ArticleAdvanced pharmaceutical bulletin2024
Diagnosis Unreliability of ChatGPT for Journal Evaluation.
Article in Advanced pharmaceutical bulletin, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed.
- Knowledge, practices, and perception of predatory journals among North-African Dental University Hospital Doctors.BMC medical education · 2026Article
- How To Cope With Predatory Journals.Journal of Korean medical science · 2025Review
- A Decade in Hijacked Journals: What Will be the Future Trend?Advanced pharmaceutical bulletin · 2024Article
- Unveiling the Hidden Menace: A Topic Modeling Analysis of Hijacked Medical Journals.Advanced pharmaceutical bulletin · 2024Article
- Evaluating human resources management literacy: A performance analysis of ChatGPT and bard.Heliyon · 2024Article
- ChatGPT's Inconsistency in the Diagnosis of Alzheimer's Disease.Journal of Alzheimer's disease reports · 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
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: Academic and other researchers have limited tools with which to address the current proliferation of predatory and hijacked journals. These journals can have negative effects on science, research funding, and the dissemination of information. As most predatory and hijacked journals are not error free, this study used ChatGPT, an artificial intelligence (AI) technology tool, to conduct an evaluation of journal quality. Methods: Predatory and hijacked journals were analyzed for reliability using ChatGPT, and the reliability of result have been discussed. Results: It shows that ChatGPT is an unreliable tool for journal quality evaluation for both hijacked and predatory journals. Conclusion: To show how to address this gap, an early trial version of Journal Checker Chatbot has been developed and is discussed as an alternative chatbot that can assist researchers in detecting hijacked journals.
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.