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All that paperwork is then categorized and organized.
Each runner was then categorized by sex, age, country, rank, split results, final results and the date of the performance – with outliers excluded.
Difficulty reasons were then categorized following this scheme.
Eighteen responses received were then categorized based on similar answers.
The façade ratings for each characteristic were then categorized into factors through factor analyses.
Local characteristic features are extracted from the recordings and then categorized by RBF classifiers.
Patients are then categorized into one of three categories: seriously addicted, potentially addicted or normal.
The patients' findings were then categorized as high (≥3) or non-high (≤2).
Twenty-nine responses received were then categorized based on their similarity.
These probable causes were then categorized as shown in cause-effect diagram in Fig. 5.
Thereafter, the codes were then categorized by common issues that emerged from the data.
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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