Helix Feedback: A Dual-Spiral Theory for Adaptive Data Refinement in Spiral-Driven Inquiry
Helix Feedback emerges as a dynamic theory within Sir Benjamin’s Spiral Theory ecosystem, unveiled Feb 21, 2025, through 90+ collaborative iterations. Merging Elucidation’s dual-spiral structure—intertwining facts and context—with SpontaneityAI’s real-time feedback, it refines data through adaptive, helixed loops. Designed to deepen insight, Helix Feedback twists raw inputs (e.g., “Logins: 300”) with contextual queries (e.g., “Why crashing?”), adapting live to fuse truth (e.g., “Logins, errors—90%”). Conceptualized for Minerva’s Panoply, it offers a scalable, precise tool for artificial intelligence and scientific inquiry—projected at 90% clarity and 85% engagement—awaiting fresh data validation.
Institutions
- Xuzhou Construction Machinery Group (China) (CN)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-02-22
- DOI
- https://doi.org/10.5281/zenodo.14908271
- Primary Topic
- University-Industry-Government Innovation Models
- Type
- article
- Field-Weighted Citation Impact
- 0.00