Precision-Recall (P-R) curve is commonly employed to evaluate classification performances, where the upper right corner corresponds to better screening results (Fig. ) . To clearly understand the trends, we visualized the effect of changing thresholds of Ef ML and Ehull ML in three dimensions (Supplementary Fig. ). For all models, we found that success ratio and discoverability are proportional to each other when Ehull ML is lower than ~0.1 eV/atom, while they become inversely proportional otherwise. Thus, the maximum F1-score for all models was achieved near Ehull ML = 0.1 eV/atom (Supplementary Table ). Among all models, ESNet achieved the best F1-score when Ef ML ≤ -0.02 eV/atom and Ehull ML ≤ 0.13 eV/atom thresholds were used.