To calculate the feature importances, we used SHAP analysis . Comparing SHAP values gives a statistical quantification of the importance of each discharge profile feature. Despite removing highly correlated features, SHAP results still exhibits some dependence on the random seed. To address this issue, the average of 25 random seed runs is reported. Results were consistent across different traintest splits (Figure ). The EoL metrics variability is dependent on both the variability induced by the average current (illustrated by 2d) and the variability induced by protocol-specific characteristics. In this work, we are interested in explaining the variability not induced by the average C-rate. As a result,