Evidence map›Paper›PMID 39879415›Full record

ArticleArquivos brasileiros de oftalmologia2025

ChatGPT applications in academic writing: a review of potential, limitations, and ethical challenges.

Yuanyuan Liu, Wenting Kong, Kaygac Merve

Abstract readScoping Review
In one paragraph

Article in Arquivos brasileiros de oftalmologia, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Yuanyuan LiuSchool of Foreign Studies, China University of Petroleum (East China), Qingdao, Shandong, China.ORCID 0000-0002-6463-6476
Wenting KongSchool of Foreign Studies, China University of Petroleum (East China), Qingdao, Shandong, China.ORCID 0009-0009-7521-9553
Kaygac MerveSchool of International Education, China University of Petroleum (East China), Qingdao, Shandong, China.ORCID 0009-0008-5623-4427

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This article systematically reviewed 327 documents in the core collection of the Web of Science database regarding ChatGPT applications in the writing domain. This study aimed to comprehensively assess the latest progress and potential applications. ChatGPT demonstrates significant potential in overcoming writing anxiety, improving writing efficiency, generating initial scientific papers, and assisting researchers and students in giving feedback. However, it still faces significant challenges in data accuracy and the ethics of generated content, including inaccurate or outdated information, plagiarism risks, gender or race biases, etc. Authorship verification is particularly important for academic writing and publishing as it relates to objectivity, accuracy, and fairness. Future studies need to explore how to address these challenges through improvements at the technical and policy levels, ensuring that ChatGPT promotes the sustainable development and application of academic writing while adhering to ethical standards.

Indexed as

Generative Artificial IntelligencePublishingWritingAuthorshipHumansPlagiarism

Identifiers

PMID39879415
PMCPMC12997649

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.