This record provides a reusable software framework for simulation based evaluation of deployment governance strategies in clinical artificial intelligence systems. The software implements contextual, cost aware multi armed bandit policies to govern adaptive model selection among multiple pre trained and independently validated predictive models under uncertainty, operational constraints, and delayed outcome feedback. The contribution of this resource is deployment governance methodology rather than predictive model development or clinical decision support. The framework is intended for retrospective simulation, audit informed governance research, and methodological evaluation of adaptive decision systems in safety critical domains. The software operates on credentialed datasets such as MIMIC IV but does not include patient level data, derived datasets, or trained model artifacts. Reproduction using real clinical data requires independent approval and credentialed access through PhysioNet.