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Using AI to write scholarly publications
Open accessAbstract
Artificial intelligence (AI) natural language processing (NLP) systems, such as OpenAI's generative pre-trained transformer (GPT) model (https://openai. com) or Meta's Galactica (https://galactica.org/)may soon be widely used in many forms of writing, including scientific and scholarly publications (Heaven 2022). 1 While computer programs (such as Microsoft WORD and Grammarly) have incorporated automated text-editing features (such as checking for spelling and grammar) for many years, these programs are not designed to create content.However, new and emerging NLP systems are, which raises important issues for research ethics and research integrity.2 NLP is a way of enabling computers to interact with human language.A key step in NLP, known as tokenization, involves converting unstructured text into structured text suitable for computation.For example, the sentence "The cat sat on the mat" can be structured by tagging its parts: "the [article] cat [noun] sat [verb, past tense] on [preposition] the [article] mat [noun]."Once the parts of the text have been tagged, they can be processed by means of algorithms designed to produce appropriate responses to text (i.e., language generation).Rudimentary NLP-systems, such as the first generation of chatbots that assisted customers on websites, operated according to thousands of human-written rules for processing and generating text.Recent advances in computational speed and capacity and the development of machine-learning (ML) algorithms, such as neural networks, have led to tremendous breakthroughs in NLP (Mitchell 2020).Today's NLP systems use ML to produce and refine statistical models (with billions of parameters) for processing and generating natural language.NLP systems are trained on huge databases (45 terabytes or more) of text available on the internet or other sources.Initial training (or supervised learning) involves giving the system the text and then "rewarding" it for giving correct outputs, as determined by human trainers.3 Over time, NLP systems will reduce their percentage of erroneous outputs and will learn from the data (Mitchell 2020).While NLP systems continue to learn as they receive and process data beyond their initial training data, they do not "know" the meaning or truth-CONTACT
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“Currently, several journals have attempted to develop guidelines [28, 29].”
From Fighting reviewer fatigue or amplifying bias? Considerations and recommendations for use of ChatGPT and other large language models in scholarly peer review (2023) · cites this paper as [28]
In the citing paper
“A final issue is that AI tools will tend to generate output that reproduces or amplifies biases inherent within the source data [19].”
From Artificial intelligence-assisted academic writing: recommendations for ethical use (2025) · cites this paper as [19]
In the citing paper
“While new models of ChatGPT have ‘learned’ compared to prior releases, they cannot differentiate between real and factitious data that is received, integrated and used to generate new content [19].”
From Artificial intelligence-assisted academic writing: recommendations for ethical use (2025) · cites this paper as [19]
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Citations
Cites
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“Ethical problems related to the misuse of statistics programs and digital image manipulation are well-known and have unfortunately been the subject of numerous research misconduct investigations (Gardenier and Resnik 2002; Rossner and Yamada 2004; Cromey 2013; Shamoo and Resnik 2022).”
Responsible Conduct of Research
Shamoo, A. E., & Resnik, D. B. (2022) · doi:10.1093/oso/9780197547090.001.0001 · Cited by 224
Self-citationAuthorship policies of scientific journals: Table 1
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Self-citationThe Misuse of Statistics: Concepts, Tools, and a Research Agenda
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“Ethical problems related to the misuse of statistics programs and digital image manipulation are well-known and have unfortunately been the subject of numerous research misconduct investigations (Gardenier and Resnik 2002; Rossner and Yamada 2004; Cromey 2013; Shamoo and Resnik 2022).”
Self-citationDigital images are data: and should be treated as such
Cromey, D. W. (2012) · Methods in Molecular Biology · doi:10.1007/978-1-62703-056-4_1 · Cited by 82 · cited 1×
“Ethical problems related to the misuse of statistics programs and digital image manipulation are well-known and have unfortunately been the subject of numerous research misconduct investigations (Gardenier and Resnik 2002; Rossner and Yamada 2004; Cromey 2013; Shamoo and Resnik 2022).”
Limits on risks for healthy volunteers in biomedical research
Resnik, D. B. (2011) · Metamedicine · doi:10.1007/s11017-011-9201-1 · Cited by 63
Self-citationKohl, M. (2015) · The Philosophical Quarterly · doi:10.1093/pq/pqv044 · Cited by 54 · cited 1×
“The OpenAI chatbot gave a completely incorrect answer to this query, because Kant explicitly said that ought implies can (Kohl 2015).”
Evolution and adoption of contributor role ontologies and taxonomies
Hosseini, M., Colomb, J., Holcombe, A. O., Kern, B., Vasilevsky, N., & Holmes, K. (2022) · Learned Publishing · doi:10.1002/leap.1496 · Cited by 16 · cited 1×
“…(Resnik et al. 2016), and widely used contributor roles taxonomies (e.g., CRediT) make clear distinctions between writing the first draft and revising it (Hosseini et al. 2022), use of NLP systems should be acknowledged in the text (e.g., methods section) and mentioned in the references section.”
Self-citation
Research works printed but not linked: 3
- Cell Press. 2022. Cell Press Digital Image Guidelines. Last accessed December 15 2022. https://www.cell.com/figureguidelines.
- International Committee of Medical Journal Editors. (2023). Preparing a Manuscript for Submission to a Medical Journal. Last accessed January 10 2023. https://www.icmje.org/recommendations/browse/manuscript-preparation/preparing-for-submission.html.
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“30 Furthermore, journals explicitly preclude GenAI from being designated as an author, given that AI cannot be held accountable or responsible for the content created.”
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“2 These are more than academic principles, beyond responsibility or transparency for their own sake.”
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“Such breaches may occur due to weakness of will, rationalization, and/or a loss of objectivity (Gorman, 2018; Resnik, 2023).”
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“…críticamente revisada por el equipo de investigación para verificar su precisión, ses-go, relevancia y razonamiento, considerando que esta es una herramienta nueva, que no reemplaza el rol del investigador y el pensamiento científico, y que requiere ser declarada al momento de la publicación 8 .”
BackgroundIntegration and Assessment of ChatGPT in Medical Case Reporting: A Multifaceted Approach
Lin, K.-C., Chen, T.-A., Lin, M.-H., Chen, Y., & Chen, T. (2024) · European Journal of Investigation in Health Psychology and Education · doi:10.3390/ejihpe14040057 · Cited by 3
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Mendoza, K. K. R., Zúñiga, L. H. P., & García, A. Y. L. (2024) · Texto Livre Linguagem e Tecnologia · doi:10.1590/1983-3652.2024.51222 · Cited by 9
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“Notably, it helps in designing interventions for students that can train them to properly and efficiently use AI tools responsibly while wielding them, possibly removing any sense of writing anxiety (Hosseini et al., 2023).”
BackgroundChatGPT in the Context of Scientific Communication
Тихонова, Е. В. (2023) · Хранение и переработка сельхозсырья · doi:10.36107/spfp.2023.518 · Cited by 3
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“This may have several consequences and may alter scientific facts, spread misinformation, and give rise to unethical practices in scholarly communication [2,3,4].”
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Khalil, W., Sheikh, M., & Islam, J. U. (2025) · Cureus · doi:10.7759/cureus.97047 · Cited by 2
“Professional organizations and academic publishers increasingly mandate disclosure of AI involvement, emphasizing that while AI may support content development, it cannot be recognized as a legal author and that human researchers must retain full responsibility for the final work [19].”
Wong, A. K. L., Tsang, K. C. K., Lin, S., & Chan, L. L. (2025) · Education Sciences · doi:10.3390/educsci15121701 · Cited by 3
“2, presents both prospects and hurdles for educators in terms of assessing students’ academic performance (Dehouche, 2021; Hosseini et al., 2023; Williamson et al., 2023).”
AI chatbots and scholarly writing
Mason, T. M., & Blount, M. (2025) · Nursing · doi:10.1097/nsg.0000000000000279 · Cited by 2
On Undisclosed or Improper Use of Generative AI and Sanctions
Pflanzer, M., & Dubljević, V. (2026) · AJOB Neuroscience · doi:10.1080/21507740.2025.2606302 · Cited by 2
“Examples include fabricated (Retraction Watch 2025b) or irrelevant citations (Hosseini et al. 2024), tortured phrases (Holly 2021), explicit LLM language (e.g. “as a large-language model…”) (Academ-AI 2025), the presence of text that is intended to be invisible to human readers but visible to…”
Generative Artificial Intelligence in Academic Research
Arbabi, M. A., Monib, W. K., Abubakari, M. S., & Shafik, W. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-4982-4.ch003 · Cited by 2
Kushnir, I., & Mbah, M. F. (2026) · Sustainability · doi:10.3390/su18083885 · Cited by 2
Uçan, S., & Uçan, A. D. (2026) · Journal of Academic Ethics · doi:10.1007/s10805-026-09739-y · Cited by 5
Is AI-Produced Humanities Scholarship a Case of Research Misconduct?
Metcalf, T. R. (2026) · Journal of Academic Ethics · doi:10.1007/s10805-026-09745-0 · Cited by 3
“But there is almost no ethics literature yet on the question of whether and when the researcher has actually committed any serious research misconduct (Hosseini et al., 2023, 2024 ; Moffatt & Hall, 2025 ; Resnik & Hosseini, 2025).”
Student Ratings: Skin in the Game and the Three-Body Problem
Dziuban, C. D., Moskal, P. D., Reiner, A., Cohen, A., & Carassas, C. (2023) · Education Sciences · doi:10.3390/educsci13111124 · Cited by 2
[Scientific integrity faces plagiarism fabricated with the ChatGPT]
Rivera, H. (2023) · PubMed Central · doi:10.5281/zenodo.10064457 · Cited by 12
Embracing Generative AI in the Classroom Whilst Being Mindful of Academic Integrity
Meakin, L. A. (2024) · Advances in educational marketing, administration, and leadership book series · doi:10.4018/979-8-3693-0240-8.ch004 · Cited by 3
How soon will surgeons become mere technicians? Chatbot performance in managing clinical scenarios
Bryan, D. S., Platz, J. J., Naunheim, K. S., Ferguson, M. K., Abbas, G., Antonoff, M., Ben-Or, S., Demarest, C. T., Finley, D., Cameron, R., et al. (2024) · Journal of Thoracic and Cardiovascular Surgery · doi:10.1016/j.jtcvs.2024.11.006 · Cited by 2
Awareness and Familiarity with AI Writing Tools Among Media Students
Narayan, S. (2024) · LinguaEducare Journal of English and Linguistic Studies · doi:10.63324/lec.1v.1i.5 · Cited by 2
“In the context of higher education, AI writing tools have gained attention for their potential to improve students' academic writing skills and productivity (Hosseini et al., 2023).”
Integrating Large Language Models in Foundational University Courses: A Teaching Reform Approach
Zhang, C., & Premy, T. (2025) · International Conference on Computer Science and Technologies in Education (CSTE) · doi:10.1109/cste64638.2025.11092138 · Cited by 4
Sun, W., Deng, X., Yu, H., Antwi‐Afari, M. F., & Hwang, B. (2025) · Journal of Construction Engineering and Management · doi:10.1061/jcemd4.coeng-17029 · Cited by 2
Editorial: Generative AI, human authorship and the transformation of scholarly communication
Pinochet, L. H. C., Hamza, K. M., & Dwivedi, Y. K. (2026) · Revista de Gestão · doi:10.1108/rege-04-2026-0058 · Cited by 2
Trending Technologies: A Corpus-based Genre Analysis of Abstracts on ChatGPT
Bonsu, E. M., & Adusei, D. K. (2023) · Linguistics Initiative · doi:10.53696/27753719.3283 · Cited by 1
“OpenAI’s Chat Generation Pretrained Transformer (ChatGPT) has 175 billion parameters and is part of a cascade of natural language processing (NLP) models designed to enable computers to interact with human speech (Hosseini et al., 2023).”
BackgroundAI and Higher Education in Developing Country Contexts: About Envisioning Potentiality!
Singh, U. G., & Maistry, S. M. (2024) · Future education and learning spaces · doi:10.1007/978-981-97-6473-0_11 · Cited by 1
Castejón, M. J., Almódovar, A. A. B., Carmo, A. M. D. S., Lopes, G. I. S. L., Catarino, R. M., Pereira, T. C., & Machado, B. C. (2024) · BEPA Boletim Epidemiológico Paulista · doi:10.57148/bepa.2024.v.21.40951 · Cited by 1
Bailey, H. E., Carter‐Templeton, H., Peterson, G. M., Oermann, M. H., & Owens, J. K. (2024) · CIN Computers Informatics Nursing · doi:10.1097/cin.0000000000001237 · Cited by 1
Ethical Aspects of Generative AI in Medicine
Põder, J.-C., & Helgesson, G. (2025) · Integrated science · doi:10.1007/978-3-031-87023-1_12 · Cited by 1
Mustafa, Ş. (2025) · i-manager s Journal on School Educational Technology · doi:10.26634/jsch.20.3.21784 · Cited by 1
Sciuva, J., DeVengencie, I., Fulton, J., Morton, M. A., Chalif, J., Rios‐Doria, E., & Chambers, L. (2025) · Gynecologic Oncology Reports · doi:10.1016/j.gore.2025.101923 · Cited by 1
Kumar, A., & Sangwan, S. R. (2025) · Digital Scholarship in the Humanities · doi:10.1093/llc/fqaf100 · Cited by 1
Knowledge and practices about research integrity among Peruvian university students
Muñoz-del-Carpio-Toia, Á., Guerra-Pérez, H. E., del Carpio, L. B. M., Vargas, L. F. R., Dávila-Del-Carpio, G., Peña-Pinto, Y. M., Calvo, P. D. D. O., Mendoza-Carrera, E., & Valenti, E. (2025) · BMC Medical Ethics · doi:10.1186/s12910-025-01344-9 · Cited by 1
“The inappropriate use of generative artificial intelligence in scientific paper writing could expose students to plagiarism [29, 30].”
Metadata
- Authors
- Hosseini, M., Rasmussen, L. M., & Resnik, D. B.
- Affiliations
- Northwestern University (US)
- University of North Carolina at Charlotte (US)
- National Institute of Environmental Health Sciences (US)
- Corresponding author
- Resnik, David B.
- Venue
- Accountability in Research
- Publisher
- Informa UK Limited
- Published
- 2023-01-25
- Volume
- 31
- Issue
- 7
- Pages
- 715-723
- ISSN
- 0898-9621 (ISSN-L)
- 1545-5815
- PMC
- PMC10366336
- OpenAlex
- W4318035272
- Cited by
- 286
- References
- 10
- Citations by year
- 2026: 56 · 2025: 80 · 2024: 85 · 2023: 65
- FWCI
- 71.56
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Accountability in Research (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institute of Environmental Health Sciences
- National Center for Advancing Translational Sciences (UL1TR001422)
- Topics
- Social Sciences › Education › Academic integrity and plagiarism
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Social Sciences › Library and Information Sciences › Academic Writing and Publishing
- Keywords
- AI-generated text, scholarly publishing, research ethics, research integrity, generative pre-trained transformer, large language models, tokenization, machine learning, chatbots, supervised learning, authorship attribution
- MeSH terms
- Scholarly Communication, Artificial Intelligence, Humans, Periodicals as Topic, Publications, Writing
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.
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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