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Preprint . 2026
License: CC BY
Data sources: Datacite
ZENODO
Preprint . 2026
License: CC BY
Data sources: Datacite
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The Voynich Protocol v3.0: Statistical Analysis of MS408 as a Formal Technical System

Authors: Bezvesilnyi, Bohdan;

The Voynich Protocol v3.0: Statistical Analysis of MS408 as a Formal Technical System

Abstract

Abstract This paper presents a comprehensive statistical analysis of the Voynich Manuscript (MS408), proposing its interpretation as technical documentation of a formal system rather than encrypted natural language. Through rigorous quantitative analysis of 116,755 words from the complete EVA transcription, we demonstrate that MS408 exhibits statistical properties inconsistent with natural language but strongly aligned with formal technical protocols. Key Statistical Findings: Type-Token Ratio (TTR): 0.130 — Places MS408 strictly within the range of formal languages (0.1–0.3), effectively ruling out natural language encryption (typically 0.4–0.6). Zipf’s Law: $\alpha = 1.27 \pm 0.07$ — Matches technical documentation and server logs, distinct from natural narrative ($\alpha \approx 1.0$). Structural Formality: 38.7% of the corpus is concentrated in the top-10 bigram patterns. Sequential Determinism: 47% of word-pair sequences show deterministic repetition, characteristic of procedural protocols. Conclusion: Using Bayesian inference, we assess the "Systemic Protocol" hypothesis at 85% probability. We propose a paradigm shift from cryptanalytic to systems-engineering approaches in Voynich research. This document (v3.0) supersedes previous hypotheses regarding the "R&D Logbook".

Keywords

Linguistics/statistics & numerical data, Finite State Machine, Medieval Technology, Formal Languages, Information Theory, Protocol Analysis, Voynich Manuscript, Information Theory/history, Computational Linguistics, Zipf's Law, Type-Token Ratio, Historical Cryptography, Bayesian Analysis, MS408, Artificial Syntax, Digital humanities

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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