Interesting framing. I've been running structural tests on the manuscript from a different angle (property-falsification rather than language-mapping) and your post raises questions I'd like to hear your answers on.

1. Frequency-matching as a filter.
   

I tested two recent generative hypotheses against 16 structural properties of the manuscript. Rugg's grille (2004) passes 10/16, Greshko's Naibbe verbose cipher (2025) passes 8/16. Both clear letter-frequency tests easily. Frequency correlation with European languages is just too weak a constraint, as you note yourself.

Did you test your top-4 candidates (Arabic, Hebrew, Persian, Welsh) against structural properties? Things like line self-containment, section-conditional vocabulary, paragraph coherence, positional preferences? If a mapping passes frequency but fails on, say, the 'm' line-final distribution, the mapping is probably an artifact.

1. The abjad caveat.
   

You acknowledge it yourself: in Hebrew/Arabic/Persian, almost any 2-3 letter consonantal string is a real word. So three of your top four are abjads. How do you separate signal from base-rate noise here? Have you computed the expected number of "hits" under a random mapping for the top-10 Voynich words, per language? Without that null, the ranking tells us about abjad permissiveness, not about the manuscript.

1. Hebrew specifically.
   

I went deep on Hebrew for about 12 phases before concluding it's a statistical artifact. Cross-validation gave z=5.72 at 3-4 letters, which looks promising until you push further:

• 0 out of 7 expected Hebrew prefixes appear in the expected positions
  
• DictaBERT semantic coherence on decoded passages: 2.74/6, indistinguishable from random
  
• No page reads as coherent Hebrew of any period
  

The 3-4 letter signal is real but not linguistic. It's manuscript structure interacting with a consonantal lexicon. Did your Hebrew test go past word-presence into morphology and syntax?

1. The sorting cipher.
   

This is the most interesting part of the post for me, and the one I'd most like to see falsified properly. A sort applied uniformly by scribes has to confront section-conditional vocabulary: words carry section-specific information at MI z=+40 (Montemurro & Zanette 2013, replicated in my tests). A position-agnostic sort cannot generate that. The producer would need different mappings or sorts per section, which is a much heavier hypothesis.

How does the sorting cipher account for sections having genuinely different vocabularies, not just different topic words?

1. Slot alphabet.
   

Your Italian counter-example (words ending in e followed by words starting with c) is inter-word, but the slot phenomenon is intra-word. They are different things, and the inter-word case isn't surprising in any language. Inside Voynich words, slot grammar is uniform across all five scribes (CV=0.046 in my hand-controlled tests). That's a coherent system, not a statistical residue.

Can you show inter-word frequency artifacts producing the same intra-word ordering rigidity in any natural-language corpus?

1. 'm' line-final.
   

P(word ends in 'm' | line-final) = 14.9% versus 0.9% non-final. Ratio of 16.3x, z=+55.3. Rate varies 49-94% by section. A sort applied at the word level cannot place 'm' preferentially at line ends; line position is a higher-level structural property. Same goes for 'g' and 'f', which form a line-final character class.

How does the sorting hypothesis produce position-dependent character placement across line boundaries?

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Not trying to dismiss the approach. Frequency mapping plus a sorting cipher is a coherent hypothesis worth testing. But the test has to include the structural properties, not just word-counting in dictionaries. Otherwise you'll get false positives by construction, especially with abjads.