% généré par make_paper_tables.py
\newcommand{\nSalesRaw}{456,950}
\newcommand{\nSalesClean}{390,996}
\newcommand{\nTrain}{201,642}
\newcommand{\nVal}{64,795}
\newcommand{\nTest}{124,559}
\newcommand{\nTargetsVal}{64,795}
\newcommand{\nTargetsTest}{124,559}
\newcommand{\nTargetsAll}{189,354}
\newcommand{\nConfigs}{2,256}
\newcommand{\nTransactionsDb}{766,596}
\newcommand{\nUnits}{3.75 million}
\newcommand{\dateMin}{2021-01-05}
\newcommand{\dateMax}{2026-09-29}
\newcommand{\medianPrice}{400,000}
\newcommand{\mdapeMzero}{11.1\%}
\newcommand{\mdapeMtwo}{18.1\%}
\newcommand{\mdapeMthree}{13.0\%}
\newcommand{\mdapeMsix}{13.4\%}
\newcommand{\mdapeMseven}{13.0\%}
\newcommand{\mdapeMnine}{10.6\%}
\newcommand{\mdapeMten}{13.8\%}
\newcommand{\mdapeMelevenA}{10.7\%}
\newcommand{\mdapeMelevenB}{9.0\%}
\newcommand{\mdapeMtwelve}{8.9\%}
\newcommand{\mdapeMthirteen}{11.5\%}
\newcommand{\convMdape}{13.4\%}
\newcommand{\localMdape}{13.5\%}
\newcommand{\covMthirteen}{90.3\%}
\newcommand{\pTenMzero}{46.1\%}
\newcommand{\pTenMelevenB}{54.1\%}
\newcommand{\mdapeMoneRange}{17.9--19.1\%}
\newcommand{\mdapeGridRange}{13.0--13.4\%}
\newcommand{\transparencyCost}{2.2}
\newcommand{\transparencyCostNoRole}{0.4}
\newcommand{\roleGainRatio}{1.5}
\newcommand{\roleGainGbm}{1.8}
\newcommand{\gainTime}{0.3}
\newcommand{\gainGridLo}{4.2}
\newcommand{\gainGridHi}{5.7}
\newcommand{\localVsHedo}{slightly worse}
\newcommand{\gbmVsHedo}{1.1}
\newcommand{\gainSelHedo}{0.5}
\newcommand{\wrRange}{1.0}
\newcommand{\margSelLo}{12.9}
\newcommand{\margSelHi}{14.4}
\newcommand{\margAdjLo}{11.8}
\newcommand{\margAdjHi}{15.4}
\newcommand{\margWLo}{13.1}
\newcommand{\margWHi}{13.6}
\newcommand{\margReconMedian}{13.2}
\newcommand{\margReconMean}{13.6}
\newcommand{\kOpt}{20}
\newcommand{\mdapeKone}{16.5\%}
\newcommand{\mdapeKthree}{13.8\%}
\newcommand{\mdapeKfive}{13.0\%}
\newcommand{\mdapeKten}{12.4\%}
\newcommand{\mdapeKopt}{12.1\%}
\newcommand{\mdapeKfifty}{12.1\%}
\newcommand{\narrowMdape}{13.6\%}
\newcommand{\narrowCov}{89.2\%}
\newcommand{\bestSel}{compromise}
\newcommand{\bestK}{30}
\newcommand{\bestD}{25}
\newcommand{\bestT}{24}
\newcommand{\bestAdj}{hedonic grid}
\newcommand{\bestValMdape}{11.9\%}
\newcommand{\bestTestMdape}{11.1\%}
\newcommand{\mZeroDesc}{compromise, $k=30$, $\le 25$ km, 24 months, hedonic grid, equal weights, median}
\newcommand{\mZeroUncDesc}{compromise, $k=10$, $\le 10$ km, 24 months, assessment ratio}
\newcommand{\mZeroUncMdape}{10.7\%}
\newcommand{\mZeroUncCov}{90.3\%}
\newcommand{\densHighMseven}{10.2\%}
\newcommand{\densLowMseven}{25.3\%}
\newcommand{\hOneGeoDone}{17.2\%}
\newcommand{\hOneGeoDoneCov}{96.0\%}
\newcommand{\hOneSimDten}{13.0\%}
\newcommand{\hOneGeoDten}{17.6\%}
\newcommand{\hOneGeoDtenHedo}{13.0\%}
\newcommand{\hOneSimDtenHedo}{12.7\%}
\newcommand{\hOneMixDtenHedo}{12.1\%}
\newcommand{\hFiveGapHomog}{1.4}
\newcommand{\hFiveGapHeter}{3.1}
\newcommand{\ivWidth}{66.5\%}
\newcommand{\condMdape}{11.3\%}
\newcommand{\condPten}{42.5\%}
\newcommand{\condCov}{93.4\%}
\newcommand{\betaFloor}{0.60}
\newcommand{\betaLand}{0.07}
\newcommand{\betaAge}{1.0\%}
\newcommand{\betaSemi}{7.4\%}
\newcommand{\betaRow}{10.5\%}
\newcommand{\gainTimeLong}{1.4}
\newcommand{\noneKten}{17.3\%}
\newcommand{\noneKfifty}{18.4\%}
\newcommand{\prixQoneMseven}{36.7\%}
\newcommand{\prixQfourMseven}{10.0\%}
\newcommand{\biasQoneMseven}{-2.4\%}
\newcommand{\biasQthreeMseven}{+1.5\%}
\newcommand{\wNineNone}{0.07}
\newcommand{\wNineGbm}{0.33}
\newcommand{\wNineRole}{0.59}
\newcommand{\wTwelveGbm}{0.91}
\newcommand{\wTwelveCompGbm}{0.03}
\newcommand{\wTwelveCompHedo}{0.07}
\newcommand{\densLowN}{9,177}
\newcommand{\densLowNall}{9,426}
\newcommand{\ivCovLo}{66}
\newcommand{\ivCovHi}{78}
\newcommand{\ivHalf}{33\%}
\newcommand{\hFourSimDense}{10.5\%}
\newcommand{\hFourEqualMeanDense}{10.9\%}
\newcommand{\gridRtwo}{0.36}
\newcommand{\gridN}{266,437}