22-09-2025, 08:44 AM
I know the conversation up to now was quite technical, but a simpler briefing is this.
I fed the Voynich transcription into an automatic topic model that doesn’t know the manuscript’s sections, illustrations, or my expectations. After a light clean-up (removing single-character tokens and a tiny set of forms that occur everywhere) the model was asked to find recurring “themes” in the text and to say how strongly each paragraph uses each theme. I also let it account for obvious style factors (language A/B and scribal hands) in how much of each theme appears, without letting those factors change what the themes are.
With that setup, the model settled on six themes that line up with the well-known sections: Herbal, Pharmaceutical, Biological (balneological), Astronomical/Zodiac, Marginal Stars, and a Text/Cosmological connector. When the manuscript switches section, the dominant theme usually flips at the same boundary. Language and hands still matter, but mainly in how much of each theme is used; they don’t redefine the themes themselves. This pattern shows up clearly in both the heatmaps and the “timeline by folio” plots.
What does that mean? In plain terms, the clustering the model finds is not random. The themes it discovers match the book’s content divisions, even though the model wasn’t told about those divisions. That is hard to reconcile with pure gibberish. It doesn’t prove a reading, but it does suggest there’s systematic structure in the text beyond scribal style.
It is also hard to reconcile with independent gibberish per theme (as if each section invented its own nonsense). The themes reuse stable families of forms across many paragraphs, the dominant theme flips exactly at section boundaries, and related sections share overlaps (e.g., Herbal with Pharmaceutical). Even after letting language and scribal hands nudge the mixtures, the same theme vocabularies persist. That pattern looks like shared structure running through the book, not several unrelated streams of invented text.
I fed the Voynich transcription into an automatic topic model that doesn’t know the manuscript’s sections, illustrations, or my expectations. After a light clean-up (removing single-character tokens and a tiny set of forms that occur everywhere) the model was asked to find recurring “themes” in the text and to say how strongly each paragraph uses each theme. I also let it account for obvious style factors (language A/B and scribal hands) in how much of each theme appears, without letting those factors change what the themes are.
With that setup, the model settled on six themes that line up with the well-known sections: Herbal, Pharmaceutical, Biological (balneological), Astronomical/Zodiac, Marginal Stars, and a Text/Cosmological connector. When the manuscript switches section, the dominant theme usually flips at the same boundary. Language and hands still matter, but mainly in how much of each theme is used; they don’t redefine the themes themselves. This pattern shows up clearly in both the heatmaps and the “timeline by folio” plots.
What does that mean? In plain terms, the clustering the model finds is not random. The themes it discovers match the book’s content divisions, even though the model wasn’t told about those divisions. That is hard to reconcile with pure gibberish. It doesn’t prove a reading, but it does suggest there’s systematic structure in the text beyond scribal style.
It is also hard to reconcile with independent gibberish per theme (as if each section invented its own nonsense). The themes reuse stable families of forms across many paragraphs, the dominant theme flips exactly at section boundaries, and related sections share overlaps (e.g., Herbal with Pharmaceutical). Even after letting language and scribal hands nudge the mixtures, the same theme vocabularies persist. That pattern looks like shared structure running through the book, not several unrelated streams of invented text.
![[+]](https://www.voynich.ninja/images/collapse_collapsed.png)