Overall, these results show that the physical description of long-range contributions in kQEq allows the use of rather small cutoffs for the ML part, effectively focusing on the nearest neighbors. This is beneficial both in terms of transferability of the models and the This indicates that kQEq does a good job of partitioning contributions into long-ranged physical terms and a short-ranged ML model.