Methodology defining structured workflow topology and reproducibility guarantees for governed research.
Python-based models revealing the harmonic architecture of planetary orbital spacing through the Silver Ratio and Celtic Cross geometry. Supplementary scripts and figures for The Harmonic Architecture of the Solar System: A Silver-Ratio-Based Hypothesis for Planetary Spacing (Gherbi, 2026).
Recursive law learning under measurement constraints. A falsifiable SQNT-inspired testbed for autodidactic rules: internalizing structure under measurement invariants and limited observability.
MCP server for Claude Desktop that applies Popperian falsifiability to verify claims from social media, news and blogs — with real academic sources, not opinions.
Informational interpretation of quantum mechanics, gravity, and cosmology based on coherence-driven compression. Includes a falsifiable adaptive-interference protocol.
🌌 Explore the harmonic architecture of the solar system with scripts for verifying gravitational quantization laws and improving predictive accuracy.
Special Edition documentation and public gateway for AUTO DZ ACT (canonical definition published on Zenodo: 10.5281/zenodo.18134257).
Small Audio Post-Processor
An interactive model of the alignment phase ratio Φ = C / A_causal — the variable governing whether AI capability outpaces system-awareness before the crossing to stability can occur. Includes falsification test, oracle counterfactual, and point-of-no-return detection. Built to accompany The Alignment of Intelligence, Article 3: The Crossing.
What Do Precision Tests of General Relativity Actually Measure? A methodological taxonomy showing why most precision tests constrain largely local, reciprocity-even observables within assumed frameworks. Proposes discriminating experiments. TEP Paper 10.
Theory of Nothing with the Coherence Keeper of finite math — check your work here — use our spectrometer, no data shared with us if you don't want to\! Welcome to the 7Site Research Collaboration.
🔍 Explore a testbed for quantum-inspired law learning, allowing controlled and falsifiable evaluations under measurement invariants.
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