The first three papers in this series built the argument for rethinking how trustworthiness is constructed in AI-enabled research. This paper closes the arc by demonstrating the confidence layer built into a working multi-agent modeling system, where transparency, traceability, selective attention, and calibrated human oversight are each a load-bearing architectural decision, and the assurance record is produced as a byproduct of doing the work.