The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index; none of the 6 sources its claims cite is checked for support yet.
Chatbots, Generative AI, and Scholarly Manuscripts: WAME Recommendations on Chatbots and Generative Artificial Intelligence in Relation to Scholarly Publications Revised May 31, 2023
Open accessAbstract
Introduction This statement revises our earlier “WAME Recommendations on ChatGPT and Chatbots in Relation to Scholarly Publications” (January 20, 2023). The revision reflects the proliferation of chatbots and their expanding use in scholarly publishing over the last few months, as well as emerging concerns regarding lack of authenticity of content when using chatbots. These Recommendations are intended to inform editors and help them develop policies for the use of chatbots in papers published in their journals. They aim to help authors and reviewers understand how best to attribute the use of chatbots in their work, and to address the need for all journal editors to have access to manuscript screening tools. In this rapidly evolving field, we will continue to modify these recommendations as the software and its applications develop. A chatbot is a tool “[d]riven by [artificial intelligence], automated rules, natural-language processing (NLP), and machine learning (ML)…[to] process data to deliver responses to requests of all kinds.”1 Artificial intelligence (AI) is “the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings.”2 “Generative modeling is an artificial intelligence technique that generates synthetic artifacts by analyzing training examples; learning their patterns and distribution; and then creating realistic facsimiles. Generative AI (GAI) uses generative modeling and advances in deep learning (DL) to produce diverse content at scale by utilizing existing media such as text, graphics, audio, and video.”3, 4 Chatbots are activated by a plain-language instruction, or “prompt,” provided by the user. They generate responses using statistical and probability-based language models.5 This output has some characteristic properties. It is usually linguistically accurate and fluent but, to date, it is often compromised in various ways. For example, chatbot output currently carries the risk of including biases, distortions, irrelevancies, misrepresentations, and plagiarism many of which are caused by the algorithms governing its generation and heavily dependent on the contents of the materials used in its training. Consequently, there are concerns about the effects of chatbots on knowledge creation and dissemination – including their potential to spread and amplify mis- and disinformation6 – and their broader impact on jobs and the economy, as well as the health of individuals and populations. New legal issues have also arisen in connection with chatbots and generative AI.7 Chatbots retain the information supplied to them, including content and prompts, and may use this information in future responses. Therefore, scholarly content that is generated or edited using AI would be retained and as a result, could potentially appear in future responses, further increasing the risk of inadvertent plagiarism on the part of the user and any future users of the technology. Anyone who needs to maintain confidentiality of a document, including authors, editors, and reviewers, should be aware of this issue before considering using chatbots to edit or generate work.9 Chatbots and their applications illustrate the powerful possibilities of generative AI, as well as the risks. These Recommendations seek to suggest a workable approach to valid concerns about the use of chatbots in scholarly publishing.
Overview
CoChat Summary
TL;DR
These revised WAME recommendations state that chatbots cannot be authors and set transparency and attribution requirements for their use in scholarly manuscripts. They add a fifth recommendation that editors and reviewers disclose chatbot use and that editors need digital tools to address AI’s effects on publishing.
Key findings
- Five principal recommendations are listed: only humans can be authors; authors should acknowledge sources; authors must take public responsibility; editors and reviewers should specify any chatbot use in evaluation, reviews, and correspondence; and editors need appropriate digital tools to deal with chatbots’ effects on publishing.
- Chatbots cannot meet ICMJE authorship criteria, particularly final approval of the published version and accountability for accuracy/integrity; they cannot understand conflict-of-interest statements, have no legal standing to sign them, and have no affiliation independent of their developers.
- Authors using a chatbot to draft new text should note this in the acknowledgment and specify all prompts used to generate text or convert text/prompts into tables or illustrations. If AI is used for analytical work, results reporting, tables/figures, or code, this should be stated in the Abstract and Methods, with the full prompt, time and date of query, AI tool, and version.
- Chatbots retain prompts and content and may use them in future responses, so supplying a manuscript to a chatbot breaches confidentiality. Authors are responsible for accuracy, plagiarism, attribution, and including counterviews; editors and reviewers are responsible for any content and citations generated by a chatbot.
Methods
- This is a revised WAME consensus/recommendation statement, updating the January 20, 2023 “WAME Recommendations on ChatGPT and Chatbots in Relation to Scholarly Publications” in response to chatbot proliferation and concerns about authenticity.
- No empirical design, dataset, sample, or statistical analysis is reported; the document provides normative guidance for editors, authors, and reviewers.
Limitations
- Stated: the field is rapidly evolving, and the recommendations will continue to be modified as software and applications develop.
- Evident: the document reports no empirical data, formal evidence synthesis, or tested interventions; its recommendations are normative rather than empirically validated.
Model-written summary. Check it against the paper before relying on it.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
0 Valid · 5 Not valid · 5 Not checked · 7 Own results and interpretations
- Probably not a substantial claim. 15
- It may state two separate claims as one. 9
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ WAME Recommendations on Chatbots and Generative Artificial Intelligence in Relation to Scholarly > Additional information
“Noting that plagiarism is "the practice of taking someone else's work or ideas and passing them off as one's own", 13”
§ WAME Recommendations on Chatbots and Generative Artificial Intelligence in Relation to Scholarly > References
“13. Methods. Preparing a Manuscript for Submission to a Medical Journal. ICMJE. https://www.icmje.org/recommendations/browse/manuscript-preparation/preparing-for-submission.html#d Accessed May 27, 2023. 14. Plagiarism. Oxford Reference, https://www.oxfordreference.com/display/10.1093/oi/authority.20110803100329803;jsessioni d=D1759DA0FD79ACB96407CDB4B7BC8FA0 Accessed May 27, 2023.”
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ WAME Recommendations on Chatbots and Generative Artificial Intelligence in Relation to Scholarly > WAME Recommendation 2:
“providing in the Methods detailed information about how the study was conducted and the results generated.12”
§ WAME Recommendations on Chatbots and Generative Artificial Intelligence in Relation to Scholarly > References
“12. Non-Author Contributors. Defining the Role of Authors and Contributors. ICMJE. https://www.icmje.org/recommendations/browse/roles-and-responsibilities/defining-the-role-of-authors-and-contributors.html. Accessed May 27, 2023. 13. Methods. Preparing a Manuscript for Submission to a Medical Journal. ICMJE. https://www.icmje.org/recommendations/browse/manuscript-preparation/preparing-for-submission.html#d Accessed May 27, 2023.”
Citations
Cites
A Brief Overview of ChatGPT: The History, Status Quo and Potential Future Development
Wu, T., He, S., Liu, J., Sun, S., Liu, K., Han, Q.-L., & Tang, Y. (2023) · IEEE/CAA Journal of Automatica Sinica · doi:10.1109/jas.2023.123618 · Cited by 1,452
A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications
Gui, J., Sun, Z., Wen, Y., Tao, D., & Ye, J. (2023) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2021.3130191 · Cited by 1,231
A Survey of Unsupervised Generative Models for Exploratory Data Analysis and Representation Learning
Abukmeil, M., Ferrari, S., Genovese, A., Piuri, V., & Scotti, F. (2021) · ACM Computing Surveys · doi:10.1145/3450963 · Cited by 91
Research works printed but not linked: 2
- Methods. Preparing a Manuscript for Submission to a Medical Journal. ICMJE. https://www.icmje.org/recommendations/browse/manuscript-preparation/preparing-for-submission.html#d Accessed May 27, 2023.
- Plagiarism. Oxford Reference, https://www.oxfordreference.com/display/10.1093/oi/authority.20110803100329803;jsessioni d=D1759DA0FD79ACB96407CDB4B7BC8FA0 Accessed May 27, 2023. · DOI
Cited by
Resnik, D. B., & Hosseini, M. (2026) · Accountability in Research · doi:10.1080/08989621.2025.2481949 · Cited by 104
Generative Artificial Intelligence, Human Agency and the Future of Cultural Heritage
Spennemann, D. H. R. (2024) · Heritage · doi:10.3390/heritage7070170 · Cited by 88
Anti-dependency teaching strategy for innovation in the age of AI among technology-based students
Calzada, K. P. D. (2024) · Environment and Social Psychology · doi:10.59429/esp.v9i8.3026 · Cited by 50
The role of ChatGPT in perianesthesia Nursing
Odom-Forren, J. (2023) · Journal of PeriAnesthesia Nursing · doi:10.1016/j.jopan.2023.02.006 · Cited by 26
Hamm, B., Martí‐Bonmatí, L., & Sardanelli, F. (2024) · European Radiology · doi:10.1007/s00330-023-10511-8 · Cited by 13
Hamm, B., Martí‐Bonmatí, L., & Sardanelli, F. (2024) · Insights into Imaging · doi:10.1186/s13244-023-01600-9 · Cited by 10
Matsubara, S. (2024) · International Journal of Gynecology & Obstetrics · doi:10.1002/ijgo.15516 · Cited by 9
Artificial Intelligence: Opportunities and Challenges in Health Professions Education
Mitra, N. K. (2023) · International e-Journal of Science Medicine & Education · doi:10.56026/imu.17.3.2 · Cited by 7
Hamm, B., Martí‐Bonmatí, L., & Sardanelli, F. (2024) · European Radiology Experimental · doi:10.1186/s41747-023-00420-2 · Cited by 6
AI in Scholarly Communications and Academic Research
Tzanova, S. (2024) · Advances in library and information science (ALIS) book series · doi:10.4018/979-8-3693-3053-1.ch002 · Cited by 3
Ng, J. Y., Maduranayagam, S. G., Lokker, C., Iorio, A., Haynes, R. B., & Moher, D. (2023) · medRxiv · doi:10.1101/2023.07.26.23293211 · Cited by 3
Świgoń, M. (2025) · Zagadnienia Informacji Naukowej - Studia Informacyjne · doi:10.36702/zin2024.02.07 · Cited by 2
Generative Artificial Intelligence and Digital Synthetic Outputs
Shafik, W. (2025) · IGI Global eBooks · doi:10.4018/979-8-3373-2277-3.ch009
Ethics, Authorship, and Transparency: Responsible AI Use in Research and Writing
(2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-9340-7.ch004
Writing Systems That Work: Dissertation Momentum, Coauthoring, and AI-Supported Revision
(2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-9340-7.ch012
Literature Discovery and Synthesis With AI: Narrative, Scoping, and Systematic Reviews
(2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-9340-7.ch003
Walking the Middle Path: Problem, Policy, and Adaptation to Generative-AI in Academic Publishing
Kelly, L. C., Istratoaie, A., Dowling, L. J., & Ward, S. A. (2026) · Journal of Bioethical Inquiry · doi:10.1007/s11673-025-10530-8
Metadata
- Authors
- Zielinski, C., Winker, M., Aggarwal, R., Ferris, L., Heinemann, M., Lapeña, J. F., Pai, S., Ing, E., Citrome, L., Alam, M., Voight, M., & Habibzadeh, F.
- ORCID
- Venue
- Philippine Journal of Otolaryngology Head and Neck Surgery
- Published
- 2023-06-04
- Volume
- 38
- Issue
- 1
- Pages
- 7
- ISSN
- 1908-4889 (ISSN-L)
- 2094-1501
- OpenAlex
- W4379473231
- Cited by
- 17
- References
- 3
- Citations by year
- 2026: 4 · 2025: 3 · 2024: 7 · 2023: 3
- FWCI
- 5.32
- Type
- journal article
- Language
- en
- Open access
- diamond
- dx.doi.org
- Licence
- Locations
- Philippine Journal of Otolaryngology Head and Neck Surgery (publishedVersion, cc-by-nc-nd)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Social Sciences › Library and Information Sciences › Publishing and Scholarly Communication
- Social Sciences › Education › Academic integrity and plagiarism
- Social Sciences › Library and Information Sciences › Academic Writing and Publishing
- Keywords
- generative AI, scholarly publishing, AI attribution, journal editorial policy, AI-generated content, AI-generated manuscripts, AI-generated references, AI-generated abstracts, AI-generated data, AI-generated code, AI-generated text, AI-generated images, AI-generated audio, AI-generated video
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-11-13, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-11-13 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.