Ordered boosting in one walkthrough: how CatBoost makes gradient boosting unbiased

Previous post argued that standard gradient boosting has a self-referential bias problem: every example contributes to the model that then predicts it. Cross-validation under-detects the bias because it manifests inside a single training fold.