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"Is the Voynich a Hoax?" — Five test say NO

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  • "Is the Voynich a Hoax?" — Five test say NO
• "Is the Voynich a Hoax?" — Five test say NO

• "Is the Voynich a Hoax?" — Five test say NO

  Vuk88 > 1 hour ago

  Hello everyone,
  
  I would like to share with you the latest revision of my work on the statistical infrastructure of Beinecke MS 408.
  I tried to structure the paper following a strict, step-by-step logical thread.
  I also want to take this opportunity to sincerely thank Prof. @Jorge_Stolfi for his insights in previous threads, which I found incredibly useful for better calibrating the morphological parameters.
  
  You can download the PDF + the Python codes for verification directly from Zenodo at this link:
  You are not allowed to view links. Register or Login to view.
  
  For those who don't have the time to read everything right away, here is a quick summary of the 5 key points (all fully supported by their respective tests and charts inside the paper):
  
  1. Reduplications are not random (Logistic Regression) 
  Running Monte Carlo tests (1,000 iterations, being careful to avoid data leakage across single dialects), the numbers speak clearly. Word reduplication is not a distraction error by the scribe, but responds to precise syntactic rules. Furthermore, cross-linguistic benchmarking shows that this behavior is quantitatively superimposable on that of isolating/Austronesian languages (like Indonesian).
  
  2. 1-to-1 Compression and Greenberg Index 
  I applied Prof. Stolfi's Core Alphabet to clean the text from false entropy peaks generated by the EVA system. By feeding the data to the Zellig Harris algorithm, we get an Index of Synthesis of 2.86. Considering we are talking about very short words (3-4 glyphs on average), this certifies that we are dealing with 3 rigid morphological slots (Onset + Nucleus + Coda). It looks exactly like the profile of a monosyllabic isolating language.
  
  3. The anomaly of the missing pages 
  By mapping the syntax, we can see that the density of the markers (the reduplicated words) is not uniform, but it spikes exactly near the 14 folios that were historically removed from the quire. This leads me to hypothesize that they acted as references/pointers to reading keys or legends that are now lost. (Note: this analysis was validated by cross-referencing the dialects across the entire volume)
  
  4. Falsification Test I (Copy-Mutate & Skew Squares) 
  I rigorously tested the stochastic Copy-Mutate model (Null Hypothesis) and it fails the Contextual Asymmetry test: it cannot replicate the real cross-dependencies we see between prefixes (like o-, y-) and suffixes (-edy, -eedy)
  
  5. Falsification Test II (Ghost Roots) 
  I tried to permute the letters within the dictionary. The text rejects these permutations with a ratio of 200 to 1 (12,450 attested real words vs. only 60 "ghost" ones). It is very hard to believe in a random generation with such strict phonotactic constraints.
  
  I would really appreciate knowing what you think of these specific mathematical metrics, and I would also be absolutely thrilled to see these tests pushed to their limits
  -Alfredo

• RE: "Is the Voynich a Hoax?" — Five test say NO

  Vuk88 > 58 minutes ago

  Hi @JoeyB,
  
  That's exactly the risk I was trying to avoid. Both instances of the duplicate are stripped before the classifier ever sees the text — the model is completely blind to them.
  The logic in the code provided with the paper is straightforward. When the function detects a repeated word, it flags the page as "infected" but doesn't add the word to the cleaned list. The next iteration catches the second instance too, so both get dropped:
  
  if i < len(words) - 1 and words == words[i+1]:
  
      is_infected = True  # flag the page, but don't add the word
  else:
      if i == 0 or words != words[i-1]:
          cleaned_words.append(words)  # continue with next word
   
  With your example qokedy qokedy chol daiin, both tokens are gone. The model only sees chol daiin and predicts the page label from the surrounding 30 word context alone.
  The fact that it still reaches p < 0.05 against 1,000 shuffled baselines is what makes the result interesting … the duplicates clearly co-occur with a specific syntactic environment, not at random.
  Thanks for pushing on this, it's a fair point.
  Alfredo

• RE: "Is the Voynich a Hoax?" — Five test say NO

  eggyk > 44 minutes ago

  Why is the double word density a basic sine wave? Surely that's not right? 
     
  
  vs in your previous thread:
     
  
  Perhaps I have misunderstood something. I don't understand 90% of the jargon in the paper.

• RE: "Is the Voynich a Hoax?" — Five test say NO

  oshfdk > 18 minutes ago

  I didn't really check the paper, I just would like to comment on the general premise. Unless the paper provides a deciphering which produces a sensible plaintext, it's impossible to use a statistical test as an argument that the manuscript is NOT a hoax. No statistical test ever will be able to show that the manuscript is not a hoax.
  
  One of the easiest way to create a plausible hoax is to get a real text as the source. For example, I can take each second letter (including spaces, skipping punctuation) of the beginning of this very post and produce a hoax text, which probably will pass a lot of statistical tests:
  
  IDDTRAL HC H AE UTWUDLK OCMETO H EEA RMS NESTEPPRPOIE EIHRN HC RDCSASNIL LITX T MOSBET S TTSIA ETA NAGMN HTTEMNSRP SNTAHA OSAITCLTS VRWL EAL OSO HTTEMNSRP SNTAHA N FTEESETWYT RAEAPASBEOXI OGTARA ETA H OREFREAPEICNTK AHSCN ETRICUIGSAE KPIGPNTAINFTEBGNIGO HSEYPS N RDC OXTX HC RBBYWL ASALTO TTSIA ET
  
  It has some repeating words (SNTAHA which is made from "iS NoT A HoAx"), it would have some topic clustering. It would have weird statistics and the original text may or may not be recoverable, but I guess it would look more like a meaningful text than not, because it is based on a meaningful text. Yet, it is not designed to convey any meaning, just to give an impression of a meaningful text, which makes it a hoax.

• RE: "Is the Voynich a Hoax?" — Five test say NO

  Vuk88 > 8 minutes ago

  @Eggyk
  
  You're completely right, it's a huge mistake. I haven't slept in a couple of days and I made a total mess.
   In the first draft I wanted to redo the graph to make it cleaner, and that sine wave is literally just the test trace I used for the script to calibrate the alignment with the missing pages.
   I eventually decided not to use it because the one with the raw spikes was visually better. Then I messed up renaming the draft file and accidentally put the test image in the paper too... 
  I'm removing it from the paper right now. 
  Thank you so much for pointing it out right away. 
  Sorry for the misunderstanding
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