Computational methodology and verification pipeline for historical manuscript analysis using the Fixed Vector Shorthand Model (FVSM).
See the codeIn scientific research, reproducibility is the ultimate shield against skepticism. We have engineered the repository so that any independent critic or researcher can verify our adversarial control scores on their own machine in seconds.
Ensure you have Python installed, clone the repository, and execute the following command in your terminal:
python adversarial_control_test.py
# Voynich Project
An open-source Python automation suite and computational linguistic analysis of the Voynich manuscript.
> Read the complete breakdown and findings in our [White Paper](./white_paper.md).
## Overview
This repository contains the complete codebase, validation scripts, and findings designed to invite community peer review and collaboration.
* Explore the analysis tools in `src/`
* Review output data in `outputs/`
* Read full documentation in `white_paper.md`
## Methodological Framework: Fixed Vector Shorthand Model (FVSM)
The **Fixed Vector Shorthand Model (FVSM)** treats the Voynich manuscript as a structured operational, inventory, and astronomical tracking matrix.
* **Character-to-Value Mapping:** The model maps specific manuscript glyphs to fundamental structural values (`T`, `I`, `R`, `D`, `A`, `O`, `S`, `C`, `F`, `P`). Rather than arbitrary substitution, these mappings function as shorthand primitives designed for rapid data logging and metric tally isolation.
* **Vector Reversal & Token Processing:** The automation suite processes raw interlinear transcriptions (sourced from datasets like `voynich.nu`) by applying directional token reversals to account for compressed shorthand writing habits.
* **Automated Validation:** Mass trial scripts isolate metric tallies and convert ambiguous glyph strings into a coherent, standardised ledger format.
## Golden Output Sample
Below is a sample decoded ledger output showcasing a processed section of the manuscript, translating raw tokens into structured operational values:
| Raw Token / Folio | Processed Vector | Translated Ledger Output |
| f1r | T-I-R-D-A | Unit Tracker - Initial Folio Ledger Entry |
=======
# Voynich_Project: Fixed Vector Shorthand Model (FVSM)
(Update README with professional FVSM framework overview)
Python
91.1%
Rich Text Format
8.9%
Computational methodology and verification pipeline for historical manuscript analysis using the Fixed Vector Shorthand Model (FVSM).
See the codeIn scientific research, reproducibility is the ultimate shield against skepticism. We have engineered the repository so that any independent critic or researcher can verify our adversarial control scores on their own machine in seconds.
Ensure you have Python installed, clone the repository, and execute the following command in your terminal:
python adversarial_control_test.py
# Voynich Project
An open-source Python automation suite and computational linguistic analysis of the Voynich manuscript.
> Read the complete breakdown and findings in our [White Paper](./white_paper.md).
## Overview
This repository contains the complete codebase, validation scripts, and findings designed to invite community peer review and collaboration.
* Explore the analysis tools in `src/`
* Review output data in `outputs/`
* Read full documentation in `white_paper.md`
## Methodological Framework: Fixed Vector Shorthand Model (FVSM)
The **Fixed Vector Shorthand Model (FVSM)** treats the Voynich manuscript as a structured operational, inventory, and astronomical tracking matrix.
* **Character-to-Value Mapping:** The model maps specific manuscript glyphs to fundamental structural values (`T`, `I`, `R`, `D`, `A`, `O`, `S`, `C`, `F`, `P`). Rather than arbitrary substitution, these mappings function as shorthand primitives designed for rapid data logging and metric tally isolation.
* **Vector Reversal & Token Processing:** The automation suite processes raw interlinear transcriptions (sourced from datasets like `voynich.nu`) by applying directional token reversals to account for compressed shorthand writing habits.
* **Automated Validation:** Mass trial scripts isolate metric tallies and convert ambiguous glyph strings into a coherent, standardised ledger format.
## Golden Output Sample
Below is a sample decoded ledger output showcasing a processed section of the manuscript, translating raw tokens into structured operational values:
| Raw Token / Folio | Processed Vector | Translated Ledger Output |
| f1r | T-I-R-D-A | Unit Tracker - Initial Folio Ledger Entry |
=======
# Voynich_Project: Fixed Vector Shorthand Model (FVSM)
(Update README with professional FVSM framework overview)
Python
91.1%
Rich Text Format
8.9%