% Author: Simon-Pierre Boucher — contact@spboucher.ai
% Generated by scripts/06_tables.py — do not edit by hand.
\begin{table}[!htbp]
\centering
\caption{Descriptive statistics for cosine similarity features and bivariate correlations with log(price).}
\label{tab:sim_stats}
\begin{threeparttable}
\small
\begin{adjustbox}{max width=\textwidth}
\begin{tabular}{lR{1.2cm}R{1.2cm}R{1.2cm}R{1.2cm}R{1.2cm}R{1.4cm}}
\toprule
\textbf{Reference} & \textbf{Mean} & \textbf{Std.~Dev.} & \textbf{Min} & \textbf{Median} & \textbf{Max} & \textbf{Corr.\ $\ln P$} \\
\midrule
Luxury & 0.337 & 0.157 & $-$0.030 & 0.376 & 0.692 & $-$0.234 \\
Entry-Level & 0.313 & 0.167 & $-$0.085 & 0.385 & 0.660 & $-$0.270 \\
Renovated & 0.352 & 0.168 & $-$0.056 & 0.411 & 0.753 & $-$0.250 \\
Needs Renovation & 0.321 & 0.138 & $-$0.083 & 0.367 & 0.652 & $-$0.251 \\
Bright \& Spacious & 0.357 & 0.153 & $-$0.104 & 0.400 & 0.672 & $-$0.228 \\
Land \& Nature & 0.330 & 0.116 & $-$0.021 & 0.337 & 0.701 & $-$0.174 \\
Panoramic View & 0.316 & 0.120 & $-$0.114 & 0.343 & 0.613 & $-$0.185 \\
Premium Location & 0.321 & 0.141 & $-$0.025 & 0.364 & 0.693 & $-$0.289 \\
Quiet \& Peaceful & 0.358 & 0.111 & $-$0.065 & 0.376 & 0.630 & $-$0.228 \\
Income/Investment & 0.358 & 0.126 & $-$0.029 & 0.398 & 0.661 & $-$0.275 \\
Garage \& Parking & 0.310 & 0.112 & $-$0.078 & 0.317 & 0.685 & $-$0.210 \\
Finished Basement & 0.305 & 0.139 & $-$0.069 & 0.324 & 0.708 & $-$0.228 \\
Modern/Contemporary & 0.365 & 0.115 & $-$0.044 & 0.382 & 0.671 & $-$0.187 \\
Heritage/Character & 0.366 & 0.143 & $-$0.090 & 0.399 & 0.715 & $-$0.235 \\
Energy Efficient & 0.298 & 0.134 & $-$0.058 & 0.327 & 0.648 & $-$0.234 \\
Motivated Seller & 0.254 & 0.165 & $-$0.151 & 0.326 & 0.586 & $-$0.279 \\
Family-Friendly & 0.349 & 0.142 & $-$0.080 & 0.371 & 0.722 & $-$0.231 \\
Waterfront & 0.331 & 0.151 & $-$0.117 & 0.370 & 0.728 & $-$0.223 \\
New Construction & 0.372 & 0.122 & $-$0.020 & 0.396 & 0.694 & $-$0.240 \\
Pool \& Landscaping & 0.348 & 0.158 & $-$0.070 & 0.382 & 0.756 & $-$0.240 \\
\bottomrule
\end{tabular}
\end{adjustbox}
\begin{tablenotes}
\footnotesize
\item \textit{Notes:} Cosine similarity is computed between each listing embedding and the corresponding reference description embedding using the all-MiniLM-L6-v2 sentence transformer. Corr.\ $\ln P$ denotes the Pearson correlation with log listing price.
\end{tablenotes}
\end{threeparttable}
\end{table}
