ScholarGPT's performance in oral and maxillofacial surgery

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dc.authoridBALEL, YUNUS/0000-0003-0496-8564
dc.contributor.authorBalel, Yunus
dc.date.accessioned2025-05-04T16:47:09Z
dc.date.available2025-05-04T16:47:09Z
dc.date.issued2025
dc.departmentSivas Cumhuriyet Üniversitesi
dc.description.abstractObjective: The purpose of this study is to evaluate the performance of Scholar GPT in answering technical questions in the field of oral and maxillofacial surgery and to conduct a comparative analysis with the results of a previous study that assessed the performance of ChatGPT. Materials and Methods: Scholar GPT was accessed via ChatGPT (www.chatgpt.com) on March 20, 2024. A total of 60 technical questions (15 each on impacted teeth, dental implants, temporomandibular joint disorders, and orthognathic surgery) from our previous study were used. Scholar GPT's responses were evaluated using a modified Global Quality Scale (GQS). The questions were randomized before scoring using an online randomizer (www.randomizer.org). A single researcher performed the evaluations at three different times, three weeks apart, with each evaluation preceded by a new randomization. In cases of score discrepancies, a fourth evaluation was conducted to determine the final score. Results: Scholar GPT performed well across all technical questions, with an average GQS score of 4.48 (SD=0.93). Comparatively, ChatGPT's average GQS score in previous study was 3.1 (SD=1.492). The Wilcoxon Signed-Rank Test indicated a statistically significant higher average score for Scholar GPT compared to ChatGPT (Mean Difference = 2.00, SE = 0.163, p < 0.001). The Kruskal-Wallis Test showed no statistically significant differences among the topic groups (x(2) = 0.799, df= 3, p = 0.850, epsilon(2) = 0.0135). Conclusion: Scholar GPT demonstrated a generally high performance in technical questions within oral and maxillofacial surgery and produced more consistent and higher-quality responses compared to ChatGPT. The findings suggest that GPT models based on academic databases can provide more accurate and reliable information. Additionally, developing a specialized GPT model for oral and maxillofacial surgery could ensure higher quality and consistency in artificial intelligence-generated information. (c) 2024 Elsevier Masson SAS. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
dc.identifier.doi10.1016/j.jormas.2024.102114
dc.identifier.issn2468-8509
dc.identifier.issn2468-7855
dc.identifier.issue4
dc.identifier.pmid39389541
dc.identifier.scopus2-s2.0-85206110398
dc.identifier.scopusqualityQ2
dc.identifier.urihttps://doi.org/10.1016/j.jormas.2024.102114
dc.identifier.urihttps://hdl.handle.net/20.500.12418/35505
dc.identifier.volume126
dc.identifier.wosWOS:001376817400001
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.institutionauthorBalel, Yunus
dc.language.isoen
dc.publisherElsevier
dc.relation.ispartofJournal of Stomatology Oral and Maxillofacial Surgery
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WOS_20250504
dc.subjectArtificial intelligence
dc.subjectGPT
dc.subjectQuality
dc.titleScholarGPT's performance in oral and maxillofacial surgery
dc.typeArticle

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