Theoretical, Empirical, and Computational Analysis of the Core Emotion Framework

This paper presents a comprehensive analysis of the Core Emotion Framework (CEF), a structural-constructivist paradigm that conceptualizes human affect as a highly continuous, continuous system of information processing operating as a hardware-independent "Human Operating System" (Human OS). Moving beyond classical Western dualism and sequential cognitive appraisal models, the CEF resolves the tension between biological essentialism and psychological constructionism by mapping raw interoceptive inputs onto a canonical functional architecture. This architecture consists of exactly ten irreducible operators distributed across three somatic-evaluative regions: the Cephalic/Head Center, Cardiac/Heart Center, and Enteric/Gut Center. To transition the model from a qualitative therapeutic modality to a computationally tractable framework, the CEF utilizes the mathematics of quantum cognition. Within this high-dimensional Hilbert space, a person's global emotional state is represented as a state vector, while psychopathology (such as the GoodPerson Anxiety Pattern or emotional solipsism) is formalized as non-separable operator entanglement. Empirical validation from a large-scale Phase 1 scenario-based rating study (N=826) confirms the psychometric distinctiveness of the operators under acute situational stress, while qualitative feedback highlights critical boundaries regarding semantic overlap, structural fatigue, and construct omissions. Ultimately, the CEF provides an integrated transdiagnostic pipeline for clinical psychology via rotational somatic exercises, alongside a modular algorithmic blueprint for engineering synthetic affect in artificial general intelligence (AGI). Keywords Core Emotion Framework (CEF); Human Operating System (Human OS); Structural-Constructivist Architecture; Somatic Centers; Quantum Cognition; Operator Entanglement; GoodPerson Anxiety Pattern (GPAP); Emotional Flexibility; Synthetic Affect; Affective Neuroscience.