## 3 Results  
The accuracy and completeness scores, along with the response times of ChatGPT-4o, Deepseek, Gemini Advanced, and Claude 3.7 in answering the 25 questions on TDIs in primary dentition, are summarized in Table 3. Statistically significant differences were observed in the accuracy scores among the four chatbots (\(p\) = 0.005). Post hoc analysis indicated that ChatGPT-4o (4.74 \(\pm\) 0.66) achieved significantly higher accuracy scores than Gemini Advanced (4.3 \(\pm\) 1.01). Similarly, statistically significant differences were found in the completeness scores (\(p\) = 0.010), with DeepSeek (2.78 \(\pm\) 0.46) scoring significantly higher than Gemini Advanced (2.56 \(\pm\) 0.57). Significant variation was also observed in response times across the models (\(p\) < 0.001). DeepSeek (69 \(\pm\) 21 s) had the longest response time, while ChatGPT-4o (9.37 \(\pm\) 3.78 s) and Gemini Advanced (7.32 \(\pm\) 2.43 s) generated the fastest responses. Figure 2 presents the accuracy scores of the four AI models, Figure 3 displays their completeness scores, and Figure 4 illustrates their response times. \begin{table}
\begin{tabular}{l l l l l l l} \hline \hline  & & \multicolumn{4}{c}{**Chatbot**} \\  & & **ChatGPT-4 Omni** & **DeepSeek** & **Gemini Advanced** & **Claude 3.7** & \(p\)**-Value *** \\ \hline \multirow{2}{*}{**Accuracy**} & Mean \(\pm\) SD & 4.74 \(\pm\) 0.66 \({}^{\text{a}}\) & 4.42 \(\pm\) 0.92 \({}^{\text{ab}}\) & 4.3 \(\pm\) 1.01 \({}^{\text{b}}\) & 4.44 \(\pm\) 0.97 \({}^{\text{ab}}\) & **0.005** \\  & Median (min.\(-\)max.) & 5 (2–5) & 5 (2–5) & 5 (1–5) & 5 (1–5) & **0.005** \\ \hline \multirow{2}{*}{**Completeness**} & Mean \(\pm\) SD & 2.74 \(\pm\) 0.44 \({}^{\text{ab}}\) & 2.78 \(\pm\) 0.46 \({}^{\text{a}}\) & 2.56 \(\pm\) 0.57 \({}^{\text{b}}\) & 2.74 \(\pm\) 0.52 \({}^{\text{ab}}\) & **0.010** \\  & Median (min.\(-\)max.) & 3 (2–3) & 3 (1–3) & 3 (1–3) & 3 (1–3) & **0.010** \\ \hline \multirow{2}{*}{**Response Time**} & Mean \(\pm\) SD & 9.37 \(\pm\) 3.78 \({}^{\text{a}}\) & 69 \(\pm\) 21 \({}^{\text{b}}\) & 7.32 \(\pm\) 2.43 \({}^{\text{a}}\) & 14.11 \(\pm\) 4.22 \({}^{\text{c}}\) & **0.001** \\  & Median (min.\(-\)max.) & 8.87 (4.7–23.32) & 63.61 (43.55–128) & 7.15 (3.56–13.53) & 12.53 (8.56–25.03) & **<0.001** \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Comparison of accuracy and completeness scores and response time for ChatGPT-4 Omni, DeepSeek, Gemini Advanced, and Claude 3.7 in answering traumatic dental injuries in primary dentition questions. In addition to statistical significance, effect sizes were calculated using eta-squared (\(\eta^{2}\)) to quantify the magnitude of between-group differences. The \(\eta^{2}\) values for accuracy (0.032) and completeness (0.028) were small, while the response time dimension demonstrated a very large effect (\(\eta^{2}\) = 0.846), underscoring substantial variation in processing latency across chatbot models. These results provide not only statistically significant but also practically meaningful distinctions among the evaluated models. Figure 3: Mean completeness scores of ChatGPT-4o, DeepSeek, Gemini Advanced, and Claude 3.7 in responding to questions related to traumatic dental injuries in primary dentition. Figure 2: Mean accuracy scores of ChatGPT-4o, DeepSeek, Gemini Advanced, and Claude 3.7 in responding to questions related to traumatic dental injuries in primary dentition. The readability scores of the four chatbots, based on various readability assessment criteria, are presented in Table 4. According to the FRES, Deepseek (41) achieved the highest median score, while Claude 3.7 (4.5) recorded the lowest, with a statistically significant difference (_p_ < 0.001). In terms of the FKGL, Claude 3.7 (19.8) demonstrated a significantly higher median grade level, whereas DeepSeek (11.1) had the lowest (_p_ < 0.001). For the GFI and SMOG Index, Claude 3.7 also produced significantly higher median scores than the other chatbots (24 and 18.5, respectively) (_p_ < 0.001).