The mean and standard deviation for these 1,000 query spectra were then summarized, presenting an average computational expense per query spectrum. Further investigation into the relationship between the number of query mass spectra and the computational expense was conducted, as depicted in Supplementary Figure . Across both ESI and EIbased identification, among the three evaluated similarity measures, the Cosine Correlation emerged as the least computationally expensive, followed by the Shannon and Tsallis Entropy