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| Quire 13. Text first. Pictures after. |
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Posted by: dashstofsk - 14-12-2025, 02:31 PM - Forum: Physical material
- Replies (16)
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Has it ever been discussed that in quire 13 it seems that the pictures might have been done after the text had been written? The writer left spaces for the drawings to be added later? And all the tubes, ponds and flower pot things were then sized to fit the available space? Here is some evidence.
- f79r and f79v. The text margin is straight and does not flow around the contours of the pictures.
- f81r. Space had been left on the right of the page for drawings that were never made. There wasn't enough space at the top to fully draw the bath tub thing that was intended. The bath tub at the bottom has also not been completed. Perhaps the writer just got annoyed with himself and abandoned this page.
- f84v. The text on the right does not align with the bulk of the text. If text came last then it would have aligned. So it looks like that text was added after the drawings were done, and these drawings after the main text was done.
- f75r. If drawings came first then it is unlikely the first drawing would have been done slanty.
- f82v and other pages. The drawings on the right hand sides were done cramped. Had they been done first they would have commanded more space and the writing would have stopped short.
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| Functional Reconstruction of the Voynich Manuscript as a Modular Medical System (DOI- |
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Posted by: juananAI - 13-12-2025, 10:03 PM - Forum: The Slop Bucket
- Replies (3)
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Hello everyone,
I would like to share a recently completed research project on the Voynich Manuscript (Beinecke MS 408), now formally published with DOI, which proposes a non-linguistic, functional reconstruction of the manuscript as a modular medical system rather than a narrative or literary text.
The central hypothesis of the study is that the Voynich Manuscript operates as a 15th-century professional vademecum: a structured expert system integrating diagnosis, materia medica, and therapeutic protocols. Instead of pursuing phonetic or linguistic decipherment, the research focuses on structural engineering, internal consistency, and functional correlations between the manuscript’s sections.
The analysis treats the manuscript as an operational system in which different sections interact through a defined workflow, rather than as isolated or symbolic components.
Key contributions of the study include:
• Identification of a relational workflow linking diagnosis (zodiacal and anatomical sections), ingredients (herbal folios), and preparation/execution protocols (recipe section).
• Proposal of a binary pharmaceutical code based on recurring stars, containers, and humoral logic (hot/dry vs. cold/wet), consistently applied across multiple sections.
• Evidence for rigid syntactic templates in the recipe text, supporting the interpretation of the script as technical notation or procedural encoding rather than natural language prose.
• Functional reconstruction of the final recipe section (folios 103r–116v), organized according to the medieval anatomical principle a capite ad calcem, and consistent with contemporary medical traditions such as Salernitan humoral theory.
The full research is openly available here:
DOI: You are not allowed to view links. Register or Login to view.
Figshare (open access): You are not allowed to view links. Register or Login to view.
In addition, I have prepared a short explanatory video that summarizes the methodology and main structural findings. This video is intended solely as a visual aid to the published paper, not as a substitute for the formal analysis.
I am sharing this work here for critical discussion and feedback, particularly regarding the proposed structural model, its internal consistency, and its compatibility with known late-medieval medical and pharmacological practices.
Best regards,
Juanan
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| Bifolio as a functional unit? |
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Posted by: Bernd - 13-12-2025, 12:32 PM - Forum: Analysis of the text
- Replies (32)
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Assuming the VM originally existed as a stack of loose bifolia, has it ever been tested if there are textual similarities within a bifolio (4 pages on the same vellum sheet)? I'm aware the sample size is probably too small for proper statistics but it would be interesting to see if there are patterns that link the text on a bifolio compared to single pages.
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Hidden animals in the roots |
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Posted by: Rafal - 13-12-2025, 12:16 PM - Forum: Imagery
- Replies (26)
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Forgive me if it was discussed before but I haven't seen a global thread about it, just some discussions about individual pictures.
Several times it was suggested that there are hidden animals and other creatures in the plant roots. Not in all roots but in several ones.
I browsed the manuscript and thought about it myself and came to this:
Of course there is such thing as pareidolia. Let's quote a classic philosopher:
“There is an universal tendency among mankind to conceive all beings like themselves, and to transfer to every object, those qualities, with which they are familiarly acquainted, and of which they are intimately conscious. We find human faces in the moon, armies in the clouds; and by a natural propensity, if not corrected by experience and reflection, ascribe malice or good- will to every thing, that hurts or pleases us.”
David Hume
So are these animals there or are these just quirks of our brains?
I will tell you my opinion. For me it's too much to be a random coincidence. These animals are real and intentional.
I am trying to make a poll to see your opinions.
And if there are animals indeed, what are the implications?
One quite obvious one to me is that the artist wasn't copying some herbal faithfully but rather freestyling and improvising.
Another one is that at least some plants are imaginary.
And there is a question - why was he doing it? Just for fun (entirely possible for me) or could there be something deeper behind it?
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| Working my way to a semantic word analysis |
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Posted by: mxv456 - 12-12-2025, 01:51 PM - Forum: Analysis of the text
- Replies (12)
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Hey folks,
I've been binging Koen's videos on Youtube over the last week, great stuff!
Obviously that means I'm a Voynich novice, but I did use computational linguistics during my PhD at the MPI in Nijmegen, Netherlands, so I couldn't help but dig my fingers into the data :)
I'm not claiming any novelty but I haven't seen the different analysis steps put together in one place so I figured I might as well publish it here. (However, I do think in the end, I have some interesting results that I didn't see anywhere else... but more about this below and in the next post.)
I put the data, scripts and a small analysis report on a dedicated Github repository, if somebody wants to have a deeper look: You are not allowed to view links. Register or Login to view.
My main idea for this round is to perform an TF-IDF analysis. This is a statistical tool where you count how often words occur over the whole text, vs the individual text segments (pages). With this method, one can (approximately) distinguish "content words" from "function words". Content words are those that are specific to a particular topic, like "Voynich" or "Quantum", while function words are words that show up everywhere, like "the", "of", "and", etc. I think it would be tantalizing to produce a list of Voynich words, where we can guess, from section and illustration cues, what they might mean, given where they show up. (Although I don't think it would bring us closer to deciphering the text, it would be fun.)
Down the line, maybe I have time to produce a visual tool where people can explore how words cluster in certain portions of the text. Not quite as fancy as the amazing tool on voynichese.com but in the same spirit.
I'm currently getting into working with LLMs (building them, not talking to Chat GPT) and I am very curious if one can use these tools to identify semantic clusters of Voynich words. Tbd.
I obviously haven't read everything there is on Voynich, but I did my best to go through voynich.nu and Bowern and Lindemann (2020) as well as the latest and pinned posts on this forum, to get a base understanding what's commonly known and what's currently under discussion. I'm looking forward to learn more from you.
I want to start by stating my base preconceptions/assumptions when I went into the analysis, as well as some questions that maybe you can help me with.
Assumptions:
1. The text is real in the sense that somebody in the 15th century wrote something down to communicate information to somebody else.
2. The transcription is reasonably good and conveys the textual content of the VMS to an overwhelming degree, so we can base an analysis on it.
3. The words are words in the sense that they can, through translation, combination, compression, augmentation by auxiliary information, or some other process, be rendered into a language that someone at some time spoke. If there is a cipher, it did not jumble words by moving word boundaries or similar shenanigans.
4. Letters are only meaningful with regards to the manuscript itself. They cannot be identified in a one-to-one manner with any language.
5. The manuscript was written by several scribes/authors, possibly at different times, possibly without knowing each other. The known separations are Currier A and B as well as the 5 Hands (Davis, Lisa Fagin. 2020).
6. There is no hope of me ever decrypting the text by myself since I have none of the necessary skills to actually understand any language that the authors spoke, even less the manuscript itself.
Questions:
1. The whole analysis is based on IT2a-n.txt from You are not allowed to view links. Register or Login to view. Is this the correct choice? As far as I understand, it's a version of the TT transcription, but I don't know what the state of the art is. I noticed that the transcription used on voynichese.com is different and in some places more complete, but I don't know.
2. How is the interaction between "fan groups" like this one and the academic community? From what I saw in the videos, there is a fairly good collaboration, but I still wonder. I know that for some topics that garner so much public interest, there can be a lot of tension.
3. I had trouble finding a "definitive" distinction of pages into Currier A and B. I don't know if that's because it is not fully defined, if there is disagreement or if I just didn't look at the right places.
Base results:
Before we get to the good stuff, I want to post the base analysis as a sanity check but also so they are all in one spot. As I said, these are all well known but it's good for me to see the data myself, so maybe also for others.
I split up all the analysis steps by Currier A and B. Going in, I did not have any idea how close both languages are. My initial assumption was actually that they are as different as German and Latin. These stats helped me understand it better.
[EDIT: I made a mistake in my Currier A/B separation for these plots. Corrected plots in my reply on page 2.]
1. The word length plots for Currier A and B with the distributions for 4 reference languages. (I just chose 4 languages that were easily accessible to me.)
![[Image: word_length_stats.png?raw=true]](https://github.com/Marvel4U/Voynich_semantic_exploration/blob/master/plots/word_length_stats.png?raw=true)
2. The known Zipf distribution of word frequencies with reference languages
![[Image: Zipf_stats.png?raw=true]](https://github.com/Marvel4U/Voynich_semantic_exploration/blob/master/plots/Zipf_stats.png?raw=true)
3. Bigram heatmap.
This one was interesting to me because it shows a very close correspondence between Currier A and B. I expected a much bigger variation.
![[Image: bigram_heatmap_a_b.png]](https://github.com/Marvel4U/Voynich_semantic_exploration/raw/master/plots/bigram_heatmap_a_b.png)
As a reference looked at the bigram statistics of the reference languages and one can see that they vary much much more from each other, compared to the currier A and B.
![[Image: bigram_heatmap_ref_shared.png]](https://github.com/Marvel4U/Voynich_semantic_exploration/raw/master/plots/bigram_heatmap_ref_shared.png)
4. Word start and end bigrams/trigrams
The bigrams and word-initial trigrams did not show that much irregularity but the word-end trigrams clearly shows the famous -edy ending for Currier B
![[Image: word_end_trigrams_a_b.png]](https://github.com/Marvel4U/Voynich_semantic_exploration/raw/master/plots/word_end_trigrams_a_b.png)
What did surprise me is that the -edy ending is also among the most common endings in the Currier A script. From what I read and saw, I assumed that it is almost exclusive to the Currier B. Does that mean that I (a) simply misunderstood or (b) chose the wrong page split between currier A and B?
My current split is defined by the code below. Input is very welcome.
Code: CURRIER_A_RANGES = [("f1r", "f24v"), ("f31r", "f31v"), ("f88r", "f90v1"), ("f100r1", "f116r"), ]
CURRIER_A_SINGLES = ["f25r", "f25v", "f32r", "f32v", "f33r", "f34r", "f34v", "f67r2", "f67v1", "f67v2", "f91v"]
CURRIER_B_RANGES = [ ("f26r", "f30v"), ("f35r", "f39v"), ("f75r", "f84v"), ("f93r", "f96v"), ]
CURRIER_B_SINGLES = ["f68r1", "f68r2", "f68v1", "f68v2"]
I'll leave it at that for now. I'm curious how the interaction in the community here works and if I'll hear from anybody. I'm still preparing the plots for the TF-IDF analysis, as I said, I actually think they are quite interesting. I will add them as reply when I'm done.
Until then, cheerio,
Marvin.
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| Testing AI on a Context‑Free Excerpt from My Voynich Translation |
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Posted by: Malatin_1 - 11-12-2025, 09:51 PM - Forum: Theories & Solutions
- Replies (14)
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Last February, I made a breakthrough in my research on the Voynich manuscript and was able to identify its original language. It has been a long journey toward complete translations, but now I can translate entire sentences from the work. I base my translations directly on grammar, using meanings drawn from a dictionary.
Today I wanted to test how well an AI can analyze a text without any background information. To do this, I took a short passage from my own translation and gave it to the AI in complete isolation. I did not reveal which text it came from, what language it was originally written in, or what era it belonged to. The AI was only given the words and their basic meanings.
The purpose of the experiment was to see whether an AI could draw conclusions based solely on the text itself – without any clues about its origin.
The result was surprisingly successful. The AI was able to determine which language group the text belonged to, even though it knew nothing about its background. It didn’t need the original manuscript, the context, or even the knowledge that it was a translation. A single text fragment was enough.
The experiment showed that AI can recognize linguistic and cultural features even when the text is completely disconnected from its original environment. At the same time, it confirmed that my translation is not arbitrary, but based on a correct interpretation of the source text.
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