When expanding a node (or computing knowledge at a node) it is possible the derived class can prove that the state corresponding to the node is a proven win or loss.
Note this differs from a terminal node since a terminal node by definition has no children, whereas a proven node can have any number of children.
Any in-tree phase that encounters a proven node is immediately terminated and the result passed back up the tree just as if a playout (with the value corresponding to the proven value) had been performed.
The existence of proven nodes in a SgUctTree does not change the move selection in any way. For example: a node with both winning and losing children will continue to select children without regard to their proven value. This means losing children will not be avoided and winning children will not be chosen except as a result of the playouts recorded as those children are visisted (the values of which would now be perfectly accurate).
Proven values are not currently passed up the tree like in a min-max search. It would be possible to pass back winning moves, that is, mark the parent of winning moves as winning, but it is not possible mark a node as losing if all its moves are losing. This is because it is possible progressive widening (or other heuristics) are being used by the derived state and in such a case it may not be true that all the current children being losses implies the parent state is a loss.