For learning and testing the scalar models, the entire LTO-EFG database for each nucleus is randomly divided into a training and test set with a ratio of 4:1. The learning of each scalar quantity, y (= CQ , η, θ, ϕ), over all configurations X across the entire training set of the LTO-EFG database is performed using Gaussian Process Regression (GPR) 15