An axiomatic 32-bit nested closed-loop logic framework for AI reasoning calibration, data protocol design, and biological homeostasis modeling.
The Canonical Logic System (CLS) defines the geometry, mechanics, and operational rules of a Nested Closed Loop System. It uses integer boundaries (
This repository is an open-source framework intended for scientists, engineers, corporate research teams, logic artists, autistic savants, and the curious. It provides a non-ordinary, scale-invariant lens to evaluate complex, closed-loop, physical, and digital systems.
- AI Reasoning Calibration & System Prompts: Enforces deterministic logic and zero-hallucination state tracking in Large Language Models (LLMs) and agentic pipelines.
- Data & Communication Protocols: Offers a zero-loss, 32-bit state-machine architecture for low-latency packet routing, loss-free data transmission, and distributed ledger clock synchronization.
- Cellular & Cognitive Equilibrium Medicine: Serves as a mathematical reference model for studying metabolic homeostasis, local energy containment, and neural stability in biological systems.
- Physics & Systems Analysis: Provides a discrete geometric lens for examining closed-loop thermodynamic engines and scale-invariant systems.
├── LICENSE
├── README.md
├── system_prompt/
│ └── canonical_logic_system.txt # Raw CLS specifications for LLM insertion
├── examples/
│ ├── python_orchestrator.py # LLM-as-Translator/Database integration
│ └── flask_warmup_app.py # Flask app with blind CLS calibration