Opportunity Loss at an Input-Sensitive Top-Group Boundary
Abstract
Input uncertainty can move group membership while expected opportunity cost determines which exclusions are serious. Evaluation needs a declared group size and a shared loss across scenarios. It counts input evidence separately from simulator replications. Resolving interior nominal ranks can be less useful than directly checking the candidates whose scenario-sensitive membership changes the next action. This focused synthesis develops an empirical comparison that preserves the terminal action, observation process, and total verification cost. Its proposed tests are prospective; no new simulation run, model-training result, or intervention effect is reported.
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