Regime Science: A Mechanics of Scientific Closure, Translation, and Validity Toward a General Theory of Scientific Regimes

The classical foundations of science formalized internal engines but not their global coordination. Thermodynamics established macroscopic closure through state variables and invariants (energy, entropy) [1–5]. Statistical mechanics provided a probabilistic micro–macro bridge under ensemble assumptions [4–6]. Information theory defined channel capacity and coding under explicit noise models [8,14]. Cybernetics and control formalized feedback, stability, and estimation under model constraints [9,18,19]. Inference theory provided probability as a logic of plausibility and principled model selection [10–12,16,17,32]. Measurement theory formalized realizations, traceability, and uncertainty under declared procedures [20–23]. Each of these advances created a regime: a closure class with admissible states, observables, invariants, approximation rules, and failure modes. What none of these traditions supplied is a mechanics of regimes themselves. There is no canonical object that declares a regime’s closure; no typed algebra of translations between regimes; no graph structure that encodes scientific workflows as paths with bounded uncertainty and intersecting validity domains. As a result, cross-domain reasoning is governed by custom, rhetoric, and convenience rather than by a uniform calculus.