Piece-square and feature weights now converge to a presence-weighted fractional win-rate per cell (percent of games won with a piece there minus percent lost), tracked via running visits/score sums instead of an incrementally clamped nudge. The training signal is also scaled by how much of a game's result is NOT already explained by the winner's average material edge (via the standard centipawn win-probability curve), so a piece no longer gets credit merely for existing on the winning side of a material blowout in the endgame. Co-Authored-By: Claude Sonnet 5 <[email protected]> Claude-Session: https://claude.ai/code/session_018CmAti1baCjidbJM2HeJfk