Model calibration
From calibration standpoint, the main effect model and machine learning algorithm (fig S1a and S1b) were well calibrated in the lower segment of predicted probability (0-5%). Beyond this probability range, the main effect model did not seem well calibrated due to perhaps the absence of adequate number of parameters (in other words, misspecification error in the 5% to 100% probability range) resulting in risk over-estimation. The ML based algorithm overestimated the risk beyond 5% (beyond the range of operation), but had better calibration than that obtained for the main effect model.