Singularity remains unresolved, but capital cannot wait for an answer. 0 and 1 are the endpoints of a normalized governance range. This is Authorized Intelligence: a pre-execution check testing a proposed parameter against a defined boundary before it becomes action, regardless of which engine — classical or quantum-assisted — produced the proposal. Live: www.0to1doctrine.com This invention is a checkpoint. Every field can speak its own language — physics in joules, medicine in enzyme levels, AI in probabilities. A quantum-assisted credit model could flag an application as low-risk; a classical model, checking the same application, could read it differently. Nothing is necessarily wrong with either result. The problem is that the underlying measures may not share a common decision framework. Defined normalizable parameters can instead be converted into a shared 0-to-1 representation, making relevant differences visible before a consequential decision. This invention creates that common governance layer. WHY THIS KEEPS HAPPENING Every control built for one engine inherits the blind spot of never having questioned what a different engine’s numbers actually mean. Most governance tooling was built to test classical outputs against classical thresholds. It was never built to ask whether a quantum-derived confidence interval, an amplitude-based estimate, or a hybrid pipeline’s result means the same thing the threshold assumes it means. A qubit is not a classical bit behaving like a tiny 0 and 1 — quantum computation uses states and amplitudes; measurement produces a classical outcome, but not necessarily one calibrated the way a classical system expects. A GATE THAT DOES NOT CARE WHICH ENGINE PRODUCED THE NUMBER The check was never on the computation. It was always on the proposed consequence. The 0→1 Doctrine uses 0 and 1 differently from either classical bits or qubits: as endpoints of a normalization range testing a proposed action against a defined