To assess the statistical accuracy of FFMD predictions against experimental data, Gaussian process regression (GPR) was applied to the experimental scattering data to estimate the mean and variance of the structure factor distribution. GPR, which is a nonparametric Bayesian method, provides a rigorous framework for quantifying the statistical properties of unknown functions given noisy observations, offering a robust way to evaluate model fits by accounting for both data trends and uncertainty. Here we estimated the experimental uncertainty bounds using GPR and subsequently compared the CHARMM36 and prosECCo75 models to this distribution in Fig. .