\begin{table}[t]
\centering
\begin{tabular}{clc|cc}
\hline

Rank & Team & \textbf{Accuracy} & TPR $\uparrow$ & FPR $\downarrow$ \\
\hline
1 & Gradient Descenders & \textbf{0.9458}  & 0.8965 & 0.0048 \\
2 & Kenji-Endo & 0.9426 & \underline{\textbf{0.9031}} & 0.0176 \\
3 & UniTor$^*$ & 0.9288 &  0.8621 & 0.0042 \\
4 & Nicla & 0.9243   & 0.8598 & 0.0109 \\
5 & Stochastic Gradient Descenders & 0.9216  & 0.8468 & \textbf{0.0032} \\
\hline
\rowcolor{gray!15}
& Baseline & 0.8769 & 0.7857 & 0.0315 \\

\rowcolor{gray!15}
& Pangram & 0.8893 & 0.7791 & \underline{0.0000} \\

\rowcolor{gray!15}
& UniTor (late) & \underline{0.9578} & \underline{0.9238} & 0.0081 \\

\hline
\end{tabular}
\caption{Team rankings and accuracies on sub-task A. Rows with a \colorbox{gray!15}{gray background} indicate non-competing results. \textbf{Bold} scores indicate best results among competing participants, an \underline{underlined} one indicates best results among both competing and non-competing systems.}
\label{tab:res-detection}
\end{table}
