This work presents Integrated Structural Generation Theory (IGS), a minimal unified framework describing emergence, persistence, and decay across physical, biological, and artificial systems. Rather than modeling systems as collections of components, IGS interprets them as evolving structures governed by a generative chain: Difference → Fixation → Information → Meaning → Emergence → Persistence → Decay The framework is built on three core structural variables: - Structural persistence F (t) - Structural density C (x, t) - Connectivity Γ (t) A central concept is structural viability, defined as: R (E) = (C · Γ · dSC/dt) / Θ (E) From this, structural lifespan is defined as: Tₗife = t | R (E, t) > 1 This provides a unified way to describe when systems emerge, remain stable, and decay. The framework is visualized through a complete set of figures (Fig1–Fig10), which cover: - Generative structure (Fig1) - Core variables (Fig2) - Structural dynamics (Fig3–Fig5) - Disease interpretations (Fig6–Fig8) - Structural phase space (Fig9) - Viability threshold crossing (Fig10) In particular, Fig9 introduces a structural phase space (F, C, Γ), where different systems and diseases are interpreted as trajectories, and Fig10 defines the boundary between persistence and decay through R (E, t) =1. All figures are fully reproducible using the provided Python script. This framework does not replace empirical data; it reorganizes its meaning, offering a unified structural interpretation of intelligence, biological organization, and disease.
Koji Okino (Tue,) studied this question.
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