MRU v18: Global-Primary-Likeness and Alignment-Dominant Route-Memory Response in a Dimensionless Toy Model

Abstract This module reports a closed MRU v18 branch in a **dimensionless toy-response harness**. The tested question was whether route-memory-derived density structure can produce a distinguishable passive toy tracer response under repaired replication, stress testing, matched adversarial controls, and block-shuffle controls. The clean interpretation is **global-primary-likeness**, with component analysis showing an **alignment-dominant** signal and **secondary path-bias**. Independent local-rank/microstructure survival was not earned. This result does not establish physical gravity, does not establish physical fields, and does not establish orbital dynamics. 1. Scope and Claim Boundary This paper module is restricted to a dimensionless MRU v18 toy-model branch. It reports behavior inside a route-memory density and passive toy tracer-response harness. The terms “density,” “response,” “alignment,” and “path-bias” are used only in the internal toy-model sense. The frozen claim boundary is: In a dimensionless toy tracer-response harness, route-memory-derived density structure produces a distinguishable response that survives repaired replication, stress testing, matched adversarial controls, and block-shuffle controls. The clean interpretation is global-primary-likeness, with the component signal primarily carried by directional alignment and secondarily supported by path-bias. Independent local-rank/microstructure survival was not earned. The module does not establish physical gravity, does not establish physical fields, and does not establish orbital dynamics. It does not claim force, mass, acceleration, physical units, or a physical value of any gravitational parameter. AI Use Disclaimer This work was developed by Malin Hess with assistance from AI systems, including GPT-5.5 Thinking by OpenAI, Claude by Anthropic, and DeepSeek. All conceptual direction, research framing, acceptance or rejection of claims, final interpretation, and publication responsibility remain with the human author. The AI systems did not independently verify the scientific validity of the framework, and their contributions should be understood as collaborative assistance rather than institutional endorsement.