\begin{table*}[htp]
\resizebox{\textwidth}{!}{
\begin{tabular}{lrrrrrr}
\toprule
Model/adapter & EM & # eval & # train & truncated & # prompt tokens & # output tokens \\
\midrule
BioMistral (7B) & 0.6226415094339622 & 265.0 &  &  & 88.17358490566038 & 1.0 \\
Meditron (7B) & 0.3283018867924528 & 265.0 &  &  & 90.37358490566038 & 1.0 \\
Llama 2 (7B) & 0.44528301886792454 & 265.0 &  &  & 90.37358490566038 & 1.0 \\
Llama 3 (70B) & 0.8301886792452831 & 265.0 &  &  & 73.92830188679245 & 1.0 \\
Mistral Instruct v0.1 (7B) & 0.5924528301886792 & 265.0 &  &  & 88.17358490566038 & 1.0 \\
Mixtral (8x22B) & 0.7811320754716982 & 265.0 &  &  & 88.17358490566038 & 1.0 \\
Claude 3 Haiku (20240307) & 0.7886792452830189 & 265.0 &  &  & 88.4566037735849 & 1.0 \\
Claude 3 Sonnet (20240229) & 0.7886792452830189 & 265.0 &  &  & 88.4566037735849 & 1.0 \\
Claude 3 Opus (20240229) & 0.8754716981132076 & 265.0 &  &  & 88.4566037735849 & 1.0 \\
Gemini 1.5 Pro (0409 preview) & 0.026415094339622643 & 265.0 &  &  & 76.59245283018868 &  \\
PaLM-2 (Bison) & 0.7283018867924528 & 265.0 &  &  & 76.59245283018868 &  \\
PaLM-2 (Unicorn) & 0.8037735849056604 & 265.0 &  &  & 77.76981132075471 &  \\
MedLM (Medium) & 0.7433962264150943 & 265.0 &  &  & 77.76981132075471 &  \\
MedLM (Large) & 0.8301886792452831 & 265.0 &  &  & 77.76981132075471 &  \\
GPT-3.5 Turbo (0125) & 0.7471698113207547 & 265.0 &  &  & 73.94716981132075 & 1.0 \\
GPT-4 Turbo (2024-04-09) & 0.8264150943396227 & 265.0 &  &  & 73.94716981132075 & 1.0 \\
GPT-4o (2024-05-13) & 0.7849056603773585 & 265.0 &  &  & 72.98490566037736 & 1.0 \\
\bottomrule
\end{tabular}}
\caption{Results for mmlu_subject:clinical_knowledge (mmlu)}
\label{fig:mmlu_subject:clinical_knowledge (mmlu)}
\end{table*}