Audio note: The companion audio discussions emphasize that the Richat model is geodesic rather than conventionally cartographic, and that major spoke families may form continuous great-circle structures rather than isolated alignments. They also highlight the predictive significance of near-hit cases such as Nazca and frame the blind-spot outputs as a shift from descriptive clustering toward candidate-zone generation for future investigation. This document formalizes a strategic paradigm shift in geospatial archaeology,transitioning from the constraints of modern cartographic standards to a predictivemodel centered on the Richat Structure in Mauritania. By implementing a "PrimeMeridian Reset," we move beyond the Eurocentric grid systems that dominatecontemporary geography to analyze the distribution of ancient monumental sitesthrough a proprietary "Spoke-Wheel Analysis." This model posits that the world’smajor ceremonial and archaeoastronomical complexes are not distributed randomlyacross the terrestrial surface but instead resolve into coherent "families"—directionalspokes and radial bands—when measured from this singular, centralized geodeticorigin.The methodology utilizes high-precision geodesic mathematics to calculate theshortest paths over the Earth’s ellipsoidal surface, establishing the foundationalskeletal structure of a global wheel. By applying intentional mathematical offsets andsophisticated mirror logic, the framework has generated 1,152 total nodes, including927 high-priority "Blind-Spot Nodes"—coordinates in underexamined regions wherearchaeological evidence is mathematically predicted to exist. This research providesa rigorous, hypothesis-generating framework for identifying the missing componentsof the human monumental record, transitioning the field from descriptive survey to atargeted, predictive roadmap for global exploration. Thanks to Allan Christopher (CdnBigBear / لوی ږیره) Beckingham, CD He/Him 1st degree connection1st Lead Architect @ Coherence Dynamic Laboratory | System Architect of Consciousness, Artificial General Intelligence | ORCID: 0009-0004-2830-4089