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February 19, 2026Open Access

UFAL/UBM v0. 1: The Muñoz Number (NM) — A Stability Margin and Reference Benchmark for Long-Context Reliability

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Authors

JRJonatan Muñoz Rodriguez

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Overview

This release introduces a stability margin and benchmarks long-context reliability in adaptive predictive systems, suggesting new reporting standards.

Key Points

  • The aim is to introduce the Muñoz Number as a universal metric for assessing stability in AI and physical systems.
  • Defined the Muñoz Number as a dimensionless stability margin using N_M = -ln(F/C).
  • Developed UBM v0.1, a protocol for reproducible long-context reliability reporting.
  • Implemented KNC reference with methods like quantile binning and isotonic regression.
  • Illustrated dynamic analogy through a dual demonstration involving stability operators.
  • Established a framework for evaluating the stability of predictive systems under informational drive.
  • Provided specifications for independent replication and standardized reporting of long-context reliability.

Cite This Study

Jonatan Muñoz Rodriguez (2026) studied this question.

synapsesocial.com/papers/6996a818ecb39a600b3ee716https://doi.org/10.5281/zenodo.18653103
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