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May 26, 2026Open Access

De Substratis Neuralibus et Reticularibus A Risk-Aware Neuro-Network Routing Substrate for Governed Agentic Execution Toward classification, inhibition, fallback, evidence capture, and route-card proof in agentic AI systems

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Authors

AHAlfredo Medina Hernandez

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Overview

Randomized trial examines route selection strategies in agentic AI systems, indicating enhanced safety and interpretability.

Key Points

  • The research aims to enhance the governability of agentic AI systems by making their path selection visible and interpretable.
  • Developed a risk-aware neuro-network routing substrate called Ratio Ordinis.
  • Separated the orientation function (ORO) from the ordering function (ORDO) for task pressure detection and pathway selection.
  • Introduced a route card schema that outlines selected routes, rejected alternatives, and evidence requirements.
  • Demonstrated improved safety by classifying tasks before action and inhibiting unsafe paths.
  • Provided a formal route-selection model that significantly enhances transparency and testability of AI workflows.
  • Established clear acceptance criteria for implementations, supporting correctable and governable AI systems.

Cite This Study

Alfredo Medina Hernandez (2026) studied this question.

synapsesocial.com/papers/6a1539ccb5d9c58d83e8ce84https://doi.org/10.5281/zenodo.20361885
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