ReviewKorean journal of radiology2023
Is ChatGPT a "Fire of Prometheus" for Non-Native English-Speaking Researchers in Academic Writing?
Review in Korean journal of radiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 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
32 citing papers in PubMed, 93 citations in OpenAlex.
- Is Vibe Coding a 'Fire of Prometheus' for Non-Developer Clinicians, Especially Clinical Radiologists?Korean journal of radiology · 2026Review
- Generative Artificial Intelligence for Empowering Non-Native English Speakers in Verbal Scientific Communication and Dissemination.Korean journal of radiology · 2026Article
- Fabricated citations in the age of AI: A wake-up call for editors, reviewers, and authors.Journal of dental sciences · 2026Article
- Does ChatGPT enhance equity for global health publications? Copyediting by ChatGPT compared to Grammarly and a human editor.PloS one · 2026Article
- Perceptions of Japanese Medical Trainees and Physicians About Writing Case Reports: A Questionnaire-Based Survey.Cureus · 2025Article
- How Can We Make Scientific Events More Inclusive? Insights From Q&A Sessions and Surveys From an International Conference.Ecology and evolution · 2025Article
- A Review of the Opportunities and Challenges with Large Language Models in Radiology: The Road Ahead.AJNR. American journal of neuroradiology · 2025Review
- Techniques for supercharging academic writing with generative AI.Nature biomedical engineering · 2025Article
- Artificial Intelligence-Generated Editorials in Radiology: Can Expert Editors Detect Them?AJNR. American journal of neuroradiology · 2025Article
- Article
- Generative artificial intelligence (GAI) usage guidelines for scholarly publishing: a cross-sectional study of medical journals.BMC medicine · 2025Article
- Three versions of an atopic dermatitis case report written by humans, artificial intelligence, or both: Identification of authorship and preferences.The journal of allergy and clinical immunology. Global · 2025Article
- A manifesto for a globally diverse, equitable, and inclusive open science.Communications psychology · 2025Review
- Non-native speakers of English or ChatGPT: Who thinks better?F1000Research · 2025Article
- Navigating cognitive dissonance: master's students' experiences with ChatGPT in dissertation writing.Frontiers in psychology · 2025Article
- Delving Into PubMed Records: How AI-Influenced Vocabulary has Transformed Medical Writing since ChatGPT.Perspectives on medical education · 2025Article
- Conceptual review of outcome metrics and measures used in clinical evaluation of artificial intelligence in radiology.La Radiologia medica · 2024Review
- Testing the capacity of Bard and ChatGPT for writing essays on ethical dilemmas: A cross-sectional study.Scientific reports · 2024Article
- The performance of OpenAI ChatGPT-4 and Google Gemini in virology multiple-choice questions: a comparative analysis of English and Arabic responses.BMC research notes · 2024Article
- [Large Language Models: A Comprehensive Guide for Radiologists].Journal of the Korean Society of Radiology · 2024Review
Corrections and comments
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Authors and funding
7 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Large language models (LLMs) such as ChatGPT have garnered considerable interest for their potential to aid non-native English-speaking researchers. These models can function as personal, round-the-clock English tutors, akin to how Prometheus in Greek mythology bestowed fire upon humans for their advancement. LLMs can be particularly helpful for non-native researchers in writing the Introduction and Discussion sections of manuscripts, where they often encounter challenges. However, using LLMs to generate text for research manuscripts entails concerns such as hallucination, plagiarism, and privacy issues; to mitigate these risks, authors should verify the accuracy of generated content, employ text similarity detectors, and avoid inputting sensitive information into their prompts. Consequently, it may be more prudent to utilize LLMs for editing and refining text rather than generating large portions of text. Journal policies concerning the use of LLMs vary, but transparency in disclosing artificial intelligence tool usage is emphasized. This paper aims to summarize how LLMs can lower the barrier to academic writing in English, enabling researchers to concentrate on domain-specific research, provided they are used responsibly and cautiously.
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.