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feat: Complete academic metadata update with DOI and ORCID
- Add ORCID ID (0009-0007-6116-0613) to all metadata files - Update pyproject.toml with academic description and keywords - Add Citation and Zenodo URLs to project metadata - Update CITATION.cff with version 9.0.2 and complete info - Update .zenodo.json with publication date and version - Add prominent ORCID display in README citation section Repository now has complete academic metadata for proper citation and discoverability.
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.zenodo.json

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{
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"title": "TNFR-Python-Engine: Resonant Fractal Nature Theory Implementation",
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"description": "Canonical computational implementation of TNFR - a paradigm shift from modeling 'things' to modeling coherent patterns that persist through resonance. This Python package provides the complete TNFR physics engine including the 13 structural operators, unified grammar validation (U1-U6), and the four canonical structural fields (Φ_s, |∇φ|, K_φ, ξ_C). Features include: nodal equation dynamics (∂EPI/∂t = νf·ΔNFR), structural potential confinement, phase synchronization, and multi-scale coherence analysis.",
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"version": "9.0.2",
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"publication_date": "2025-11-13",
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"doi": "10.5281/zenodo.17602861",
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"creators": [
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{
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"name": "FMG",
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"affiliation": "TNFR Research"
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"affiliation": "TNFR Research",
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"orcid": "0009-0007-6116-0613"
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}
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],
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"keywords": [

CITATION.cff

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title: "TNFR-Python-Engine: Resonant Fractal Nature Theory Implementation"
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message: "If you use this software, please cite it as below."
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type: software
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version: "9.0.2"
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date-released: "2025-11-13"
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authors:
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- given-names: "FMG"
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family-names: ""
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affiliation: "TNFR Research"
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orcid: "https://orcid.org/0009-0007-6116-0613"
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repository-code: "https://github.com/fermga/TNFR-Python-Engine"
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url: "https://pypi.org/project/tnfr/"
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doi: "10.5281/zenodo.17602861"
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license: "MIT"
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keywords:
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- "TNFR"
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- "Resonant Fractal Nature Theory"
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- "complex systems"
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- "network dynamics"
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- "structural operators"
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- "coherence theory"
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- "physics simulation"
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abstract: >-
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Canonical computational implementation of TNFR - a paradigm shift from
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modeling 'things' to modeling coherent patterns that persist through resonance.

README.md

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author = {FMG},
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year = {2025},
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url = {https://github.com/fermga/TNFR-Python-Engine},
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doi = {10.5281/zenodo.17602861}
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doi = {10.5281/zenodo.17602861},
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note = {ORCID: 0009-0007-6116-0613}
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}
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```
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**DOI**: [10.5281/zenodo.17602861](https://doi.org/10.5281/zenodo.17602861)
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**DOI**: [10.5281/zenodo.17602861](https://doi.org/10.5281/zenodo.17602861)
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**Author ORCID**: [0009-0007-6116-0613](https://orcid.org/0009-0007-6116-0613)
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### Minimal Example
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```python

pyproject.toml

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[project]
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name = "tnfr"
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dynamic = ["version"]
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description = "Modular structural-based dynamics on networks."
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description = "Resonant Fractal Nature Theory (TNFR) - Computational engine for modeling coherent patterns through resonance dynamics"
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readme = "README.md"
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requires-python = ">=3.10"
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license = "MIT"
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license-files = ["LICENSE.md"]
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authors = [{ name = "fmg" }]
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authors = [{ name = "FMG", orcid = "0009-0007-6116-0613" }]
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keywords = [
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"TNFR", "complex systems", "fractals", "resonance",
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"networks", "structural dynamics",
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"structural analysis"
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"TNFR", "Resonant Fractal Nature Theory", "complex systems", "fractals", "resonance",
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"networks", "structural dynamics", "structural operators", "coherence theory",
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"physics simulation", "emergence", "synchronization", "zenodo", "doi"
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]
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classifiers = [
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"Programming Language :: Python :: 3",
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tnfr-is-prime = "tnfr.tools.tnfr_is_prime_cli:main"
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[project.urls]
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Homepage = "https://pypi.org/project/tnfr/"
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Homepage = "https://github.com/fermga/TNFR-Python-Engine"
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Repository = "https://github.com/fermga/TNFR-Python-Engine"
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PyPI = "https://pypi.org/project/tnfr/"
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Citation = "https://doi.org/10.5281/zenodo.17602861"
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Zenodo = "https://zenodo.org/records/17602861"
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Issues = "https://github.com/fermga/TNFR-Python-Engine/issues"
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Documentation = "https://fermga.github.io/TNFR-Python-Engine/"
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GPT = "https://chatgpt.com/g/g-67abc78885a88191b2d67f94fd60dc97-tnfr-resonant-fractal-nature-theory"
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[tool.setuptools.package-data]

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