Comparison between predicted and true values of R_ta for models using the MDPL2 “mass” images from: the low-velocity-cut data (left panel); the high-velocity-cut data (middle panel); and the low-velocity-cut data after removing the central halo of each projection (right panel). The colors represent the number density of the plotted points, calculated using a Gaussian kernel density estimate. R² scores and the mean absolute errors (MAEs) are shown at the bottom right of each plot. While the models in the left and middle panel show some correlation between true and predicted R_ta values, the right-panel model appears to mostly predict the mean value of the R_ta distribution, especially when comparing the MAEs with the standard deviation of the R_ta distribution (2.2 Mpc) as shown in the upper panel of Fig. 1.