Evidence mapPaperPMID 39882908Full record

ArticleEuropean journal of translational myology2025

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

Giorgio Fanò-Illic, Daniele Coraci, Maria Chiara Maccarone, Stefano Masiero, Marco Quadrelli, Aldo Morra, Barbara Ravara, Amber Pond, Riccardo Forni, Paolo Gargiulo

Abstract read
In one paragraph

Article in European journal of translational myology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Giorgio Fanò-IllicInteruniversity Institute of Myology, Chieti-Pescara University, Italy; Free University of Alcatraz, Gubbio, Perugia, Italy; A&C M-C Foundation for Translational Myology, Padua. fanoillic@gmail.com.
Daniele CoraciDepartment of Neuroscience, Section of Rehabilitation, University of Padova, Padua. daniele.coraci@unipd.it.
Maria Chiara MaccaroneA&C M-C Foundation for Translational Myology, Padua, Italy; Department of Neuroscience, Section of Rehabilitation, University of Padova, Padua. mariachiara.maccarone@phd.unipd.it.
Stefano MasieroA&C M-C Foundation for Translational Myology, Padua, Italy; Department of Neuroscience, Section of Rehabilitation, University of Padova, Padua, Italy; CIR-Myo-Interdepartmental Research Center of Myology, University of Padova, Padua. stef.masiero@unipd.it.
Marco QuadrelliSynlab Euganea Medica Padova, Padua. marco.quadrelli@synlab.it.
Aldo MorraSynlab Euganea Medica Padova, Padua, Italy; Synlab IRCCS SDN S.p.A., Naples. aldo.morra@synlab.it.
Barbara RavaraA&C M-C Foundation for Translational Myology, Padua, Italy; CIR-Myo-Interdepartmental Research Center of Myology, University of Padova, Padua, Italy; Department of Biomedical Sciences, University of Padova, Padua . barbara.ravara@unipd.it.
Amber PondA&C M-C Foundation for Translational Myology, Padua, Italy; Southern Illinois University, Carbondale, IL. apond@siumed.edu.
Riccardo ForniInstitute of Biomedical and Neural Engineering, Reykjavik University, Reykjavik, Iceland; Department of Digital Transformation, Landspitali University Hospital, Reykjavík. riccardo21@ru.is.
Paolo GargiuloA&C M-C Foundation for Translational Myology, Padua, Italy; Institute of Biomedical and Neural Engineering, Reykjavik University, Reykjavik, Iceland; Department of Digital Transformation, Landspitali University Hospital, Reykjavík. paolo@ru.is.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Identifiers

PMID39882908
PMCPMC12038559

What Socratic holds

Textmetadata
LicenceCC BY-NC
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.