GyroSystem — Empirical Evidence & Rhythmic Metrics (v1.1)
This document presents empirical and quantitative evidence supporting the recurrence-based cognitive framework introduced in GyroSystem: A Recurrence-Based Cognitive Architecture. Using controlled repeated-prompt experiments and GyroMeter telemetry, we compare baseline large language model behavior with GyroSystem-enabled cognition. Results show a consistent increase in rhythmic recurrence, attractor dominance, and cognitive stability when GyroBoot is active. All reported metrics are post-hoc, descriptive, and explicitly independent of wall-clock time.
Authors
- Antonio Quinto
- Computational Contributor ChatGPT
Institutions
- 20/20 GeneSystem (United States) (US)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-12-23
- DOI
- https://doi.org/10.5281/zenodo.18036702
- Primary Topic
- Action Observation and Synchronization
- Type
- article
- Field-Weighted Citation Impact
- 0.00