For 𝑇 𝑔 predictions (Figure The results demonstrate that BNN provides the best balance of predictive accuracy and uncertainty estimation across all four polymer properties. GPR, despite good calibration, fails to align uncertainties with errors effectively, as reflected by negative Spearman's coefficients. These findings highlight the importance of combining predictive accuracy with robust UQ metrics, like Spearman's correlation coefficient and calibration area, to comprehensively evaluate ML models.