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docs: update infrastructure files and meta.yaml
Rewrites ENVIRONMENT.md (removes TinyCIMM/SCBF). Adds historical note to REPOSITORY_RESTRUCTURE_PLAN.md. Strips emoji from blueprint READMEs. Updates 3 meta.yaml files to match actual directory contents and current terminology.
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ENVIRONMENT.md

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# Environment and Reproducibility
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This repository targets Python 3.103.12 on Windows, macOS, and Linux. The core models (TinyCIMM, SCBF, legacy CIMM) are pure Python with optional GPU acceleration via PyTorch.
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This repository targets Python 3.10-3.12 on Windows, macOS, and Linux. Experiments are pure Python with optional GPU acceleration via PyTorch.
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Quick start (CPU-only):
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- Install Python 3.11
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- Create a virtual environment
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- Install the base requirements
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- Install PyTorch separately (see below)
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## Quick Start (CPU-only)
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Windows PowerShell (example):
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```
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py -3.11 -m venv .venv
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.\.venv\Scripts\Activate.ps1
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python -m pip install --upgrade pip
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```bash
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python -m venv .venv
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source .venv/bin/activate # or .venv\Scripts\Activate.ps1 on Windows
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pip install --upgrade pip
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pip install -r requirements.txt
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# Install PyTorch last, using the official selector for your CUDA/CPU setup:
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# Install PyTorch separately for your platform:
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# https://pytorch.org/get-started/locally/
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# Example (CPU): pip install torch --index-url https://download.pytorch.org/whl/cpu
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```
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Notes:
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- Torch is intentionally excluded from requirements.txt to avoid platform wheel mismatches. Install it per your CUDA/CPU environment.
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- SCBF uses matplotlib/seaborn; TinyCIMM experiments use pandas/matplotlib; legacy CIMM pulls in scipy/sklearn utilities.
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## Dependencies
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Core experiments use numpy, scipy, matplotlib, and sympy. PyTorch is optional (used by reality-engine and some GAIA experiments).
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PyTorch is intentionally excluded from requirements.txt to avoid platform wheel mismatches. Install it per your CUDA/CPU environment.
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## Related Repos
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Tested baseline (Aug 2025):
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- Python 3.11.9
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- numpy 1.26.x, pandas 2.2.x, matplotlib 3.8.x, seaborn 0.13.x, scipy 1.11.x, scikit-learn 1.4.x, tqdm 4.66.x
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- torch 2.3–2.4 (install per platform)
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| Repo | Purpose | Dependencies |
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|------|---------|-------------|
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| `fracton` | PAC math SDK (70+ modules) | numpy, scipy |
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| `reality-engine` | GPU simulator | PyTorch, numpy |
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| `dawn-models` | GAIA ML models | PyTorch, fracton |
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Per-submodule hints:
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- TinyCIMM: requires torch, numpy, pandas, matplotlib
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- SCBF: requires torch, numpy, scipy, matplotlib, seaborn
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- CIMM (legacy): requires torch, numpy, scipy, scikit-learn, pandas, matplotlib
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## Reproducibility
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Reproducibility:
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- See EVIDENCE_MAP.md for a claim→artifact index
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- Experiments in `foundational/experiments/` are self-contained Python scripts
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- Each experiment directory has a `meta.yaml` with metadata and a `README.md` with results
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- Prefer running experiments inside a fresh virtual env
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- Pin exact versions in a lock file if you snapshot a result for a preprint

REPOSITORY_RESTRUCTURE_PLAN.md

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# 🌌 Dawn Field Theory Repository Restructure Plan
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# Dawn Field Theory Repository Restructure Plan
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**Status:** Community Review Phase
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**Target Date:** Q4 2025 - Q1 2026
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**Author:** Peter Groom, Dawn Field Institute
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> **Historical document from September 2025.** The repo restructure happened differently than planned here — repos were split into dawn-field-theory, fracton, reality-engine, dawn-models, GRIM, kronos-vault, and dawn-infrastructure as separate git repositories in the core_workspace. CIP protocol references are superseded. This document is preserved for historical reference only.
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**Status:** Superseded
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**Original Target Date:** Q4 2025 - Q1 2026
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**Author:** Peter Groom, Dawn Field Institute
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**Last Updated:** September 8, 2025
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blueprints/README.md

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# 🧠 Blueprints Directory
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# Blueprints Directory
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This directory contains early-stage **architectures**, **protocols**, and **technical concepts** developed alongside the core DAWN Field Theory and Infodynamics framework.
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## 🚀 Recent Advances (2025)
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- **AI Detection Blueprint**: New adaptive, feedback-driven neural models for explainable AI and blackbox mitigation (see `AI_detection/`).
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- **Protocol-driven validation**: Blueprints now integrate with the Cognition Index Protocol (CIP) for reproducible, auditable experiments.
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- **Transparency metrics**: Designs include entropy, fractal dimension, and neuron activity tracking for interpretability.
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---
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## 📁 Contents
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* `AI_detection/` – 🤖 Adaptive, feedback-driven neural models for explainable AI.
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* `balance_based_energy_generation/` – ⚡ Blueprints and simulations for programmable carbon-based energy harvesting.
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* `nuclear_containment/` – ☢️ Designs and simulations for nuclear-scale entropy containment using field-theoretic principles.
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Early-stage architectures, protocols, and technical concepts developed alongside the Dawn Field Theory framework. These are speculative applications — not validated theory.
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## 🔍 What You'll Find Here
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## Contents
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These are documents and designs that:
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- Explore **how to implement** the ideas from the main framework
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- Sketch out future tools, platforms, and interfaces
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- May form the basis of future standalone modules or projects
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- **Showcase recent enhancements** such as:
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- Adaptive feedback and dynamic field control (see nuclear containment v2 roadmap)
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- Gradient-aware and hierarchical containment architectures
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- Predictive, noise-resilient, and multi-channel energy management strategies
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- Modular, extensible simulation frameworks for rapid prototyping
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| Directory | Description |
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|-----------|-------------|
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| `AI_detection/` | Adaptive, feedback-driven neural models for explainable AI |
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| `balance_based_energy_generation/` | Programmable carbon-based energy harvesting blueprints |
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| `nuclear_containment/` | Nuclear-scale entropy containment using field-theoretic principles |
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## 🚧 What This Folder Is For
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## What This Folder Is For
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This folder is intended to:
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- Provide **a home for in-progress, applied ideas**
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- Let others explore, comment on, or even build upon these ideas with transparency
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- Give me the room to move forward confidently without worrying about idea appropriation
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- **Serve as a living incubator** for concepts I may continue developing, but also as a resource for others to draw inspiration from or implement independently
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- A home for in-progress, applied ideas
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- Exploratory designs that may form the basis of future standalone projects
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- Open for dialogue, exploration, and future development
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Many of these ideas are still evolving — and this is a way to open them up to **dialogue, exploration, and future development**, without locking them into premature implementation or hiding them behind closed doors.
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Many of these ideas are still evolving. They are opened up for conversation and creative reuse without locking them into premature implementation.
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## 🛡️ Licensing
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## Licensing
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This folder has a different license than the rest of the repository.
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It’s designed to:
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- Protect the **integrity and intent** of these designs
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- Allow for **open conversation and copyleft-friendly development**
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- Prevent misuse or premature reimplementation without consent
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See [`LICENSE.md`](./LICENSE.md) in this folder for details.
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This folder has a different license than the rest of the repository. See `LICENSE.md` in this folder for details.
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## 📬 Interested?
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If you’d like to discuss any of the ideas here, open an issue or reach out.
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Curiosity, respectful dialogue, and creative reuse are welcome—whether you want to collaborate, adapt, or simply get inspired.
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If you'd like to discuss any of the ideas here, open an issue or reach out.

blueprints/balance_based_energy_generation/README.md

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# Balance-Based Energy Generation
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# Balance-Based Energy Generation
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This directory contains the theory, simulation, and practical blueprints for **carbon-based energy harvesting** using balance field and entropy control principles from the DAWN Field Theory framework. Here, energy is extracted from advanced carbon substrates (graphite, graphene, CNTs) by leveraging recursive feedback and informatic field modulation—enabling programmable, efficient, and safe energy systems.
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## 📚 Contents
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## Contents
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- **balance_based_energy_generationv1.py / v2.py**: Core simulation scripts for baseline and advanced control strategies
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- **carbon_energy_theory.md**: Foundational theory and control models (QBE, RBF, sigmoid, oscillatory)
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## 🧬 Core Concept
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## Core Concept
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Traditional batteries and fuel cells rely on chemical reactions.
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**Balance-based energy generation** uses electromagnetic pulses to disrupt the internal informational balance of a carbon lattice, releasing energy as both electromagnetic and thermal output.
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## 🧪 What’s Inside
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## What’s Inside
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### Theory & Models
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## 🏗️ Blueprints
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## Blueprints
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- **Consumer Prototype:**
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Modular, safe, and low-cost—ideal for portable or emergency power ([consumer_energy_blueprint.md](consumer_energy_blueprint.md))
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## 🌱 Why This Matters
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## Why This Matters
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- **Programmable Energy:**
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Move beyond static batteries—enable adaptive, intelligent energy systems
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## 🤝 Get Involved
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## Get Involved
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This folder is a living incubator for ongoing work and a resource for others to explore, adapt, or build upon.
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See the [LICENSE.md](../LICENSE.md) for terms.

blueprints/nuclear_containment/README.md

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# ☢️ Nuclear Containment Blueprints
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# Nuclear Containment Blueprints
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This directory contains the evolving design, theory, and simulation work for **nuclear-scale entropy containment** using the DAWN Field Theory framework. Here you’ll find both foundational experiments and advanced enhancements aimed at stabilizing high-entropy events—such as nuclear detonations—through informatic field control rather than traditional material barriers.
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## Contents
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- **v1/**: First-generation blueprint, theory, math, and simulation results
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- **v2/**: Roadmap and planned enhancements for next-generation containment
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## Core Concept
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Traditional nuclear containment relies on physical resistance. Here, we explore a paradigm shift:
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**Containment via recursive, feedback-driven informational fields** that convert entropy into structure, dynamically stabilizing even extreme energy releases.
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## What’s Inside
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## Why This Matters
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## 🤝 Get Involved
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## Get Involved
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foundational/docs/meta.yaml

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schema_version: 2.0
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directory_name: docs
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description: 'Foundational documentation, theoretical papers, and supporting materials
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for Dawn Field Theory.
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'
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description: >
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Foundational documentation for Dawn Field Theory. Contains theoretical essays
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spanning the project's history (April 2025 through current), empirical alignment
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studies, bridge documents, and published preprints. Current framework docs are
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from Dec 2025+; earlier docs are preserved as historical foundation.
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semantic_scope:
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- documentation
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- theory
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- documentation
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- theory
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files:
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- README.md
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- '[id][F][v0.1][C5][I5][R]_imperfection_engine_epistemic_collapse_dawn_field_repo.md'
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- '[id][F][v1.0][C5][I5][E]_arithmetic_identity_and_structural_novelty_in_computation.md'
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- '[id][F][v1.0][C5][I5][E]_landauer_erasure_cost_superfluidity_viscosity.md'
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- '[id][F][v1.0][C5][I5][E]_phase_shifts_classical_vs_emergent_collapse.md'
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- '[id][F][v1.0][C5][I5][E]_symbolic_collapse_recursive_field_pruning.md'
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- '[id][F][v1.0][C5][I5][E]_symbolic_entropy_collapse_geometry_foundation.md'
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- '[id][F][v1.0][C6][I6][E]_tinycimm_navier_macro_emergence_sec_inverse_unified_complexity.md'
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- '[m][D][v0.9][C3][I3]_recursive_calculus_and_entropy_regulation.md'
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- '[m][F][v0.1][C5][I5]_symbolic_entropy_collapse_and_hodge_mapping.md'
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- '[m][F][v1.0][C4][I4]_recursive_tree.md'
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- '[m][F][v1.0][C4][I4]_super_fluid.md'
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- '[m][F][v1.0][C4][I5]_bifractal_time_emergence.md'
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- '[m][F][v1.0][C4][I5]_dawn_field_theory_recursive_balance_field.md'
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- '[m][F][v1.0][C4][I5]_herniation_hypothesis.md'
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- '[m][F][v1.0][C4][I5]_pi_harmonics.md'
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- '[m][F][v1.0][C4][I5]_reality_as_herniation_precipitate.md'
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- '[m][F][v1.0][C4][I5]_recursive_balance_field.md'
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- '[m][F][v1.0][C4][I5]_superfluid_informational_crystallization.md'
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- '[m][F][v1.0][C5][I5][R]_recursive_symbol_collapse.md'
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- '[m][F][v1.1][C4][I5]_recursive_entopy.md'
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- '[m][F][v2.0][C5][I5]_collapse_dynamics_in_entropic_fields.md'
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- README.md
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- FOUNDATIONAL_AMPLIFICATION_CORRECTION.md
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- '[id][F][v0.1][C5][I5][R]_imperfection_engine_epistemic_collapse_dawn_field_repo.md'
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- '[id][F][v1.0][C5][I5][E]_arithmetic_identity_and_structural_novelty_in_computation.md'
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- '[id][F][v1.0][C5][I5][E]_landauer_erasure_cost_superfluidity_viscosity.md'
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- '[id][F][v1.0][C5][I5][E]_pac_confluence_xi_unified_framework.md'
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- '[id][F][v1.0][C5][I5][E]_phase_shifts_classical_vs_emergent_collapse.md'
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- '[id][F][v1.0][C5][I5][E]_symbolic_collapse_recursive_field_pruning.md'
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- '[id][F][v1.0][C5][I5][E]_symbolic_entropy_collapse_geometry_foundation.md'
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- '[id][F][v1.0][C5][I5][E]_vcpu_empirical_validation_computational_naturalness.md'
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- '[id][F][v1.0][C5][I5][R]_universe_internal_reorganization_unified_framework.md'
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- '[id][F][v1.0][C6][I6][E]_pac_sec_as_information_dynamics.md'
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- '[id][F][v1.0][C6][I6][E]_tinycimm_navier_macro_emergence_sec_inverse_unified_complexity.md'
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- '[m][D][v0.9][C3][I3]_recursive_calculus_and_entropy_regulation.md'
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- '[m][F][v0.1][C5][I5]_symbolic_entropy_collapse_and_hodge_mapping.md'
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- '[m][F][v1.0][C4][I4]_recursive_tree.md'
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- '[m][F][v1.0][C4][I4]_super_fluid.md'
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- '[m][F][v1.0][C4][I5]_bifractal_time_emergence.md'
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- '[m][F][v1.0][C4][I5]_dawn_field_theory_recursive_balance_field.md'
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- '[m][F][v1.0][C4][I5]_herniation_hypothesis.md'
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- '[m][F][v1.0][C4][I5]_pi_harmonics.md'
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- '[m][F][v1.0][C4][I5]_reality_as_herniation_precipitate.md'
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- '[m][F][v1.0][C4][I5]_recursive_balance_field.md'
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- '[m][F][v1.0][C4][I5]_superfluid_informational_crystallization.md'
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- '[m][F][v1.0][C5][I5][R]_recursive_symbol_collapse.md'
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- '[m][F][v1.1][C4][I5]_recursive_entopy.md'
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- '[m][F][v2.0][C5][I5]_collapse_dynamics_in_entropic_fields.md'
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- '[m][F][v2.2][C5][I5][E]_pre_field_recursion_resonance_driven_emergence.md'
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child_directories:
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- bridges
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- docx
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- empirical_alignment
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- preprints
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- bridges
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- docx
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- empirical_alignment
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- preprints

meta.yaml

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schema_version: '2.0'
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directory_name: dawn-field-theory
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description: >
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Dawn Field Theory foundational repository containing core theoretical framework,
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experimental validations, and research documentation. References implementation
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repositories: dawn-models (production models), cip-core (navigation protocol),
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and fracton (computational language).
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Dawn Field Theory foundational repository. Core theoretical framework (PAC/SEC/RBF/MED),
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117+ experiments across 11 milestones, and published papers (PACSeries on Zenodo).
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Derives physical constants from information-theoretic first principles.
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repository_role: foundational_theory
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semantic_scope:
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- physics
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- open_science
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- field_theory
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- infodynamics
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- consciousness_research
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- theoretical_framework
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- information_theory
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- README.md
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- CLAUDE.md
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- CITATION.cff
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- CONTRIBUTION.md
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- ENVIRONMENT.md
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- EPISTEMIC_CORRECTIONS_REGISTRY.md
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- LICENSE
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- LICENSE_APPENDIX.md
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- MISSION.md
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- REGISTRY_TERMS.md
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- REPOSITORY_RESTRUCTURE_PLAN.md
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- dawn-field-theory.md
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- infodynamics.md
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- devkit
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- mcp
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- resources
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- tools

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