Need advice for testing of hypotheses related to the self-citation method

[Torsten]

satisfied with an explanation of why "the whole thing cannot work" (dixit ReneZ).

Very brief:

The high level of repetitions is not the most conspicuous artifact of the text. Perhaps not even the second most conspicuous, but probably the third. This is so subjective that I don't want to argue about it.

Using this as the prime method for the text generation, while it does nothing towards the most conspicuous aspects (low entropy, word pattern - same thing really) is my biggest problem.

But this risks getting us off topic.

Short answer: The Self-Citation Method was developed by me through the systematic reverse-engineering of the word patterns identified in the Voynich Manuscript.

I did also ask ChatGPT for a longer answer:
From a structural and statistical perspective, self-citation naturally leads to both low entropy and characteristic word patterns.

1. What is the Self-Citation Method?
It refers to generating new text by:

• Copying previously written words or fragments
  
• Making small, predictable modifications
  
• Repeating this process recursively over the growing text
  

2. Why Does That Lead to Low Entropy?
Entropy, in information theory, is a measure of unpredictability or information content.
Self-citation with limited modification produces:
- High repetition of sequences
- Restricted "alphabet" or symbol combinations in context
- Predictable transitions between words or fragments (Note: There are no structure changing modification rules like reordering of glyphs.)
- A biased distribution of word lengths and glyph patterns
The result: The text statistically mirrors a low-entropy system — similar to a compressed code, repetitive ritual text, or artificially constrained system.

3. Why Does That Produce Word Patterns?
The Voynich manuscript exhibits:

• Clusters of similar-looking "words"
  
• Systematic variations
  
• Repeated fragments that mimic prefixes, suffixes, or stems
  

Self-citation directly causes this because:

• When copying an existing word and slightly modifying it, families of related words emerge
  
• Frequent reuse of certain fragments (e.g., "qo", "ol", "chedy") occurs naturally
  
• Sequences of similar words appear close together, reflecting recent "copy targets"
  

Thus, the observable word patterns — both at the micro (within lines) and macro (across sections) levels — are a direct byproduct of the self-referential text generation process.

4. Illustrative Analogy
Imagine a program that:

1. Starts with a few invented "words": qokeedy, chedy, dain
   
2. At each step:
   • Selects a previous word or fragment
     
   • Modifies it slightly (replaces glyphs/adds or removes prefixes)
     
   • Appends the result to the text
     

Over thousands of iterations:

• Some fragments become dominant
  
• Similar-looking words proliferate
  
• Novel sequences appear rarely
  
• Overall entropy remains low
  
• The "vocabulary" stabilizes into recognizable word families
  

Exactly what we observe in the Voynich manuscript.

Conclusion:
The self-citation hypothesis does explain the most conspicuous aspects of the Voynich manuscript:

• Low entropy emerges naturally through repetitive, constrained copying
  
• Word patterns arise through systematic, recursive modifications
  
• No need for an independent mechanism to impose these features
  

Thus, if the self-citation process is properly constrained and recursive, it not only explains text generation but necessarily produces the statistical and structural anomalies seen in the manuscript.