To assess the overall performance of the CNL model multiple datasets have been used for different purposes. Figure shows an overview of the assessment approaches and which datasets have been used. First, the model was trained and optimized using MassBank EU and MoNA (Figure ). Second, three datasets (i.e., standards, matrix, and concentration) of real data were used to test the model and gain insights into the aspects influencing the performance (Figure ). The standard set was used to assess the general performance, the matrix set was used to assess the influence of matrix effects, the concentration set was used to assess the influence of sample concentration, and for assessing the influence of the CNL mass range and collision energy all the datasets were used. Finally, all three datasets were also used for comparing the performance of the CNL model with existing techniques, namely apex t r difference and peak shape correlation analysis (Figure ).