Because models lose accuracy and relevance as data and environment change, the organisation defines and validates performance criteria, documents assumptions on expected inputs and incorporates quality checks, creates and monitors anomaly detection, and tunes and retrains models regularly.
The graph holds this control, the 0 it maps to, and the evidence behind each claim, over MCP and REST.