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Performance of AI Tools in Citing Retracted Literature : Content Analysis.

Sebastian Labenbacher1, Maximilian Niederer1, Sascha Hammer1

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PubMed
Summary

Generative artificial intelligence (GenAI) tools struggle to identify retracted scientific articles. Independent verification is crucial for research integrity when using these AI tools.

Keywords:
AIartificial intelligencedata accuracyethicsevidence-based Practiceretraction of publicationretractionsscientific misconduct

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Area of Science:

  • Artificial Intelligence in Scientific Research
  • Bibliometrics and Research Integrity
  • Information Science

Background:

  • Generative artificial intelligence (GenAI) tools are increasingly used in scientific research for tasks like literature searches and manuscript preparation.
  • Concerns exist regarding GenAI reliability, especially its tendency to cite inaccurate, fabricated, or retracted literature.
  • The unrecognized inclusion of retracted studies poses a significant risk to research integrity and evidence-based decision-making.

Purpose of the Study:

  • To evaluate the ability of freely available GenAI tools to correctly handle retracted scientific articles during literature searches.
  • To assess the accuracy, reliability, and consistency of GenAI tools in recognizing retracted literature.

Main Methods:

  • A pragmatic trial evaluated nine widely used free-access GenAI tools (ChatGPT 4, ChatGPT 5, Claude, Gemini, Perplexity, Microsoft Copilot, SciSpace, ScienceOS, and Consensus).
  • Standardized questions were posed to each tool regarding topic overview, article identification, summarization, and retraction status for 15 selected retracted articles.
  • Responses were repeated to assess intratool consistency and independently rated for accuracy by two researchers.

Main Results:

  • No evaluated GenAI tool consistently handled retracted articles correctly; none achieved perfect accuracy across all tasks.
  • ChatGPT 5 performed best, correctly answering all five questions for 53.3% of retracted articles.
  • Research-focused tools (SciSpace, ScienceOS, Consensus) failed to provide any fully correct response sets, and retracted articles were often included in overviews without warnings.

Conclusions:

  • Freely available GenAI tools currently cannot reliably detect, exclude, or flag retracted scientific literature.
  • The uncritical reproduction of retracted studies by GenAI poses a substantial threat to research integrity.
  • Independent source checking remains essential when using AI-assisted literature tools until retraction-aware verification mechanisms are integrated.