Structural Decipherment Without Lexical Recovery: A Cross-Validated Morphological Analysis of the Voynich Manuscript
- 1Dominik Research Institute
Abstract
The Voynich Manuscript exhibits strong statistical regularities, but the distinction between recoverable grammar and recoverable lexical meaning remains unresolved. This study asks how far a progressively frozen, cross-validated analysis can reconstruct the manuscript’s internal word-building system without assigning meanings from illustrations, candidate languages, or post-hoc English paraphrase.
Using canonical transcription, protected holdout partitions, alternate-transcription replication, exact host substitutions, and adversarial stopping rules, the analysis recovers a cumulative left-edge morphology, a transferable inventory of 39 surface CORE-0 stem/bodies, reproducible host-by-right-state coupling, a stable K/T referential contrast, and a directed network among powered lexical cores.
The 39-core inventory predicts protected-frame combinatorics and content-blind contextual fingerprints out of sample, while attempts to decompose these bodies into a deeper transferable root layer fail. Nine recurring hosts show strongly replicated coupling to EY/EEY/EDY right-edge states, supporting a distributed morphological paradigm rather than independent left- and right-side systems. A 28-node directed CORE network also replicates across canonical calibration, untouched Holdout, and alternate-transcription tests, yielding neutral outbound- and inbound-biased stem classes without requiring part-of-speech or semantic assignments.
On the project’s fully constrained 1,609-line benchmark, 12,299 of 12,495 positions are role-naturalizable (98.4314%), leaving 196 opaque positions. This percentage is explicitly a conditional benchmark-maturity statistic, not a measure of literal plaintext recovery or manuscript-wide translation accuracy.
Repeated attempts to cross from structural organization to ordinary lexical meaning—including deeper-root induction, topic clustering, functional-neighborhood anchoring, local lexical syntax, illustration matching, source-language fitting, and prospective semantic transfer—fail the project’s promotion criteria. The resulting contribution is therefore a structural decipherment rather than a lexical one: a reproducible grammatical and morphological architecture together with an empirically identified lexical-identifiability ceiling.
The work extends, but is distinct from, the earlier controlled-translation release at DOI 10.5281/zenodo.22049207.
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BibTeX
@misc{dominik2026structural,
title = {{Structural Decipherment Without Lexical Recovery: A Cross-Validated Morphological Analysis of the Voynich Manuscript}},
author = {Matthew Dominik},
howpublished = {Zenodo},
year = {2026},
month = oct,
doi = {10.5281/zenodo.23444474},
url = {https://zenodo.org/records/23444474},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Structural Decipherment Without Lexical Recovery: A Cross-Validated Morphological Analysis of the Voynich Manuscript
AU - Matthew Dominik
PY - 2026
DA - 2026/10/18
PB - Zenodo
DO - 10.5281/zenodo.23444474
UR - https://zenodo.org/records/23444474
AB - The Voynich Manuscript exhibits strong statistical regularities, but the distinction between recoverable grammar and recoverable lexical meaning remains unresolved. This study asks how far a progressively frozen, cross-validated analysis can reconstruct the manuscript’s internal word-building system without assigning meanings from illustrations, candidate languages, or post-hoc English paraphrase. Using canonical transcription, protected holdout partitions, alternate-transcription replication, exact host substitutions, and adversarial stopping rules, the analysis recovers a cumulative left-edge morphology, a transferable inventory of 39 surface CORE-0 stem/bodies, reproducible host-by-right-state coupling, a stable K/T referential contrast, and a directed network among powered lexical cores. The 39-core inventory predicts protected-frame combinatorics and content-blind contextual fingerprints out of sample, while attempts to decompose these bodies into a deeper transferable root layer fail. Nine recurring hosts show strongly replicated coupling to EY/EEY/EDY right-edge states, supporting a distributed morphological paradigm rather than independent left- and right-side systems. A 28-node directed CORE network also replicates across canonical calibration, untouched Holdout, and alternate-transcription tests, yielding neutral outbound- and inbound-biased stem classes without requiring part-of-speech or semantic assignments. On the project’s fully constrained 1,609-line benchmark, 12,299 of 12,495 positions are role-naturalizable (98.4314%), leaving 196 opaque positions. This percentage is explicitly a conditional benchmark-maturity statistic, not a measure of literal plaintext recovery or manuscript-wide translation accuracy. Repeated attempts to cross from structural organization to ordinary lexical meaning—including deeper-root induction, topic clustering, functional-neighborhood anchoring, local lexical syntax, illustration matching, source-language fitting, and prospective semantic transfer—fail the project’s promotion criteria. The resulting contribution is therefore a structural decipherment rather than a lexical one: a reproducible grammatical and morphological architecture together with an empirically identified lexical-identifiability ceiling. The work extends, but is distinct from, the earlier controlled-translation release at DOI 10.5281/zenodo.22049207.
ER -