# CTGV-System-Versions (SOURCE CODE!!!)

> DECISION ENGINE WITH AUDIT AND TRANSPARENCY

**Published by:** [Bear](https://paragraph.com/@bear-3/)
**Published on:** 2026-02-03
**Categories:** computing, topology, network, ia, ai, graphs, decision engine, automation, science, technology, market forecast
**URL:** https://paragraph.com/@bear-3/ctgv-system-versions-source-code

## Content

Developed from CTCE/Gebit and TBA; (https://doi.org/10.5281/zenodo.17049651) CTGV presents a proof of concept (PoC) of cognition through dynamic geometry: an alternative, auditable, and scalable approach to traditional artificial intelligence systems. Based on topological units (Gebits) of distinct formats—DECISION MAKER, RESONATOR, and INHIBITOR—they model complex relationships in a mesh of notification fields, structural interference, and traceable topological transmission. Its architecture is transparent, energy-efficient, and versatile, operating from simple CPUs using graphs and pictograms, allowing its adaptation to multiple computational substrates. Designed for applications that disable explanation, robustness, and verification: anomaly detection, logistics optimization, epidemiological simulation, climate simulations, and critical regulated systems—CTGV is a versatile tool that can be tested, adapted, and applied. Available today for study and development in the repository: (https://github.com/Bear-urso/CTGV-System-V-1.5) The program is a cognitive "mechanism/extension" for governable AI, based on an autonomy framework alternative to blind statistical computing.

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