1% generated by tables/make_tables.py from /Users/simon-pierreboucher/Desktop/UQO/Recherche/Recherche-UQO/informatique/wp44/results/econometrics/its_results.json2\begin{longtable}{lrrrrrrrr}3\caption{ITS slope change at December 2022 by category: pre-period slope, change, HAC and placebo $p$-values, and implied post-period slope (monthly log growth).}\label{tab:p9-its-slopes}\\4\toprule5\textbf{Category} & \textbf{Works} & \textbf{Pre-slope} & \textbf{Slope change} & \textbf{SE} & \textbf{HAC p} & \textbf{Placebo p (all)} & \textbf{Placebo p (base)} & \textbf{Post slope} \\6\midrule7\endfirsthead8\toprule9\textbf{Category} & \textbf{Works} & \textbf{Pre-slope} & \textbf{Slope change} & \textbf{SE} & \textbf{HAC p} & \textbf{Placebo p (all)} & \textbf{Placebo p (base)} & \textbf{Post slope} \\10\midrule11\endhead12AI Agents and Autonomous Systems & 116{,}719 & 0.0032 & +0.0401 & 0.0046 & 3.61e-18 & 0.400 & 0.000 & 0.0433 \\13Large Language Models & 346{,}928 & 0.0132 & +0.0336 & 0.0020 & 1.07e-60 & 0.200 & 0.353 & 0.0469 \\14Multimodal AI & 133{,}911 & 0.0192 & +0.0238 & 0.0018 & 6.35e-39 & 0.200 & 0.353 & 0.0430 \\15Information Retrieval & 206{,}216 & 0.0031 & +0.0233 & 0.0019 & 7.12e-35 & 0.092 & 0.000 & 0.0264 \\16Distributed Computing & 359{,}867 & 0.0013 & +0.0200 & 0.0015 & 4.32e-43 & 0.077 & 0.000 & 0.0213 \\17Generative AI & 175{,}254 & 0.0190 & +0.0194 & 0.0024 & 1.05e-15 & 0.308 & 0.324 & 0.0384 \\18Cloud Computing & 202{,}261 & -0.0013 & +0.0187 & 0.0018 & 1.94e-26 & 0.231 & 0.265 & 0.0174 \\19Natural Language Processing & 434{,}211 & 0.0094 & +0.0184 & 0.0015 & 1.21e-33 & 0.154 & 0.265 & 0.0278 \\20Quantum Computing & 125{,}359 & 0.0074 & +0.0181 & 0.0016 & 5.22e-31 & 0.169 & 0.000 & 0.0255 \\21Compilers & 48{,}920 & 0.0018 & +0.0180 & 0.0021 & 5.63e-18 & 0.215 & 0.176 & 0.0198 \\22Accelerators and AI Hardware & 104{,}043 & 0.0071 & +0.0180 & 0.0021 & 4.32e-18 & 0.169 & 0.029 & 0.0252 \\23Formal Verification & 77{,}664 & -0.0009 & +0.0177 & 0.0022 & 2.53e-15 & 0.246 & 0.029 & 0.0168 \\24AI Safety and Alignment & 139{,}500 & 0.0266 & +0.0164 & 0.0022 & 3.04e-13 & 0.308 & 0.029 & 0.0430 \\25Software Engineering & 388{,}733 & 0.0042 & +0.0162 & 0.0012 & 1.09e-44 & 0.154 & 0.265 & 0.0204 \\26Operating Systems & 101{,}411 & -0.0011 & +0.0158 & 0.0020 & 8.2e-15 & 0.477 & 0.294 & 0.0146 \\27Computer Architecture & 304{,}720 & -0.0011 & +0.0158 & 0.0012 & 2.36e-38 & 0.062 & 0.088 & 0.0146 \\28Sustainable Computing & 67{,}460 & 0.0039 & +0.0156 & 0.0012 & 1.23e-38 & 0.169 & 0.294 & 0.0196 \\29Human-Computer Interaction & 451{,}350 & 0.0038 & +0.0149 & 0.0009 & 7.23e-69 & 0.154 & 0.265 & 0.0188 \\30Cybersecurity & 630{,}599 & 0.0045 & +0.0146 & 0.0011 & 6.43e-37 & 0.062 & 0.000 & 0.0191 \\31Computational Complexity & 150{,}983 & 0.0024 & +0.0142 & 0.0009 & 6.63e-55 & 0.062 & 0.000 & 0.0166 \\32Computer Graphics & 192{,}097 & 0.0030 & +0.0141 & 0.0010 & 2.69e-42 & 0.185 & 0.324 & 0.0171 \\33Database Systems & 261{,}915 & 0.0013 & +0.0136 & 0.0012 & 5.81e-31 & 0.092 & 0.000 & 0.0148 \\34Applied Cryptography & 252{,}420 & 0.0026 & +0.0133 & 0.0009 & 9.67e-46 & 0.046 & 0.059 & 0.0159 \\35Privacy-Preserving Computation & 181{,}159 & 0.0140 & +0.0125 & 0.0013 & 6.58e-21 & 0.138 & 0.235 & 0.0265 \\36Programming Languages & 116{,}536 & 0.0014 & +0.0123 & 0.0023 & 1.34e-07 & 0.431 & 0.324 & 0.0137 \\37Speech and Audio Computing & 146{,}061 & 0.0029 & +0.0118 & 0.0016 & 1.76e-13 & 0.169 & 0.294 & 0.0147 \\38Reinforcement Learning & 171{,}820 & 0.0173 & +0.0116 & 0.0022 & 1.55e-07 & 0.385 & 0.000 & 0.0289 \\39Autonomous Scientific Discovery & 24{,}409 & 0.0207 & +0.0112 & 0.0021 & 1.31e-07 & 0.431 & 0.000 & 0.0319 \\40Algorithms and Data Structures & 500{,}703 & 0.0022 & +0.0098 & 0.0010 & 4.01e-21 & 0.062 & 0.000 & 0.0120 \\41Machine Learning Theory & 424{,}417 & 0.0106 & +0.0091 & 0.0016 & 1.07e-08 & 0.215 & 0.000 & 0.0197 \\42Computer Networks & 654{,}017 & 0.0002 & +0.0086 & 0.0010 & 4.81e-18 & 0.200 & 0.353 & 0.0088 \\43Scientific Computing & 388{,}897 & 0.0056 & +0.0068 & 0.0009 & 4.43e-14 & 0.154 & 0.000 & 0.0124 \\44Computer Vision & 1{,}027{,}433 & 0.0076 & +0.0065 & 0.0009 & 3.43e-13 & 0.169 & 0.294 & 0.0141 \\45Foundation Models & 193{,}776 & 0.0255 & +0.0064 & 0.0028 & 0.0208 & 0.246 & 0.412 & 0.0320 \\46Computational Biology & 267{,}762 & 0.0107 & +0.0055 & 0.0008 & 3.95e-11 & 0.308 & 0.000 & 0.0162 \\47Robotics & 318{,}268 & 0.0083 & +0.0051 & 0.0012 & 8.89e-06 & 0.108 & 0.176 & 0.0134 \\48Edge Computing & 231{,}512 & 0.0103 & +0.0039 & 0.0014 & 0.00561 & 0.077 & 0.000 & 0.0142 \\49Blockchain Systems & 138{,}361 & 0.0148 & -0.0021 & 0.0016 & 0.2 & 0.508 & 0.735 & 0.0127 \\50Deep Learning Architectures & 772{,}532 & 0.0174 & -0.0025 & 0.0017 & 0.136 & 0.708 & 1.000 & 0.0149 \\51Federated Learning & 58{,}126 & 0.0369 & -0.0063 & 0.0019 & 0.001 & 0.385 & 0.676 & 0.0305 \\52\bottomrule53\multicolumn{9}{p{0.95\linewidth}}{\footnotesize Multi-label monthly series of month-precision works (Part IV); Works: series total over the window. Placebo $p$ (all): rank of the slope $t$-statistic among all candidate event months; (base): among baseline months only, where zero is attainable. Sorted by slope change.}\\54\end{longtable}55