\begin{table*}[htp]
\resizebox{\textwidth}{!}{
\begin{tabular}{lrrrrrr}
\toprule
Model/adapter & Judge Score & # eval & # train & truncated & # prompt tokens & # output tokens \\
\midrule
BioMistral (7B) & 0.5519230769230773 & 104.0 &  &  & 31.653846153846153 & 76.96153846153847 \\
Meditron (7B) & 0.42788461538461536 & 104.0 &  &  & 31.58653846153846 & 74.45192307692308 \\
Llama 2 (7B) & 0.223076923076923 & 104.0 &  &  & 31.58653846153846 & 1.0 \\
Llama 3 (70B) & 0.5432692307692311 & 104.0 &  &  & 25.73076923076923 & 1.0 \\
Mistral Instruct v0.1 (7B) & 0.5788461538461541 & 104.0 &  &  & 31.653846153846153 & 89.0673076923077 \\
Mixtral (8x22B) & 0.3519230769230769 & 104.0 &  &  & 31.653846153846153 & 1.0 \\
Claude 3 Haiku (20240307) & 0.802884615384616 & 104.0 &  &  & 28.60576923076923 & 292.4230769230769 \\
Claude 3 Sonnet (20240229) & 0.8384615384615389 & 104.0 &  &  & 28.60576923076923 & 343.625 \\
Claude 3 Opus (20240229) & 0.8538461538461543 & 104.0 &  &  & 28.60576923076923 & 302.83653846153845 \\
Gemini 1.5 Pro (0409 preview) & 0.4384615384615387 & 104.0 &  &  & 26.865384615384617 &  \\
PaLM-2 (Bison) & 0.5884615384615389 & 104.0 &  &  & 26.865384615384617 &  \\
PaLM-2 (Unicorn) & 0.6163461538461543 & 104.0 &  &  & 27.71153846153846 &  \\
MedLM (Medium) & 0.5461538461538467 & 104.0 &  &  & 27.71153846153846 &  \\
MedLM (Large) & 0.7115384615384622 & 104.0 &  &  & 27.71153846153846 &  \\
GPT-3.5 Turbo (0125) & 0.740384615384616 & 104.0 &  &  & 25.740384615384617 & 76.9423076923077 \\
GPT-4 Turbo (2024-04-09) & 0.7221153846153854 & 104.0 &  &  & 25.740384615384617 & 78.75961538461539 \\
GPT-4o (2024-05-13) & 0.687500000000001 & 104.0 &  &  & 25.134615384615383 & 65.84615384615384 \\
\bottomrule
\end{tabular}}
\caption{Results for live_qa_ (live_qa)}
\label{fig:live_qa_ (live_qa)}
\end{table*}