"Semantic Correlation Analysis of the Voynich Manuscript Using the 33×3 Causevic Method (Partial Corpus Test – 12%)"

This study presents a Python-based implementation of semantic correlation testing for the 33×3 Causevic Method, applied to a 12% representative corpus derived from publicly available digitized Arabic-Latin medical manuscripts (11th–15th century).The results demonstrate measurable semantic alignment between transliterated Voynich tokens and historical terminology extracted from Avicenna’s Canon Medicinae and related sources.The code enables transparent replication and further validation of the 33×3 model’s linguistic consistency.