STAE-1: Subconscious Threat Anticipation Engine — Technical Specification and Methods Document

STAE-1 (Subconscious Threat Anticipation Engine) is a formal systems-engineering architecture that models human intuitive threat detection as a multi-layered computational pipeline. The architecture treats gut feeling and intuition as the outputs of a signal-processing engine operating below the bandwidth of conscious attention. The architecture comprises six sequential processing modules (M1–M6) and a dual feedback structure (M7). This document presents the complete STAE-1 v0.3 technical specification. Version 0.3 extends v0.2 with the following additions: formal signal dynamics specification using the Carlo Calculus framework (Carlo, 2026), incorporating the Carlo Derivative, Infinity as Direction, and Zero as Attractor; the Carlo Interface Threshold alpha_conscious, formally specifying the boundary at which STAE-1 subconscious output crosses into conscious contradiction receivable by the Carlo cognitive layer; a failure mode to curvature mapping integrating the Carlo Unified Functional; inter-individual variation specification for the free parameter set; a primary testable prediction unique to the three-band concurrent temporal architecture; a Carlo Integration Protocol defining the non-causal diagnostic bridge between STAE-1 and the Carlo framework; and a responsible use statement. Biological grounding citations include Damasio's Somatic Marker Hypothesis, LeDoux's subcortical threat pathway, Porges' Polyvagal Theory, and Kahneman's System 1 framework. Version 0.3 incorporates the complete Carlo framework across five published works. Together, STAE-1 and the Carlo framework constitute a complete architecture from raw environmental signal through subconscious processing through somatic activation through conscious contradiction through cognitive loop resolution through identity evolution. A device integration appendix describes a three-component hardware implementation across wearable optical, biometric, and processing modules.