## 3 Results
### Analysis of Answers Divided by Question Category  
Table 3 provides a detailed breakdown of the average accuracy and completeness scores for Bard and ChatGPT-4+context, categorized by the topic of the question. ChatGPT-4+context consistently achieved higher scores for both accuracy and completeness in the subcategories of asbestos, explosive atmospheres, work equipment and PPE, \"interpelli\", common principles, biological hazards, and the use of visual display terminals. However, Bard outperformed ChatGPT-4+context in the subcategories of manual handling of loads and physical hazards. For the chemical hazards, ChatGPT-4+context was superior in accuracy but not in completeness, where Bard performed better.  
\begin{table}
\begin{tabular}{c c c} \hline \hline  & **Google Bard vs. ChatGPT-4+Context** \\ \hline
**Metric** & **Values** & \(p\)**-Value** \\ \hline Completeness & 3.47 vs. 3.68 & \textless{}0.05 \\ \hline Accuracy & 3.14 vs. 3.67 & \textless{}0.05 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Mean score of accuracy and completeness obtained for ChatGPT-4+context and Bard.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Topic** & **Metrics** & **LLM** & **Average** & \begin{tabular}{c} **Standard** \\ **Deviation** \\ \end{tabular} & \(p\)**-Value** \\ \hline \multirow{4}{*}{Asbestos} & \multirow{2}{*}{Accuracy} & \begin{tabular}{c} Bard \\ \end{tabular} & 2.81 & 1.347 & \multirow{2}{*}{\(p=0.017\)\({}^{*}\)} \\ \cline{3-3} \cline{5-6}  & & GPT-4 & 3.44 & 1.287 & \\ \cline{2-6}  & \multirow{2}{*}{Completeness} & \begin{tabular}{c} Bard \\ \end{tabular} & 3.17 & 1.404 & \multirow{2}{*}{\(p=0.239\)} \\ \cline{3-3} \cline{5-6}  & & GPT-4 & 3.50 & 1.353 & \\ \hline \multirow{4}{*}{Risk of Explosive} & \multirow{2}{*}{Accuracy} & \begin{tabular}{c} Bard \\ \end{tabular} & 2.86 & 1.216 & \multirow{2}{*}{\(p=0.38\)} \\ \cline{3-3} \cline{5-6}  & & GPT-4 & 3.51 & 1.483 & \\ \cline{2-6}  & \multirow{2}{*}{Completeness} & \begin{tabular}{c} Bard \\ \end{tabular} & 3.03 & 1.150 & \multirow{2}{*}{\(p=0.083\)} \\ \cline{3-3} \cline{5-6}  & & GPT-4 & 3.49 & 1.401 & \\ \hline \multirow{4}{*}{Work Equipment} & \multirow{2}{*}{Accuracy} & \begin{tabular}{c} Bard \\ \end{tabular} & 2.61 & 1.443 & \multirow{2}{*}{\(p=0.00\)\({}^{*}\)} \\ \cline{3-3} \cline{5-6}  & & GPT-4 & 4.03 & 1.150 & \\ \cline{3-3} \cline{5-6}  & \multirow{2}{*}{Completeness} & \begin{tabular}{c} Bard \\ \end{tabular} & 3.21 & 1.234 & \multirow{2}{*}{\(p=0.05\)} \\ \cline{3-3} \cline{5-6}  & & GPT-4 & 4.00 & 0.986 & \\ \hline \multirow{4}{*}{\begin{tabular}{c} \"Interpelli\" \\ \end{tabular} } & \multirow{2}{*}{Accuracy} & \begin{tabular}{c} Bard \\ \end{tabular} & 3.17 & 1.342 & \multirow{2}{*}{\(p=0.00\)\({}^{*}\)} \\ \cline{3-3} \cline{5-6}  & & GPT-4 & 3.92 & 1.161 & \\ \cline{3-3} \cline{5-6}  & \multirow{2}{*}{Completeness} & \begin{tabular}{c} Bard \\ \end{tabular} & 3.49 & 1.302 & \multirow{2}{*}{\(p=0.00\)\({}^{*}\)} \\ \cline{3-3} \cline{5-6}  & & GPT-4 & 3.95 & 1.057 & \\ \hline \multirow{4}{*}{\begin{tabular}{c} Manual \\ Handling of \\ Loads \\ \end{tabular} } & \multirow{2}{*}{Accuracy} & \
\begin{tabular}{c} Bard \\ \end{tabular} & 3.35 & 1.232 & \multirow{2}{*}{\(p=0.695\)} \\ \cline{3-3} \cline{5-6}  & & GPT-4 & 3.25 & 1.284 & \\ \cline{3-3} \cline{5-6}  & \multirow{2}{*}{Completeness} &
\begin{tabular}{c} [PERSON] \\ \end{tabular} & 3.70 & 1.188 & \multirow{2}{*}{\(p=0.009\)\({}^{*}\)} \\ \cline{3-3} \cline{5-6}  & & GPT-4 & 3.20 & 1.191 & \\ \hline \hline \end{tabular}
\end{table}
Table 3: Mean, standard deviation (SD), and statistical significance (\({}^{*}\)) of the accuracy and completeness scores of the responses from the two chatbots based on the question topic. In the table, ChatGPT-4+context has been abbreviated as GPT-4.  
Figure 2: Median (red line), 25 th (green line) and 75 th percentiles (blue line) for the accuracy and completeness of the responses from and Bard and ChatGPT-4+context.