Models were calibrated using training and test data (75% and 25% randomly selected occurrence points respectively).

Area under the curve (AUC) was calculated as an average of 30 model replicate runs using subsample run type. Mean AUC and omission rate values were calculated both for test and training data. The mean omission rates are calculated at an arbitrarily chosen cumulative threshold of 10. All model omission results performed significantly better than random (pModels were calibrated using training and test data (75% and 25% randomly selected occurrence points respectively).受试者工作特征曲线下面积（Area Under the Curve, AUC）采用子采样运行模式，通过30次模型重复运行的均值计算得到。分别针对测试数据集与训练数据集，计算得到平均AUC值与遗漏率（omission rate）数值。平均遗漏率在任意选定的累积阈值为10的条件下计算得出。所有模型的遗漏结果均显著优于随机预测结果（原文此处疑似缺失p值相关标注）；模型通过训练数据与测试数据进行校准，其中训练集与测试集分别随机选取75%、25%的出现点位（occurrence points）。