This preprint presents a numerical validation of the Oscillatory Field Genesis (OFG) framework, a first-principles theory unifying curvature memory (Φ) and coherence phase (Θ) to explain cosmological, particle, and biological phenomena. Using simulated scalar fields and gradient interactions, we derive predicted values for nuclear isotope binding corrections, neutrino timing delays, and void lensing anomalies. The results are directly compared to AME2020 mass tables, IceCube data, and Euclid/DESI survey outputs. A sample Python implementation is included for reproducibility. This work demonstrates OFG's predictive capability and positions it as a viable upgrade to the Standard Model.