We trained four distinct classification models, as outlined in the previous sections. These models were trained on the IGD_FP, Subset-IGD_FP, Subset-IGD_VS and Subset-IGD_MS. We used an 80%-20% split for our dataset in all the experiments. The performance of the model was assessed using micro-averaged F1 scores, macro-averaged F1 scores, and the area under the ROC curve (AU-ROC). The results for the macro-averaged F1 scores and AUC-ROC scores are presented in Supplementary File 2.