Artificial Intelligence in Research and Publication: Tools and Guidelines
Notice bibliographique
Résumé
The world is evolving at a faster pace as regards technology in every sector of life, with artificial intelligence (AI) being one of the recent innovations. In the research front, AI has been increasingly used in the recent years, for better efficiency as well as to enhance the quality of research at every phase from enquiring a research question to research publication. AI has become an essential productivity tool which substantially revolutionizes research as well as academic writing, namely, idea development and research design, content development and structuring, literature review and synthesis, data management and analysis, editing, review, and publishing support, and communication, outreach, and ethical compliance.[1] AI tools aid in research planning, literature search and finalizing the study design by designing specific research models and by incorporating explicit research criteria into such research models, thereby generating optimal research designs that maximize the research study effectiveness.[2] For example, Connected Papers, Consensus, Elicit, Keenious, Research Rabbit, Scite, Scholarcy, Semantic Scholar, and Undermind are some of the AI tools that are useful for literature search, finding answers to research questions and refining research questions.[3] Having clear research objectives, AI tools can also effectively be used for data analysis, with most appropriate AI tools and algorithms. AI tools aid in taking and organizing notes that would be relevant during academic and research manuscript writing,[2] for example, ChatGPT, Grammarly, and Paraphraser. As regards, publication process, there are AI-powered peer review tools that can create the potential semiautomated peer review systems where potentially poor-quality or controversial research papers can be identified, and reviewers can be matched with manuscripts from their subject-matter expertise. Although AI tools cannot execute peer review, AI tools can be used effectively in the peer review process for initial quality control for submitted manuscripts and for finding peer reviewers.[2] Even though AI tools are beneficial in faster initial peer review process, it may have its own set of disadvantages such as risking confidentiality, compromising the value of human expertise, biasness, and issues with transparency and accountability.[4] GUIDELINES AND POLICIES To safeguard the research participants, for ethical conduct as well as for dissemination of research outcomes by the authors, and for ethical publication process by the editors, reviewers, and publishers, many ethical guidelines have been developed pertaining to research involving AI. THE INDIAN COUNCIL OF MEDICAL RESEARCH GUIDELINES ON ARTIFICIAL INTELLIGENCE IN RESEARCH The Ethical Guidelines for Application of Artificial Intelligence in Biomedical Research and Healthcare[5] by the Indian Council of Medical Research in 2023 have laid down the ethical principles for use of the AI technology in health care such as autonomy, safety and risk minimization, trustworthiness, data privacy, accountability and liability, optimization of data quality, accessibility, equity and inclusiveness, collaboration, nondiscrimination and fairness principles, and validity. The special concerns that need to be reviewed by the ethical review committee, for research pertaining to AI, are summarized in Table 1.Table 1: Special Ethical Issues Related to Reviewing a Protocol[ 5 ]The guidelines also highlight the specifics of informed consent process in research involving AI as well as have put forth the ethics checklist of AI for biomedical research and health care.[2] The AI technologies’ regulations in health care are still emerging in developed countries like US and EU. The Government of India is also in the process of streamlining the regulations regarding AI technologies in health care. THE INTERNATIONAL COMMITTEE OF MEDICAL JOURNAL EDITORS GUIDELINES ON ARTIFICIAL INTELLIGENCE IN RESEARCH PUBLICATION The guidelines on the “Recommendations for the Conduct, Reporting, Editing, and Publication of Scholarly Work in Medical Journals” updated in January 2025 by the International Committee of Medical Journal Editors recommend the requirements by the journals from the authors to disclose and describe in appropriate sections, the use of AI such as Large Language Models, chatbots, or image creators in the submitted manuscript. Authors are expected to be responsible for the accuracy, integrity, and originality of the work in any submitted material that included the use of AI-assisted technologies, during any phase of the conduct of research or submission of the research manuscript. Authors cannot list AI and AI-assisted technologies as an author or coauthor, nor cite AI as an author.[6] THE COMMITTEE ON PUBLICATION ETHICS GUIDELINES ON ARTIFICIAL INTELLIGENCE IN RESEARCH PUBLICATION The discussion document by the Committee on Publication Ethics (COPE) puts forth that the authors have the right to be informed if any of the publishing processes or workflows were automated or if anywhere AI decisions were involved by the editorial board of the journal.[7] The authors have the right to challenge the editorial decision, irrespective of whether decision was made by the AI or the human editor. The editorial board of the journal and publisher are accountable for the editorial decision if made by use of AI. At the current stage of the development of AI, COPE recommends a cautious approach by the editors and publishers with respect to adoption of AI for many purposes such as misconduct and research integrity evaluations, peer review process, and author’s citation count. The editors and the publishers must rule out the biases if any and share any information regarding the AI tools, so that these can be updated by developers based on their feedback. The publishing house: The Lippincott Williams and Wilkins-A Wolters Kluwer Business, Medknow Group of Publication, allows the editors, the use of AI tools and software in the Indian Journal of Occupational Therapy (IJOT) online management system for plagiarism check of submitted manuscripts. The All India Occupational Therapists’ Association executive committee and the editorial board of the IJOT along with the publication house executives recommend adhering to the national and international guidelines pertaining to use of AI in research and publications and to transparently report the use of AI in research.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».