ArticleJournal of pharmaceutical policy and practice2024
Detecting manuscripts written by generative AI and AI-assisted technologies in the field of pharmacy practice.
Article in Journal of pharmaceutical policy and practice, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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.
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.
Who cites it
5 citing papers in PubMed, 10 citations in OpenAlex.
- Recommendations for disclosure of artificial intelligence in scientific writing and publishing: a regional anesthesia and pain medicine modified Delphi study.Regional anesthesia and pain medicine · 2026Article
- Evaluation of ChatGPT-5-generated surgical literature: the accuracy of a review on penile prosthesis implantation.International journal of impotence research · 2026Article
- Article
- Survey of Guidance for Authors on the Use of Generative Artificial Intelligence in Pharmaceutical Journals.The Canadian journal of hospital pharmacy · 2026Article
- Exploring Jordanian medical students' perceptions and concerns about ChatGPT in medical education: a cross-sectional study.Journal of pharmaceutical policy and practice · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 6 institutions in 5 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Generative AI can be a powerful research tool, but researchers must employ it ethically and transparently. This commentary addresses how the editors of pharmacy practice journals can identify manuscripts generated by generative AI and AI-assisted technologies. Editors and reviewers must stay well-informed about developments in AI technologies to effectively recognise AI-written papers. Editors should safeguard the reliability of journal publishing and sustain industry standards for pharmacy practice by implementing the crucial strategies outlined in this editorial. Although obstacles, including ignorance, time constraints, and protean AI strategies, might hinder detection efforts, several facilitators can help overcome those obstacles. Pharmacy practice journal editors and reviewers would benefit from educational programmes, collaborations with AI experts, and sophisticated plagiarism-detection techniques geared toward accurately identifying AI-generated text. Academics and practitioners can further uphold the integrity of published research through transparent reporting and ethical standards. Pharmacy practice journal staffs can sustain academic rigour and guarantee the validity of scholarly work by recognising and addressing the relevant barriers and utilising the proper enablers. Navigating the changing world of AI-generated content and preserving standards of excellence in pharmaceutical research and practice requires a proactive strategy of constant learning and community participation.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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 OpenQuestion graph.