Version 2. 0 — We report an empirical regularity in multilayer networks, the Functional Proximity Law: degree-centrality hub scores correlate more strongly between layers encoding functionally similar relationships than between layers encoding dissimilar ones. We test this across 15 independent domains spanning molecular biology, systems neuroscience, computer systems, ecology, and linguistics. Thirteen domains confirm the directional inequality between pre-registered similar and dissimilar layer pairs; 9 of 15 reach p < 0. 05. Three DENIED domains reveal named structural mechanisms bounding the law's scope. A negative control confirms the method does not fire on random structure. This version adds the first external-party validation on data not designed by the author (Flask, github. com/pallets/flask, n=14 modules, 1934 commits): r (imports↔structuralcoupling) =0. 6659 (p=0. 015), the only statistically significant pair. Pre-registration artifacts are publicly archived at https: //github. com/vladi160/preregistrations
Vladi Ivanov (Wed,) studied this question.