Results and Discussion For our analysis, the dataset was partitioned into training, validation, and testing subsets in an 80:10:10 ratio. Using EGNN-DER, we achieved a mean absolute error (MAE) of 0.578 bohr² to predict electronic spatial extent (Figure ). Analysis of uncertainty components revealed that aleatoric uncertainty arising from the noise of the data was significantly larger than epistemic uncertainty, which accounts for intrinsic data noise. Consequently, the total uncertainty was dominated by aleatoric factors (Figure ).