Using the identification results obtained from the optimal preprocessing order and parameters that achieved maximum accuracy, we conducted consensus analyses using Venn diagrams and UpSet plots. Initially, we identified the names of the query compounds (i.e., metabolites) that were correctly identified for each similarity score and then calculated the number of query compounds that were commonly correctly identified based on the combination of three preprocessing orders or three similarity measures. The consensus analyses across the three preprocessing orders and the three similarity measures are depicted in Supplementary Figures and, respectively. It is evident from Supplementary Figure that the CWM and CMW processing orders were more similar to each other than to WCM across all similarity measures in terms of the number of common compounds identified. Supplementary Figure shows that, in terms of commonly identified compounds, the Cosine Shannon Entropy Correlation, regardless of the application of a low-entropy transformation, as shown in Supplementary Table . Consistent with ESI-based identification, without a weight factor transformation, the Tsallis Entropy Correlation showed the highest accuracy of 80.84% among the three similarity measures, while the Cosine Correlation had the smallest accuracy of 75.94%.