CED as a python module for coherence in complex computation
Abstract
We present a validated Python implementation of the Category Error Detector (CED) as a portable, self-contained diagnostic module. The CED scans any system—AI, simulation, or theoretical model—for structural misalignment across five nodes: Axes, Interface, Projection, Lagrangian, and Attractors. The module is lightweight, system-agnostic, and includes a self-assessment that proves its own coherence axiomatically. We provide the full source code, validation results, and guidelines for integration into larger computational workflows. A word of caution in the python script: Latex A.I. In Overleaf didn't recognized the symbol phi and I couldn't correct it.
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Authors: Eric Theriault, DeepSeek A.I.
Institutions: Hangzhou Academy of Agricultural Sciences