An item with one edge inherits that edge's ratio as its entire score basis. A single `>` loss puts the item near 33% of the winner. To express "different category" you need either a much wider ratio or more edges.
Single-edge-failure is the more useful insight. Generous defaults are a design choice; the failure mode is what falls out of that choice when data is thin. Chain-decay is a separate observation about flow propagation.
Categorical-threshold is the practical takeaway from single-edge-failure. Once the failure is named, the fix is named; the threshold is just empirical calibration of how wide the ratio needs to be.