To understand the complex relationship between electrode degradation and resistance growth in a full cell, we expand on the "protocol model" discussed in the previous section to include EOL electrode-specific capacities/ SOCs metrics as input features. This "explanatory model" aims to learn the relationship between the physically meaningful electrode-level features and the mechanistic SOH metric of interest (Fig. ). In this section, we investigate the changes in the electrode-specific capacities/SOCs and resistances with cycling. As such, the model inputs are the changes in SOH metrics from BOL to EOL (represented by ∆). The model output here is the low SOC (30%) total resistance (summation of R ohm , R ct , and R p , SI Section S.3.2). We choose this health metric as the example target of our explanatory model because resistance at low SOCs are typically the largest and limit the discharge capacity. Fig. lists the most dominant features contributing to the observed total resistance growth. From the SHAP analysis, we observe that two electrode-specific features, ∆SOC PE,2.7V and ∆SOC NE,2.7V , are dominant features impacting the total resistance but show opposite relationships with resistance growth (Fig. ). Surprisingly, negative electrode over-discharging (∆SOC NE,2.7V < 0) leads to lower resistance increase. This is unexpected because electrode kinetics are typically most sluggish at the SOC extremes; therefore, at low SOC, we expect that resistance should increase in the direction of deeper discharge for an electrode .