Evidence map›Paper›PMID 41182423›Full record

ArticleDie Naturwissenschaften2025

AI misuse of retracted literature: A comparative study of ChatGPT4o, deepseek, and grok 3 in stem cell research.

Lan Yao, Tianshu Gu, Xuexin Li, Yan Jiao, Minghui Li, J Carolyn Graff, Yulan Li, Weikuan Gu

Abstract readComparative Study
In one paragraph

Article in Die Naturwissenschaften, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Lan Yao *College of Health Management, Harbin Medical University, Heilongjiang. 157 Baojian Road, Harbin, 150081, Heilongjiang, China.
Tianshu Gu *Department of Clinical Pharmacy and Translational Science, University of Tennessee Health Science Center, Memphis, TN, 38103, USA.
Xuexin LiDepartment of Biostatistics, Vanderbilt University, 2525 West End Ave. Ste 1100, Nashville, TN, 37203, USA.
Yan JiaoDepartment of Orthopedic Surgery and BME-Campbell Clinic, University of Tennessee Health Science Centre, Memphis, TN, 38163, USA.
Minghui LiDepartment of Clinical Pharmacy and Translational Science, University of Tennessee Health Science Center, Memphis, TN, 38103, USA.
J Carolyn GraffCollege of Nursing, University of Tennessee Health Science Center, Memphis, TN, 38163, USA.
Yulan LiThe Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Weikuan GuDepartment of Orthopedic Surgery and BME-Campbell Clinic, University of Tennessee Health Science Centre, Memphis, TN, 38163, USA. wgu@uthsc.edu.

Funding

Health Science Center, University of Tennessee R073290153
6 · The paper itself

Abstract

DeepSeek and Grok 3 appear as strong competitors to AI models, particularly the widely accepted model, ChatGPT. The accuracy of the utilization of data in retracted scientific articles has proven to be a significant challenge for AI as an assistant in scientific research. It is critical to understand whether and how three AI models handle information from retracted articles when they answer scientific questions. We collected retracted articles and used AI models to generate questions and analyzed the answers. The answers were compared and evaluated among three AI models. Here we show that these three models utilized 84 out of 93 retracted articles in their answers about stem cells. ChatGPT4o retrieved 74 out of 93 (80%) articles and recognized the retract status for 46 (62%) of them. DeepSeek only found one retracted article and did not realize its retraction status. Grok 4 retrieved 69 (74%) articles and recognized the retraction status of 46 (67%) of them. In cases when the retracted articles were not identified, ChatGPT fabricated articles 5 times out of 19 (26%) for its answers. Grok 3 fabricated 15 articles out of 24 (63%) for its answers. In 82 times of 93 (88%) answers, DeepSeek fabricated the articles in various forms. The answering styles from ChatGPT4o, DeepSeek, and Grok 3 are characterized by accurate and straightforward, a tangential structure and guesswork, and comprehensive and detailed answers, respectively. Analysis with non-retracted articles revealed the similar patterns of these models. This study suggests that, while no model is perfect, DeepSeek performed the worst when facing in-depth scientific real-world challenges. Much improvement has to be made before any of these AI models become problem-free and valuable for scientists.

Indexed as

Retraction of Publication as TopicStem Cell ResearchHumansAIArticleCellChatGPTDeepSeekGrok3PublicationRetractionStem

Identifiers

PMID41182423
PMCPMC12583397

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.