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Even removing 32/128 channels (25%), kurtosis stays at 8-50. WHT rotation gets it to 2.9. Some layers get WORSE after removal (55.6 → 156.98). Heavy tails are structural, not channel-specific. WUSH paper confirmed: Hadamard is optimal data-agnostic transform. Outlier removal would also need per-model calibration, killing TurboQuant's zero-calibration advantage. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> Co-Authored-By: tturney@psyguard.ai