Natural-language plausibility is a property of surface form. A sentence is plausible if it pattern-matches against the kind of thing a competent author would write. Mathematical logic is a property of structure. A statement is logically valid if it is the consequence of explicit premises under sound inference rules, regardless of how it sounds. The two operate on entirely different axes, and conflating them is the single most common failure mode of modern reasoning systems.
A plausibility engine optimises the surface and lets the structure follow as best it can. A logic engine optimises the structure and produces surface as a byproduct. The two engines can occasionally produce identical sentences while meaning entirely different things — one because the engine inferred the result, the other because the engine guessed it would sound right. The difference becomes visible the moment you ask either system to defend its claim.
Quantm is positioned firmly on the logic axis. The structural derivation comes first, and the surface form is generated to faithfully describe it. When the structure is uncertain, the engine refuses rather than improvises. That refusal is unfamiliar to users trained on plausibility engines, but it is the only behaviour consistent with deterministic accuracy. A system that always answers is a system that occasionally fabricates. A system that sometimes refuses is a system whose answers can be trusted.