Remark. Recursive harnesses with fixed evaluators and versions [ftip-00F7]

The finite statements assume a fixed task set, evaluator, versions, and declared budget. They do not transfer to weight learning, RLVR optimization, unbounded self-modification, or capability acquisition without new hypotheses.