Evidence map›Paper›PMID 41572856›Full record

ArticleKorean journal of orthodontics2026

Comparative evaluation of ChatGPT, Gemini, and Grok in clinical decision-making and general knowledge assessment for impacted maxillary canines.

Genta Agani Sabah, Mehmet Gümüş Kanmaz

Abstract read
In one paragraph

Article in Korean journal of orthodontics, 2026. 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

2 authors.

Genta Agani SabahDepartment of Orthodontics, Izmir Tinaztepe University, Izmir, Türkiye.ORCID https://orcid.org/0000-0002-7571-6922
Mehmet Gümüş KanmazDepartment of Periodontology, Izmir Tinaztepe University, Izmir, Türkiye.ORCID https://orcid.org/0000-0002-9261-7854

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study aimed to compare extraction versus orthodontic eruption decisions for impacted maxillary canines made by three artificial intelligence-based chatbots (ChatGPT, Gemini, and Grok) with those made by orthodontist raters, and to evaluate the overall accuracy of these artificial intelligence-generated recommendations. Methods: Thirty-three patients with impacted maxillary canines were selected, and standardized case scenarios incorporating key diagnostic parameters were presented to the three chatbots. Their treatment decisions were recorded and compared with orthodontists' consensus decisions. Additionally, 10 general queries regarding impacted maxillary canines were submitted to the chatbots. The responses were rated by three orthodontists using a modified 5-point Global Quality Score. Results: The chatbots and orthodontists showed moderate agreement regarding treatment decisions (κ = 0.411-0.524, Conclusions: While Gemini showed lower clinical alignment with orthodontists for treatment decisions regarding impacted canines, ChatGPT and Grok demonstrated moderate agreement with orthodontists and produced relatively accurate responses. These findings highlight the potential of chatbots as supportive tools for orthodontic decision-making. However, their use requires careful supervision to avoid the risks associated with inaccurate or misleading recommendations.

Indexed as

Artificial intelligenceClinical decision-makingImpacted maxillary canineLarge language models

Identifiers

PMID41572856
PMCPMC12849713

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.