The Boundary Stability Verification Gate (BSVG): A Pre-Dynamic Admissibility Criterion

The Boundary Stability Verification Gate (BSVG) is a formal admissibility operator that determines whether a system boundary remains structurally valid under stress, scale shift, perturbation, or interpretation. The construct distinguishes boundary failure from internal system change and prevents continuation of analysis when boundary integrity is uncertifiable. BSVG functions as a non-interfering classification gate applicable across scientific, logical, mathematical, and observational domains. It does not modify underlying models or laws but constrains interpretation by verifying boundary stability prior to inference. The operator is falsifiable in principle and applies wherever conclusions depend on defined domain limits.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-02-15
DOI
https://doi.org/10.5281/zenodo.18642390
Primary Topic
Model Reduction and Neural Networks
Type
article
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article

The Boundary Stability Verification Gate (BSVG): A Pre-Dynamic Admissibility Criterion

Andrew John Paton
Zenodo (CERN European Organization for Nuclear Research)
Model Reduction and Neural Networks
article

The Boundary Stability Verification Gate (BSVG): A Pre-Dynamic Admissibility Criterion

Andrew John Paton
article en

Abstract

The Boundary Stability Verification Gate (BSVG) is a formal admissibility operator that determines whether a system boundary remains structurally valid under stress, scale shift, perturbation, or interpretation. The construct distinguishes boundary failure from internal system change and prevents continuation of analysis when boundary integrity is uncertifiable. BSVG functions as a non-interfering classification gate applicable across scientific, logical, mathematical, and observational domains. It does not modify underlying models or laws but constrains interpretation by verifying boundary stability prior to inference. The operator is falsifiable in principle and applies wherever conclusions depend on defined domain limits.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 53%
Model Reduction and Neural Networks
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