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The degree of relevance to different categories for the uploaded datasets is defined by p-values, and so the lower p-value gets higher priority.
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Two datasets were defined by the level of taxonomic identification, all taxa or a subset of common taxa, and the level of taxa reduction; all taxa, taxa > 1% of total abundance, and taxa significantly contributing to variation.
The datasets are defined by survival status at endpoints 5 and 7.5 years.
Each dataset is defined by a set of experimental measurements of several extracellular fluxes (e.g., biomass growth, glucose uptake rate, oxygen uptake rate, etc).
Outbreak years within the base dataset were defined by the total annual number of cases exceeding two standard deviations of any combination of three or more historical years.
In MetaCore, the degree of association of the uploaded datasets with predefined metabolic pathways is defined by P-values, with lower P-values being more relevant.
An exception is defined by (a) the dataset name, (b) the variable of interest, (c) the variable in the dataset that has to be renamed (or a 'not found' statement if the decision is not to use any of the candidate(s)) and (d) the rational to justify the exception.
Three datasets were defined for analysis.
For extreme datasets, containing either redundant or complementary features as well as noise, the index value is defined by mathematical formula.
The range is defined by the minimal and maximal distance found within the whole dataset.
Leadership is defined by winning.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com