AA-CDE Concept Disclosure Note (CDN-01)

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Authors: Yuliia Neziat
Cited by: 0

Abstract

This technical note establishes prior art for a domain-independent methodological layer for forecasting depth-driven architectural collapse in AI reasoning pipelines and quantum circuits using cumulative frequency modeling, regime breakpoint detection, and extreme-value tail analysis. The disclosed material defines a new architectural governance layer that operates above physical and semantic execution substrates. No implementation details, proprietary parameters, source code, datasets, calibration procedures, or internal heuristics are disclosed.

Fields of Study & Subjects

Software System Performance and Reliability Adversarial Robustness in Machine Learning Artificial Intelligence Applications

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
11 January 2026
Language
EN