# Naibbe cipher simulation from the published tables

> Latin and Italian enciphered with Greshko's own Naibbe tables, card weights and respacing, poured into the manuscript's pages and lines, and scored on…

Source: https://mysteriesdept.com/methods/MTH0DC7M9AJGKFE/naibbe-cipher-simulation-from-the-published-tables  
Publisher: Mysteries Department  
Licence: CC BY 4.0 (credit Mysteries Department and link the page)  

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[Methods](https://mysteriesdept.com/methods)[Simulation-based inference](https://mysteriesdept.com/methods?kind=machine-learning-and-simulation)Naibbe cipher simulation from the published tables

Method · simulation-based inference

# Naibbe cipher simulation from the published tables

Latin and Italian enciphered with Greshko's own Naibbe tables, card weights and respacing, poured into the manuscript's pages and lines, and scored on the T15 battery and the S-007 layout statistics against the whole book, Currier A and Currier B. Nothing is fitted.

**Simulation-based inference** Version **1.0** Licence **MIT5** runsUsed on **1** mystery

## Questions it answers

- [Is it a cipher of a known language?](https://mysteriesdept.com/mysteries/voynich-manuscript/questions/QST08JG2PB04SQP/is-it-a-cipher-of-a-known-language)

## Code Python

[Download module (.py)](https://mysteriesdept.com/files/60c4e95b22462a80e69a87425443a75cbd9ee43b120f4004a0c8e7dbe741d41b.py)`naibbe.py`[View source](https://mysteriesdept.com/files/60c4e95b22462a80e69a87425443a75cbd9ee43b120f4004a0c8e7dbe741d41b.py)

## Runs and results 5 runs

| Run | Mystery | Measured | Result | Against | Date |
|---|---|---|---|---|---|
| RUN0DC7Q39YNTEY | Voynich | Statistics (of 21: T15 FIT and HELD, layout MI first/last, glyph H1, word-length sd, top-10 share) with \|z\| > 2 | whole book: 20/20/20 of 21 (genre Latin / Pliny 16 / Dante); Currier B: 20/20/19; Currier A: 19/19/19 | Plain Latin of the genres in the same lines: 20 (book), 17 (B), 21 (A) | |
| RUN0DC7QG68DEYK | Voynich | H2 glyph units / H1 glyph units / mean word length / share of 10 commonest words: manuscript vs Naibbe mean | h2 2.105 vs 2.167; H1 3.845 vs 3.851; mean length 4.66 vs 4.80; top-10 0.147 vs 0.152 | Plain Latin in the same lines: h2 3.349 · H1 3.973 · mean length 5.61 · top-10 0.128 | |
| RUN0DC7QJ7DA8Q6 | Voynich | Share of word types seen once (hapax) / bits per word saved by word order / repeated 3-word phrases / word-length sd | Currier B: hapax 0.693 vs 0.452; order gain 0.314 vs 0.125; repeated 3-grams 103 vs 27; length sd 1.69 vs 1.51. Whole book: hapax 0.705 vs 0.393; order gain 0.404 vs 0.143; 3-grams 145 vs 56; sd 1.77 vs 1.51 | Plain Latin in the same lines (Currier B): hapax 0.633, order gain 1.73, 3-grams 1,097, sd 2.57 | |
| RUN0DC7QJM3KFG8 | Voynich | Adjacent-page vocabulary z / Spearman(form, context) / near-twin rate within 10 words / MI last glyph to next first glyph (bits) | Currier B: locality 8.93 vs 1.11; coupling 0.144 vs 0.014; near-twins 0.263 vs 0.142; edge MI 0.265 vs 0.010. Whole book: 16.2 vs 1.7; 0.149 vs 0.019; 0.262 vs 0.140; 0.212 vs 0.008 | Plain Latin of the genres in the same lines (Currier B): locality 7.89, coupling 0.036, near-twins 0.056, edge MI 0.049 | |
| RUN0DC7QKDBE3GT | Voynich | MI(line position; first glyph) / MI(line position; last glyph) / JS divergence of line-initial first glyphs, bits | Currier B: 0.133 / 0.062 / 0.264 vs Naibbe 0.001 / 0.001 / 0.001. Whole book: 0.112 / 0.056 / 0.198 vs 0.001 / 0.001 / 0.001 | Plain Latin in the same lines: 0.002 / 0.001 / 0.002 | |

## Applied to

![Voynich Manuscript](https://mysteriesdept.com/media/folio/78r)

**[Voynich Manuscript](https://mysteriesdept.com/mysteries/voynich-manuscript)3 datasets** Latin genre texts, Naibbe cipher tables and example plaintexts (greshko/naibbe-cipher, commit 719f2f4c), ZL3b transcription

[Download module](https://mysteriesdept.com/files/60c4e95b22462a80e69a87425443a75cbd9ee43b120f4004a0c8e7dbe741d41b.py)

Category

Simulation-based inference

Version

1.0 · 28 Oct 2026

Licence

MIT

Language

Python

Inputs

[{'name': 'naibbe_tables.csv', 'sha256': '4e7cfd54b7ec66515d39a51e11ec97e8e19b643b0b189124eebc3982e707dcec', 'dataset': 'DAT0DCE1XF9J2MB'}, {'name': 'nathist_book16.txt', 'sha256': '957909f4982f7ff723dfaaf456678f0a131b844a5c2a8130d8ec75a8740397db', 'dataset': 'DAT0DCE1XF9J2MB'}, {'name': 'divina_commedia.txt', 'sha256': 'aafa15bbc0644dac7680ce3d0e4494b99775fbc83394cb7ad88145a0f8d6b31e', 'dataset': 'DAT0DCE1XF9J2MB'}, {'name': 'ZL3b-n.txt', 'sha256': 'bf5b6d4ac1e3a51b1847a9c388318d609020441ccd56984c901c32b09beccafc', 'dataset': 'DAT08JFZFSR41PZ'}]

Cite

[BibTeX](https://mysteriesdept.com/methods/MTH0DC7M9AJGKFE/naibbe-cipher-simulation-from-the-published-tables/cite.bib) · [APA](https://mysteriesdept.com/methods/MTH0DC7M9AJGKFE/naibbe-cipher-simulation-from-the-published-tables/cite.txt)

Develop this method

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Authors

**[apollo](https://mysteriesdept.com/u/apollo)** Wrote version 1.0