Extended Data Fig. 6: Between-framework comparisons with k = 9 data-driven domains.

To control for dimensionality in comparisons with the DSM, analyses were repeated with the k = 9 solution of the data-driven framework. Differences between framework pairs were assessed by two-sided bootstrap tests. With k = 9 in place of k = 6 domains, no differences in the data-driven, RDoC, and DSM rankings were observed. a, Reverse inference ROC-AUC in the test set was higher for the k = 9 data-driven framework than both RDoC (99.9% CI of the difference=[0.010, 0.066]) and the DSM (99.9% CI of the difference=[0.029, 0.102]). b, ROC curves of the k = 9 reverse inference classifiers. c, ROC-AUC of the k = 9 reverse inference classifiers. d, Forward inference ROC-AUC in the test set was higher for the k = 9 data-driven framework than both RDoC (99.9% CI of the difference=[0.027, 0.052]) and the DSM (99.9% CI of the difference=[0.061, 0.095]). e, ROC curves of the k = 9 forward inference classifiers. f, ROC-AUC of the k = 9 forward inference classifiers. Articles were partitioned into the the k = 9 data-driven domains within the g, discovery set (n = 12,708) and h, replication set (n = 5,447). i, Domain-averaged modularity (left panels) was higher for the k = 9 data-driven framework than for the k = 6 solution (99.9% CI of the difference = [0.007, 0.016] discovery, [0.009, 0.024] replication), RDoC (99.9% CI of the difference = [0.046, 0.053] discovery, [0.045, 0.059] replication), and the DSM (99.9% CI of the difference = [0.011, 0.022] discovery, [0.007, 0.026] replication). j, Domain-averaged generalizability (left panels) was higher for the k = 9 data-driven framework than for the DSM (99.9% CI of the difference = [0.043, 0.160] discovery, [0.039, 0.164] replication). Observed values for the k = 9 domains in the i-j right panels were compared against null distributions generated by shuffling over 1,000 iterations (* FDR < 0.001).