Calibration-guided data fusion: A framework for understanding data contribution in multi-source inference through efficient Bayesian optimization with application to virus dynamics parameter estimation

We introduce a framework that uses simulation-based calibration to assess data contribution in multi-source inference, systematically evaluating what each data source contributes to parameter estimation. When inference is fast enough, calibration becomes a practical diagnostic tool. We demonstrate t