Evidence map›Paper›PMID 41980745›Full record

ArticleThe Angle orthodontist2026

Comparative evaluation of ChatGPT and Gemini artificial intelligence in patient education on clear aligner therapy.

Merve Kurnaz, Tuba Tortop, Hilal Kan, Gökhan Ocakoğlu, Emine Kaygısız

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Article in The Angle orthodontist, 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

5 authors.

Merve Kurnaz
Tuba Tortop
Hilal Kan
Gökhan Ocakoğlu
Emine Kaygısız

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: To compare the performance of ChatGPT-4 Turbo and Gemini 1.5 Pro in the domain of Clear Aligner Therapy (CAT). Materials and Methods: A total of 36 standardized questions on CAT were created based on consent forms from aligner companies and frequently asked patient questions. Responses were generated by ChatGPT-4 Turbo and Gemini 1.5 Pro. A reference answer key was developed from current literature. Two orthodontic professors independently evaluated the responses using a six-point accuracy scale and a three-point completeness scale. Questions were also categorized by topic. Readability was assessed using Flesch-Kincaid Grade Level (FKGL) and Simplified Measure of Gobbledygook (SMOG) scores. Independent samples t-tests were used to compare readability, whereas the Mann-Whitney U test was used for accuracy and completeness. Interrater reliability was assessed with intraclass correlation coefficient (ICC). Significance was set at P < .05. Results: Interrater reliability was high for both models. ChatGPT showed excellent agreement for accuracy (ICC = 0.91) and good for completeness (ICC = 0.89). Gemini also showed excellent accuracy (ICC = 0.93) and moderate-to-good completeness (ICC = 0.78). No significant differences were found between models in accuracy, completeness, or readability. Both produced content with FKGL scores indicating university-level reading and SMOG scores suggesting high school-level comprehension. Conclusions: The readability of the content may present challenges for general audiences due to its complexity. The models used in this study may assist in patient education; however, the results implied the importance of professional consultation and careful interpretation of artificial intelligence-generated information.

Indexed as

Clear aligner therapyLarge language modelsPatient educationReadabilityTreatment accuracy

Identifiers

PMID41980745

What OpenQuestion holds

Textmetadata
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Registered trials

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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.