We evaluated the performance of machine learning models discussed in Section 3. For a maximum depth of the individual estimators in the RF model set to 20 and the number of estimators set to 200 for RF and 250 for AdaBoost, respectively, we report Accuracy (ACC), True Positive Rate (TPR) also referred to as Sensitivity, the True Negative Rate (TNR) also known as Specificity, the Area Under the Curve (AUC) and the F1 score or the balanced F-measure (for Pass, Fail), the harmonic mean of precision and recall. A subset of curated data with all the features used for the development of models is made available in public share .