ArticleFrontiers in artificial intelligence2025
AI for scientific integrity: detecting ethical breaches, errors, and misconduct in manuscripts.
Article in Frontiers in artificial intelligence, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 10 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
10 citing papers in PubMed.
- Biomedical Research Images Manipulated by Generative AI to Alter Scientific Outcomes: Diagnostic Study of Human and Automated Detection.Journal of medical Internet research · 2026Article
- A large language model pipeline for automated citation quality scoring across engineering journal quartiles with expert validation.Scientific reports · 2026Article
- The impact of risk perception on perceived benefits of generative artificial intelligence users-an empirical study based on university students.Frontiers in psychology · 2026Article
- [How to detect scientific texts generated with artificial intelligence?]Revista medica del Instituto Mexicano del Seguro Social · 2026Article
- Systems biology in the era of AI: "winter" or "evolution"?Frontiers in systems biology · 2026Article
- Safeguarding Quality in Health and Medical Science Information Today.Patient related outcome measures · 2026Article
- Artificial intelligence (AI) in academic publishing: Legitimate use, plagiarism detection, and ethical challenges.Iranian journal of basic medical sciences · 2026Article
- Scientific Publishing in the era of Artificial Intelligence: Integrity and Responsibility.Arquivos brasileiros de cardiologia · 2026Article
- Artificial Intelligence in Detecting Statistical Errors: Implications for Authors, Reviewers, and Editors.Journal of Korean medical science · 2025Review
- Ten simple rules for optimal and careful use of generative AI in science.PLoS computational biology · 2025Article
Corrections and comments
- Erratum issued
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The use of Generative AI (GenAI) in scientific writing has grown rapidly, offering tools for manuscript drafting, literature summarization, and data analysis. However, these benefits are accompanied by risks, including undisclosed AI authorship, manipulated content, and the emergence of papermills. This perspective examines two key strategies for maintaining research integrity in the GenAI era: (1) detecting unethical or inappropriate use of GenAI in scientific manuscripts and (2) using AI tools to identify mistakes in scientific literature, such as statistical errors, image manipulation, and incorrect citations. We reviewed the capabilities and limitations of existing AI detectors designed to differentiate human-written (HWT) from machine-generated text (MGT), highlighting performance gaps, genre sensitivity, and vulnerability to adversarial attacks. We also investigate emerging AI-powered systems aimed at identifying errors in published research, including tools for statistical verification, citation validation, and image manipulation detection. Additionally, we discuss recent publishing industry initiatives to AI-driven papermills. Our investigation shows that these developments are not yet sufficiently accurate or reliable yet for use in academic assessment, they mark an early but promising steps toward scalable, AI-assisted quality control in scholarly publishing.
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.