The success ratio, or precision, is a ratio of DFT-validated stable materials among MLpredicted stable materials, and the discoverability, or recall, is a ratio of discovered stable materials by ML among all stable materials in the dataset (See "Terminology and Derivations of Statistical Metrics" in Method section for more details). To be suitable for HTVS, ML model should achieve both high success ratio and discoverability simultaneously. Thus, we not only evaluated these two metrics separately, but also at the same time using F1-score, a harmonic mean of two metrics . Note that we determined stability and synthesizability of materials when both formation energy (Ef DFT ) and energy above the convex hull (Ehull DFT ) satisfy criteria, Ef DFT ≤ 0.0 eV/atom and Ehull DFT ≤ 0.1 eV/atom, which are generally accepted thresholds in literature . Ehull DFT is calculated as formation energy difference with respect to the most stable phase at that composition. Thresholds of Ef ML and Ehull ML , however, are set by researchers' intuition and prediction accuracy of ML models, which could significantly affect HTVS results. Thus, we tested numerous values of Ef ML (from -0.25 to +0.25 eV/atom) and