GPT-4's performance on dental licensing examinations does not differ significantly between English-speaking and non-English-speaking countries¶

Claim · All claims
Evidence · 1 study · quant-synthesis r2 · q3
Currency · newest study 2025 · not yet checked against its sources · not reviewed by a person · recheck by 2028: tool and model accuracy changes quickly

Subclaims¶

q3 i? GPT-4 achieved 73% accuracy in both English-speaking and non-English-speaking countries' dental examinations, with no significant difference (P = .97). → Liu Mingxin 2025

Evidence¶

Liu Mingxin 2025¶

Liu Mingxin, Okuhara Tsuyoshi, Huang Wenbo, Ogihara Atsushi, Nagao Hikari Sophia, Okada Hiroko, Kiuchi Takahiro. (2025). Large Language Models in Dental Licensing Examinations: Systematic Review and Meta-Analysis. International Dental Journal. https://doi.org/10.1016/j.identj.2024.10.014

q3 · i? · quant-synthesis · r2

Subgroup analysis of GPT-4 performance by examination origin country. The review reports "No significant difference was observed (P = .97)" between the two subgroups.

"The integrate accuracy rate of GPT-4 in non-English-speaking countries' dental examinations was 73% (95% CI: 68%-78%), and in English-speaking countries' dental examinations, it was also 73% (95% CI: 68%-78%). No significant difference was observed (P = .97)"

Discussion¶

Related Claims¶

• GPT-3.5 achieves an integrated accuracy of 54% on dental licensing examinations — related
• GPT-3.5 performs significantly better on dental licensing examinations from English-speaking countries than non-English-speaking countries — related
• GPT-4 outperforms GPT-3.5 and Bard on dental licensing examinations, achieving an integrated accuracy of 72% — related
• GPT-4 performed significantly better on examinations from English-speaking countries (86% vs 80%, P=.02), while GPT-3.5 showed no such difference (P=.72) — reports the opposite