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The sections below are broken up into the official results of the two categories during the contest, shown in Table 2, followed by the post-contest evaluation and a comparison with all approaches from Category 1.
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Finally, the results of adding clear sky information as a new feature to the best model for the AMS contest, i.e. the Beta-noise SVR, are shown in Table 5.
The overall winner of the contest was announced in April 2012 and a selection of entries are shown in Table 1.
The purpose of this contest is to monitor the current state of research: this year's winner in the mood classification task, Peeters [15], achieved an overall accuracy of 63.7% on the five mood classes shown in Table 2 before the second placed participant with 55.0% accuracy.
All responses are shown in Table 1.
These analyses are shown in Table 2.
Expression values are shown in Table S1.
This list is shown in Table 1.
The primers used are shown in Table.
Subject details are shown in Table S1.
Patients profile is shown in Table 1.
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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