Comprehensive Supply Chain Risk Prediction Model

Create an advanced predictive model for supply chain risk assessment using ensemble machine learning techniques. Develop a Python script that integrates multiple data sources including historical procurement data, global economic indicators, and real-time supplier performance metrics. Implement stacked generalization with multiple base models (random forest, gradient boosting, neural networks) to predict potential supply chain disruptions with confidence intervals. Include geopolitical risk scoring and scenario simulation capabilities.