Ejtm3 experiences after ChatGPT and other AI approaches: values, risks, countermeasures.

IF 1.8 Q3 MEDICINE, RESEARCH & EXPERIMENTAL European Journal of Translational Myology Pub Date : 2025-03-31 Epub Date: 2025-01-30 DOI:10.4081/ejtm.2025.13670
Giorgio Fanò-Illic, Daniele Coraci, Maria Chiara Maccarone, Stefano Masiero, Marco Quadrelli, Aldo Morra, Barbara Ravara, Amber Pond, Riccardo Forni, Paolo Gargiulo
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Abstract

We invariably hear that Artificial Intelligence (AI), a rapidly evolving technology, does not just creatively assemble known knowledge. We are told that AI learns, processes and creates, starting from fixed points to arrive at innovative solutions. In the case of scientific work, AI can generate data without ever having entered a laboratory, (i.e., blatantly plagiarizing the existing literature, a despicable old trick). How does an editor of a scientific journal recognize when she or he is faced with something like this? The solution is for editors and referees to rigorously evaluate the track records of submitting authors and what they are doing. For example, false color evaluations of 2D and 3D CT and MRI images have been used to validate functional electrical stimulation for degenerated denervated muscle and a home Full-Body In-Bed Gym program. These have been recently published in Ejtm and other journals. The editors and referees of Ejtm can exclude the possibility that the images were invented by ChatGPT. Why? Because they know the researchers: Marco Quadrelli, Aldo Morra, Daniele Coraci, Paolo Gargiulo and their collaborators as well! Artificial intelligence is not banned by the EJTM, but when submitting their manuscripts to previous and to a new Thematic Section dedicated to Generative AI in Translational Mobility Medicine authors must openly declare whether they have used artificial intelligence, of what type and for what purposes. This will not avoid risks of plagiarism or worse, but it will better establish possible liabilities.

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Ejtm3在ChatGPT和其他AI方法之后的经验:价值、风险、对策。
我们总是听到人工智能(AI),一种快速发展的技术,不只是创造性地组装已知的知识。我们被告知,人工智能学习、处理和创造,从固定的点开始,达到创新的解决方案。以科学工作为例,人工智能可以在没有进入实验室的情况下生成数据(即公然抄袭现有文献,这是一种卑鄙的老把戏)。科学期刊的编辑如何识别她或他面临的这种情况?解决方案是让编辑和审稿人严格评估提交作者的记录和他们在做什么。例如,2D和3D CT和MRI图像的假颜色评估已被用于验证退化失神经肌肉的功能性电刺激和家庭全身床上健身计划。这些研究最近发表在Ejtm和其他期刊上。Ejtm的编辑和审稿人可以排除ChatGPT伪造图像的可能性。为什么?因为他们知道研究人员:Marco Quadrelli, Aldo Morra, Daniele Coraci, Paolo Gargiulo和他们的合作者!EJTM不禁止人工智能,但在向以前和新的专门用于转化移动医学生成人工智能的专题部分提交手稿时,作者必须公开声明他们是否使用了人工智能,使用的类型和目的。这并不能避免抄袭或更糟的风险,但它可以更好地建立可能的责任。
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来源期刊
European Journal of Translational Myology
European Journal of Translational Myology MEDICINE, RESEARCH & EXPERIMENTAL-
CiteScore
3.30
自引率
27.30%
发文量
74
审稿时长
10 weeks
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