Your team deployed a loan-approval model to a managed online endpoint with inference data collection enabled. Business stakeholders report that predictions seem to be shifting even though the overall input distribution appears stable. You want Azure Machine Learning model monitoring to specifically identify which input features are contributing differently to the model's predictions over time, so you can pinpoint the cause. Which monitoring signal should you configure?