This repository is archived as a completed proof-of-concept (v4.0).
The work is permanently recorded via DOI for reproducibility.
Waveframe v4.0 is a workflow demonstration applying
AI Workflow Orchestration (AWO) to a complex scientific problem.
- Physics content is exploratory — not a replacement for ΛCDM
- The focus is on reproducibility, transparency, and auditability
- Outputs are packaged like serious software: figures, notebooks, logs, decision records
Think of Waveframe v4.0 as a case study in AI-assisted research orchestration, not as a final cosmological model.
/Theory– Conceptual framework and derivations/Equations– Equations and assumptions/Notebooks– Python notebooks for model-vs-ΛCDM comparisons/Analysis– Results summaries, figures, CSV outputs/Figures– Generated plots (expansion history, growth factor, etc.)/Docs– Supporting documentation (workflow, logs, falsifiability scaffolds)/Demos– Lightweight apps (Streamlit, report generator)/decisions– Architecture Decision Records (ADRs)
More detailed discussion of the model, scaffolds for falsifiability, and empirical criteria can be found in
Docs/Extended_Methodology.md.
This repository is part of a broader portfolio showing how Aurora Workflow Orchestration (AWO) can scale across domains:
- Aurora Workflow Orchestration (AWO) — defines the orchestration framework
- Waveframe v4.0 — scientific case study Future projects: TBA
- Code: Apache License 2.0 (
LICENSE) - Theory, equations, figures, docs: CC BY-NC 4.0 (
LICENSE-NC.md)
Attribution is required. Commercial use prohibited without permission.
See LICENSE_POLICY.md for scope examples.
Version: Waveframe v4.0 (archived)
Concept DOI (permanent citation):
For reproducibility, always cite the concept DOI above.
This ensures future readers resolve to the correct archived version.
If you use this work, please cite it as:
@software{wright_waveframe_v4_2025,
author = {Shawn C. Wright},
title = {Waveframe v4.0: AI-Orchestrated Proof of Concept in Cosmology},
year = {2025},
publisher = {Zenodo},
version = {v4.0},
doi = {10.5281/zenodo.17041850},
url = {https://doi.org/10.5281/zenodo.17041850}
}© 2025 Waveframe Labs · Independent Open-Science Research Entity · ORCID: 0009-0006-6043-9295 · DOI: 10.5281/zenodo.16872199
Governed under the Aurora Research Initiative (ARI) · Constructed using the AWO methodology