where N is the total number of query groups, n q is the number of samples in query group q, while y i and ŷi are the actual and predicted values for the i th sample within query group q, respectively. QueryRMSE emphasizes the relative ordering of items within each query by incorporating a bias correction term that subtracts the average group-level error. Furthermore, it normalizes the error within each group by the number of samples in the group, ensuring that each group contributes equally to the overall metric, regardless of its size or sample count. For training and testing, we have defined query groups using different concentrations and system sizes.