Chemically Intuitive Descriptors for Predicting CH Borylation Regioselectivity
We present a robust machine‐learning (ML) framework incorporating chemically intuitive descriptors to predict regioselectivity in CH borylation reactions. Our method integrates electronic parameters (pKa values, CM5 atomic charges, Fukui indices) and steric metrics (buried volume, solvent‐accessible surface area) to s...