Admissibility Boundary – Pilot Loop 01 / Observing continuity concentration in a bounded interaction loop

This pilot note introduces a minimal experimental structure for observing the admissibility boundary in iterative interaction systems. The admissibility boundary is defined here as the point at which a system ceases to sustain multiple trajectories with equal continuity, while still preserving overall coherence and without introducing explicit constraints. Rather than focusing on decision outcomes or formal commitments, the approach tracks how continuity distributes across iterations within a bounded interaction loop (input → response → feedback → refinement). The central hypothesis is that admissibility shifts do not emerge through visible exclusion of alternatives, but through a gradual concentration of stability driven by reinforcement patterns across iterations. The note provides:– a minimal loop setup,– observable indicators for trajectory presence and continuity distribution,– and a first operational definition of the boundary as a detectable structural transition. This pilot serves as a foundational step toward a systematic method for identifying admissibility conditions in AI-assisted and human-in-the-loop decision environments.