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The accuracy-bias trade-offs in AI text detection tools and their impact on fairness in scholarly publication
16 references·0 citing·41 second hop
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References

  • 2023ChatGPT listed as author on research papers: many scientists disapprove868 cited
  • 2023Testing of detection tools for AI-generated text577 cited
  • 2021Transitioning to E-Learning during the COVID-19 pandemic: How have Higher Education Institutions responded to the challenge?529 cited
  • 2013Open access: The true cost of science publishing524 cited
  • 2023Nonhuman “Authors” and Implications for the Integrity of Scientific Publication and Medical Knowledge420 cited
  • 2023The manifold costs of being a non-native English speaker in science412 cited
  • 2020Disadvantages in preparing and publishing scientific papers caused by the dominance of the English language in science: The case of Colombian researchers in biological sciences399 cited
  • 2023Exploring the Boundaries of Reality: Investigating the Phenomenon of Artificial Intelligence Hallucination in Scientific Writing Through ChatGPT References397 cited
  • 2023Evaluating the efficacy of AI content detection tools in differentiating between human and AI-generated text387 cited
  • 2001Attitudes of Journal Editors to Nonnative Speaker Contributions349 cited
  • 2024Publishers’ and journals’ instructions to authors on use of generative artificial intelligence in academic and scientific publishing: bibliometric analysis259 cited
  • 2011English as an international language of scientific publication: a study of attitudes251 cited
  • 2023Detection of GPT-4 Generated Text in Higher Education: Combining Academic Judgement and Software to Identify Generative AI Tool Misuse

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231 cited
  • 2021Peer feedback or peer feedforward? Enhancing students’ argumentative peer learning processes and outcomes163 cited
  • 2004Challenges of Entering Discourse Communities Through Publishing in English: Perspectives of Nonnative-Speaking Doctoral Students in the United States of America140 cited
  • 2020Understanding university students’ behavioral intention to use Edmodo through the lens of an extended technology acceptance model127 cited
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