We sealed our predictions before running the experiments — across six public battery datasets. Full scorecard, including two unedited falsifications.

TL;DR - One data-level diagnostic workflow, applied to six battery fleets from five public sources (NASA PCoE; CALCE/UMD — the CS2 and CX2 series; MIT/Severson; Oxford; HUST). Every prediction was written down and hashed before the corresponding experiment ran — one of them with a publicly timestamped, Bitcoin-seeded protocol anyone can verify. - Diagnosis mode: on the HUST fleet (77 cells, never touched before), we predicted an error-reduction band of [−45%, −20%] before modeling. Measured: −34.4%. Hit. - Design mode: using only the manufacturer's spec sheet (max continuous charge current, 4A