在已发表的骨科研究中评估基于人工智能的写作辅助:未来解读的检测和趋势。

IF 4.3 1区 医学 Q1 ORTHOPEDICS
Tucker Callanan, Josue Marquez, Claire Pisani, Phillip Schmitt, John Pietro, Miaoyan Chen, John Milner, Mohammad Daher, Luka Katz, Jonathan Liu, Alan H Daniels
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引用次数: 0

摘要

背景:人工智能(AI),特别是大型语言模型(llm)与科学写作的整合,引发了关于其伦理、流行程度和在骨科文献中的影响的问题。虽然已经开发出检测人工智能生成内容的工具,但对人工智能检测百分比的解释及其临床相关性仍不清楚。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程度,并建立一个统计阈值来解释人工智能检测百分比。方法:为了建立基线,使用ZeroGPT对2000年发表的300篇手稿进行了人工智能生成内容的分析。随后对ChatGPT发布后连续发表的3374篇骨科论文进行了分析。计算了95%的置信区间,以设置显著人工智能参与的阈值。人工智能检测百分比高于该阈值(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份人工智能时代之前的手稿进行实证分析,平均人工智能检出率(及标准差[SD])为10.84%±11.02%。在分析的3374篇后人工智能时代的手稿中,16.7%超过了人工智能检测阈值32.875%(比前人工智能时代的基线高出2个标准差),表明人工智能的参与程度很高。原稿和综述研究之间无显著差异(显著人工智能涉及的百分比分别为16.4%和18.2%;P = 0.40)。不同期刊的人工智能参与程度差异很大,从《美国运动医学杂志》的5.6%到《骨与关节外科杂志》的38.3% (p < 0.001)。结论:本研究考察了人工智能在骨科出版稿件写作中的辅助作用,并提供了第一个基于证据的阈值来解释人工智能检测百分比。我们的研究结果显示,在最近发表的骨科文献中,有16.7%的文献涉及人工智能。这一发现强调了明确的指导方针、道德标准、负责任的人工智能使用和改进的检测工具对于保持骨科研究的质量、真实性和完整性的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluating Artificial Intelligence-Based Writing Assistance Among Published Orthopaedic Studies: Detection and Trends for Future Interpretation.

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.

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来源期刊
CiteScore
8.90
自引率
7.50%
发文量
660
审稿时长
1 months
期刊介绍: The Journal of Bone & Joint Surgery (JBJS) has been the most valued source of information for orthopaedic surgeons and researchers for over 125 years and is the gold standard in peer-reviewed scientific information in the field. A core journal and essential reading for general as well as specialist orthopaedic surgeons worldwide, The Journal publishes evidence-based research to enhance the quality of care for orthopaedic patients. Standards of excellence and high quality are maintained in everything we do, from the science of the content published to the customer service we provide. JBJS is an independent, non-profit journal.
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