Scholarlink

<p>With the emergence of generative AI models such as ChatGPT, a&#xa0;new phase of scientific work is also beginning in orthopedics and trauma surgery. As a&#xa0;language-based deep learning model (LLM), ChatGPT offers a&#xa0;wide range of possible applications—especially in the creation, translation, and optimization of scientific texts. It supports authors in finding ideas, linguistic elaboration, and can even be used to check for plagiarism. It is a&#xa0;particularly valuable tool for non-native speakers. However, despite all the opportunities, its use involves considerable risks; studies show a&#xa0;high rate of incorrect or invented references. In addition, journals are sometimes flooded due to mass publication as a&#xa0;result of easier text generation. The scientific discourse, therefore, calls for clear rules on the use of LLM—particularly with regard to transparency, authorship, and the integrity of scientific work.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Schreiben mit System – ChatGPT in der wissenschaftlichen Praxis von Orthopädie und Unfallchirurgie

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月7日

查看全文
  • Philipp Zehnder,
  • Dominik Völk,
  • Conrad Ketzer,
  • Michael Zyskowski,
  • Peter Biberthaler

摘要

With the emergence of generative AI models such as ChatGPT, a new phase of scientific work is also beginning in orthopedics and trauma surgery. As a language-based deep learning model (LLM), ChatGPT offers a wide range of possible applications—especially in the creation, translation, and optimization of scientific texts. It supports authors in finding ideas, linguistic elaboration, and can even be used to check for plagiarism. It is a particularly valuable tool for non-native speakers. However, despite all the opportunities, its use involves considerable risks; studies show a high rate of incorrect or invented references. In addition, journals are sometimes flooded due to mass publication as a result of easier text generation. The scientific discourse, therefore, calls for clear rules on the use of LLM—particularly with regard to transparency, authorship, and the integrity of scientific work.