A methodology that makes AI-assisted research transparent, traceable, and structured for independent verification.
-
Updated
Feb 2, 2026 - Python
A methodology that makes AI-assisted research transparent, traceable, and structured for independent verification.
Foundational epistemic doctrine defining the cognitive integrity requirements for AI–human scientific workflows. Establishes the eight axioms of neurotransparency.
Waveframe Labs An independent research organization focused on governance, reproducibility, and epistemic integrity in AI–human scientific workflows. Maintainers of the Aurora Research Initiative (ARI), Aurora Workflow Orchestration (AWO), and CRI-CORE.
Governance, architecture, and epistemic framework for the Aurora Workflow Orchestration ecosystem (AWO, CRI-CORE, and scientific case studies).
Deterministic validator for governed research artifacts and metadata, designed to support reproducible and auditable AI–human workflows.
Add a description, image, and links to the waveframe-labs topic page so that developers can more easily learn about it.
To associate your repository with the waveframe-labs topic, visit your repo's landing page and select "manage topics."