Performance metrics computed for the fourth-generation ML models with DFT and ML predicted DFT (ML-DFT) properties for AIE, AEA, VIE, and VEA concatenated to the MPNN representation. For ML-DFT, the required input DFT values were predicted from the fourth-generation ML model with molecular descriptors (see Table 5 for the performance of the model). MAE is reported in eV for all models. The values are averaged over five-fold cross-validation models.

Property	DFT		ML-DFT
	R 2	MAE	R 2	MAE
HOMO	0.81 ± 0.01	0.327 ± 0.140	0.68 ± 0.01	1.105 ± 1.661
LUMO	0.93 ± 0.00	0.132 ± 0.009	0.82 ± 0.01	0.235 ± 0.020
H–L	0.84 ± 0.01	0.415 ± 0.169	0.59 ± 0.01	0.872 ± 0.291
CR2	0.69 ± 0.01	0.036 ± 0.003	0.44 ± 0.00	0.057 ± 0.006
HR	0.92 ± 0.01	0.039 ± 0.011	0.44 ± 0.01	0.107 ± 0.005
AR2	0.77 ± 0.01	0.034 ± 0.008	0.47 ± 0.02	0.057 ± 0.009
ER	0.94 ± 0.01	0.045 ± 0.014	0.52 ± 0.02	0.117 ± 0.032
S0S1	0.90 ± 0.01	0.396 ± 0.041	0.80 ± 0.01	0.322 ± 0.042