Adaptive Machine Learning Model Performance Monitoring

Design an intelligent monitoring system for tracking machine learning model performance in scientific research contexts. Create a framework that automatically detects statistical drift, performs continuous validation, and generates comprehensive performance reports. Implement adaptive retraining strategies, support for multiple evaluation metrics, and provide visualization dashboards that highlight model degradation. Include robust handling for domain-specific challenges like temporal data variations and limited ground truth in research environments.