Burdick Crag Mass: A Substrate Wave Model for Galactic Rotation Curves Without Dark Matter — v4 with Quantified Neutrino Prediction and Tully-Fisher Recovery

Version 3.0: A substrate-based phenomenological alternative to cold dark matter in which the dark matter signal is modeled as the energy maintenance budget of a pre-existing 2D spatial substrate. Using four global parameters (lambda=0.1, kappa=2.0, grid=256, layers=8) and zero per-galaxy tuning, we classify 175 SPARC rotation curve galaxies into six physically distinct substrate interaction states. On 29 representative galaxies, BCM achieves a mean reduced chi-squared of 42.1 compared to NFW's 92.1 (two fitted parameters per galaxy) and MOND's 1630.4. The framework generates falsifiable predictions for IceCube/KM3NeT neutrino flavor gradients, Betelgeuse tachocline recovery, and binary mass transfer rates. All code and data: https://github.com/Joy4joy4all/Burdick-Crag-Mass Version 4.0: Preprint presenting a substrate wave model for galactic rotation curves using four frozen global parameters and zero per-galaxy tuning. Reduced chi-squared comparison against NFW and MOND on 29 SPARC galaxies: BCM wins 13/29 (mean χ²=42.1 vs NFW 92.1), dominates massive bracket 7/12 (avg χ²=62.7 vs NFW 241.8). MOND wins 0/29. The substrate maintenance luminosity scales as L_ν ~ v_max^3.9, independently recovering the baryonic Tully-Fisher relation (L ~ v^4; Tully & Fisher 1977) from the same frozen parameters — this scaling was not an input. All 29 galaxies remain sub-Eddington (max L_ν/L_Edd < 6×10⁻⁴). Predicted neutrino flux exceeds IceCube point-source sensitivity by 2-5 orders of magnitude for galaxies within 20 Mpc. All code and data publicly available on GitHub. Included, v1.0 and v2.0 drafts