Table 17: Full output of the linear model assessing the impact of data-centric processing on the classification task. The model has the following formula: auroc  $\sim$  dataset_id * generative_model + preprocessing_strategy + postprocessing_strategy.
coef	std err	t	P> |t|	[0.025, 0.975]
Intercept	0.7902	0.004	204.799	0.000	0.783	0.798
dataset_id[T3.61060]	-0.1217	0.005	-22.730	0.000	-0.132	-0.111
dataset_id[T3.61062]	0.1000	0.005	18.669	0.000	0.089	0.110
dataset_id[T3.61063]	-0.2918	0.005	-54.508	0.000	-0.302	-0.281
dataset_id[T3.61065]	-0.2965	0.005	-55.379	0.000	-0.286	-0.286
dataset_id[T3.61066]	-0.2066	0.005	-38.587	0.000	-0.217	-0.196
dataset_id[T3.61070]	-0.2510	0.005	-46.876	0.000	-0.261	-0.240
dataset_id[T3.61273]	-0.1725	0.011	-15.192	0.000	-0.195	-0.150
dataset_id[T3.61275]	-0.0790	0.002	-36.264	0.000	-0.083	-0.075
dataset_id[T3.61288]	-0.2882	0.005	-53.822	0.000	-0.299	-0.278
dataset_id[T3.61278]	-0.0492	0.002	-22.787	0.000	-0.053	-0.045
generative_model[Tetgan]	0.0228	0.006	4.107	0.000	0.012	0.034
generative_model[Tetdpm]	0.0488	0.005	9.109	0.000	0.038	0.059
generative_model[Tatflow]	0.0254	0.005	4.746	0.000	0.015	0.036
generative_model[Ttvec]	-0.0109	0.005	-2.034	0.042	-0.021	-0.000
preprocessingStrategy[Leasy-hard]	0.0007	0.001	0.635	0.000	-0.003	-0.003
postprocessingStrategy[Tno硬]	0.0067	0.001	6.393	0.000	0.005	0.009
dataset_id[T3.61060]	generative_model[Tetgan]	0.1514	0.008	19.314	0.000	0.136	0.167
dataset_id[T3.61062]	generative_model[Tetdpm]	0.0334	0.008	4.340	0.000	0.018	0.049
dataset_id[T3.61063]	generative_model[Tetgan]	0.3876	0.008	50.293	0.000	0.372	0.403
dataset_id[T3.61066]	generative_model[Tetdpm]	0.3626	0.008	47.056	0.000	0.347	0.378
dataset_id[T3.61066]	generative_model[Tetgan]	0.2351	0.008	30.504	0.000	0.220	0.250
dataset_id[T3.61070]	generative_model[Tetgan]	-0.0246	0.008	-3.191	0.001	-0.040	-0.009
dataset_id[T3.61273]	generative_model[Tetgan]	-0.0336	0.013	-2.658	0.008	-0.058	-0.009
dataset_id[T3.61275]	generative_model[Tetgan]	-0.0248	0.005	-5.147	0.000	-0.034	-0.015
dataset_id[T3.61277]	generative_model[Tetdpm]	0.3828	0.005	-3.681	0.000	-0.363	-0.359
dataset_id[T3.61278]	generative_model[Tetgan]	-0.0010	0.005	-0.204	0.838	-0.010	0.008	Omnibus: Prob(Omnibus): 368.744	Durbin-Watson: 1.231
dataset_id[T3.61060]	generative_model[Tetdpm]	0.1686	0.008	22.261	0.000	0.154	0.183	Kurtosis: -0.586	Jarque-Bera (JB): 5945.102
dataset_id[T3.61062]	generative_model[Tetdpm]	-0.0044	0.008	-0.583	0.560	-0.019	0.010
dataset_id[T3.61063]	generative_model[Tetgan]	0.3924	0.008	51.823	0.000	0.378	0.407
dataset_id[T3.61065]	generative_model[Tetdpm]	0.3751	0.008	29.555	0.000	0.360	0.390
dataset_id[T3.61066]	generative_model[Tetgan]	-0.2268	0.008	29.955	0.000	0.212	0.242
dataset_id[T3.61070]	generative_model[Tetdpm]	-0.0828	0.008	-10.929	0.000	-0.098	-0.068
dataset_id[T3.61273]	generative_model[Tetdpm]	-0.0342	0.013	-2.721	0.007	-0.059	-0.010
dataset_id[T3.61275]	generative_model[Tetdpm]	-0.0297	0.005	-6.172	0.000	-0.039	-0.020
dataset_id[T3.61277]	generative_model[Tetdpm]	0.3912	0.008	51.667	0.000	0.376	0.406
dataset_id[T3.61278]	generative_model[Tetdpm]	-0.0266	0.005	-5.681	0.000	-0.036	-0.017
dataset_id[T3.61060]	generative_model[Tatflow]	0.1307	0.008	17.264	0.000	0.116	0.146
dataset_id[T3.61063]	generative_model[Tatflow]	-0.2662	0.008	-35.153	0.000	-0.281	-0.251
dataset_id[T3.61065]	generative_model[Tatflow]	0.3527	0.008	46.577	0.000	0.338	0.368
dataset_id[T3.61065]	generative_model[Tatflow]	0.2659	0.008	35.114	0.000	0.251	0.281
dataset_id[T3.61066]	generative_model[Tatflow]	0.1658	0.008	21.898	0.000	0.151	0.181
dataset_id[T3.61070]	generative_model[Tatflow]	-0.0587	0.008	-7.755	0.000	-0.074	-0.044
dataset_id[T3.61273]	generative_model[Tatflow]	-0.0340	0.013	-2.706	0.007	-0.059	-0.009
dataset_id[T3.61275]	generative_model[Tatflow]	-0.3517	0.008	-46.451	0.000	-0.043	-0.025
dataset_id[T3.61277]	generative_model[Tatflow]	-0.0585	0.005	-10.700	0.000	-0.059	-0.041
dataset_id[T3.61060]	generative_model[Tatflow]	0.1793	0.008	23.684	0.000	0.164	0.194
dataset_id[T3.61062]	generative_model[Tatflow]	0.0874	0.008	11.540	0.000	0.073	0.102
dataset_id[T3.61063]	generative_model[Tatflow]	0.4303	0.008	56.827	0.000	0.415	0.445
dataset_id[T3.61065]	generative_model[Tatflow]	0.3816	0.008	50.397	0.000	0.367	0.396
dataset_id[T3.61066]	generative_model[Tatflow]	0.2467	0.008	32.578	0.000	0.232	0.262
dataset_id[T3.61070]	generative_model[Tatflow]	-0.5319	0.008	4.210	0.000	-0.017	-0.047
dataset_id[T3.61273]	generative_model[Tatflow]	-0.0214	0.013	-1.701	0.089	-0.046	0.003
dataset_id[T3.61275]	generative_model[Tatflow]	0.0955	0.005	2.036	0.042	0.000	0.019
dataset_id[T3.61277]	generative_model[Tatflow]	-0.4105	0.008	54.211	0.000	0.396	0.425
dataset_id[T3.61278]	generative_model[Tatflow]	-0.0283	0.005	6.062	0.000	0.019	0.038