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This paper demonstrates that pointwise metrics like RMSE and MAE structurally mislead for inverse problems with multimodal posteriors, because optimal point estimators collapse the posterior and distort spectral features. It proposes a three-part evaluation protocol using per-event distributional accuracy, spectrum-fidelity diagnostics, and coverage-based calibration to address these failures.