For each metric on every subset, a pairwise comparison of the three models was conducted to assess statistical significance using the paired t-test with Bonferroni correction. Firstly, Native consistently performs significantly worse than both RIGR and Native + Aug across all subsets, considering all metrics. Based on the RMSRR values for Native, the average range of predictions for the same radical with multiple resonance structures is around 3 kcal mol -1 , with the maximum RMSRR being greater than 25 kcal mol -1 . The substantial difference in predicted enthalpy, depending on which resonance structure is chosen as the input, reveals the inconsistency in predictions caused by resonance and underscores the necessity of RIGR. Comparing Native with Native + Aug shows that training on augmented data improves performance across all three metrics. Native + Aug achieves a slightly lower RMSE than RIGR on the entire set; however, this difference is not statistically significant.