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The segmentation ceiling gives a concrete design criterion for when mask-guided EF estimation is worthwhile, plus a simple, uncertainty-aware recipe for EF regression, and a heteroscedastic beta-NLL formulation yields informative, well-calibrated per-prediction uncertainty.