The approach sits between supervised and unsupervised learning. A little supervision anchors the model, and the unlabelled data supplies scale. The framework names it as its own approach because the evidence question changes: the labelled set is too small to carry the whole evaluation, so the unlabelled set and the assumptions used to exploit it become part of the record. The clause text is not in the public sample, and this page states the approach's logic rather than the clause's wording.
The graph holds this control, the 0 it maps to, and the evidence behind each claim, over MCP and REST.