Widely used utility functions assess the exceptionality of SGs by comparing the data distribution of the SG and that of 𝑃 ̃ via a single summary-statistics value. For example, the positive-mean-shift utility function for metric target favors the identification of SGs with high 𝑌 values only based on the means of the two distributions. Thus, it is often assumed that the distributions are well characterized by the chosen summary-statistics value and that 𝑃 ̃ is representative of the full population 𝑃. However, distributions in materials science are typically non-normal and 𝑃 ̃ might not reflect the infinitely larger, unknown 𝑃. This calls for the consideration of utility functions that circumvent the mentioned assumptions.