测百分比的阈值。我们的结果显示,在最近发表的骨科文献中,16.7%有显著的人工智能参与。这一发现凸显了明确指南、道德标准、负责任地使用人工智能以及改进检测工具对于维持骨科研究的质量、真实性和完整性的重要性。

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