Bacterialized Gematria Experimental Result 01: Historical Divergence under Sequential Textual Exposure

Abstract

This paper reports the first executed computational proof-of-concept and cross-corpus replication of Bacterialized Gematria, a population-based symbol–number system in which an initially fixed A=1 through Z=26 correspondence table is transformed into a historically contingent numerical ecology capable of mutation, horizontal numerical transfer, context-sensitive selection, dormancy, reactivation, and extinction, thereby testing whether numerical identity can become dependent upon the ordered history of textual exposure rather than remaining a static function of visible sign identity. In the initial experiment, a 47-sentence, 24,437-letter corpus was processed under original, reversed, randomly permuted, and within-sentence-shuffled histories across eight independent seeds, producing nonzero and reproducible divergence only when relational and state-dependent mechanisms were active, while both static gematria and mutation-only controls remained exactly order invariant. The complete system produced a mean original-versus-reverse normalized Earth Mover’s Distance of 0.003063 ± 0.000816, whereas disabling horizontal numerical transfer reduced divergence to 0.000278 ± 0.000019, identifying transfer as the strongest tested amplifier of historical differentiation under the present parameterization, while selection acted primarily as a stabilizing constraint and dormancy provided a smaller but reproducible contribution to path dependence. A subsequent replication using two non-overlapping, exposure-matched regions of Xenobacillus glossophagii reproduced the same architecture of effects, with original-versus-reverse divergence of 0.002801 ± 0.000327 and 0.002685 ± 0.000575 in Blocks A and B respectively, approximately tenfold reductions under transfer ablation, and exact invariance in static and mutation-only controls. Unchanged visible words consequently acquired different evolved numerical values after alternative exposure histories, supporting the operational proposition that numerical identity can be represented as a function of accumulated system state rather than as a timeless lookup value. These results establish a reproducible computational model of history-dependent mutational gematria, but they do not demonstrate semantic, mystical, predictive, or biologically literal significance and remain limited by English-language corpora, designed parameters, and the need for replication across unrelated, multilingual, non-alphabetic, and synthetic symbolic environments.