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A public copy of the files is created and begins processing, which includes generating study-level and file-level metadata, confirming all variables and values are labeled, standardizing missing values, creating and augmenting documentation, and assessing and minimizing disclosure risk by applying techniques such as recoding, masking, or removal of variables, and assigning persistent links.
The calculated values are labeled with 'CA'CA
Distance bootstraps values are labeled at their corresponding nodes.
L values are labeled L, L a, and L e, for the a posteriori (APP), a priori, and extrinsic, respectively.
The obtained values are labeled on a Cartesian coordinate system in which |F 1,0)| N and |F 0,1)| N are x and y coordinates, respectively.
On the x-axis, the centered values are labeled as 01 00, 02 00…24 00 LT hours in the figures.
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Each data set contains N test values, of which N × P(D) values are associated with "Disease", and N × [1 − P(D)] values are labelled "No disease".
Results from the dogs with expected normal values are labelled 1-10, dogs with expected intermediate values 11-20, andogsgs with known azotemia 21-30.
Some of the effects may be considered relatively large, since there is a tendency for people to avoid extreme answers on scales where extreme values are labelled in absolute terms, as it was the case in the studies included in this article [ 21].
The gap between the originally forecasted values and the actual values is labeled "second projection".
Missing values were labeled as 0 if the mean number of autonomic symptoms was calculated.
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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