Unityverse Kernel Spec v1.0: A Compression–Selection Framework for Consciousness, Learning, and Coherence

This release presents Unityverse Kernel Spec v1.0, a normative, versioned specification defining a compression–selection framework for consciousness, learning, and coherent systems.The kernel formalizes consciousness as a selection process operating over an invariant substrate (ONE), mediated by a finite lens-stack with variable compression (gain) and coupling parameters. Stable experiential and learning states are characterized as compression regimes—attractor basins in the control parameter space—while transitions between regimes are governed by explicit return (recompression) constraints.The specification includes:• a minimal ontology and mathematical formalism for compression–selection dynamics• regime-level observables and invariants• a concrete control realization (Coherence Learning OS) specifying physiological thresholds and decision rules for learning optimization• test vectors and constraints that distinguish the framework from static or purely representational modelsThis document is not a philosophical essay or empirical report. It is a kernel specification intended to support implementation, testing, and extension across domains including education, human–machine interaction, and artificial intelligence training.No claims of new particles, forces, or violations of established physical laws are made. “Dimensionality” is treated as effective degrees of freedom arising from compression state, not literal spatial extension.Versioning is explicit. Future releases may add implementation modules and domain-specific extensions while preserving kernel invariants.