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Supplementary Tables 12, 13, and 14 also include the mean ranking for each significant motif, from 1 for the lowest total frequency to 88 for the highest.
The mean ranking for oxygen saturation went down (became more influential) and potassium level went up (became less influential) as predicted mortality increased (paired t tests P < 0.0001 for each).
Therefore, PX TP/SP) motifs likely target phosphorylation by all three MAPKs, and a higher number of these motifs leads to more phosphorylation sites and a higher signal in the assay.> -wrap-foot> ETS proteins are listed by the mean ranking for ERK2, JNK1, and p38α from Tables 1, 2 and 3.
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Tables 13, 14 and 15 present the mean rank for each context separately.
The resulting ranks were averaged across all data sets to obtain a mean rank for the particular AD measure.
Canonical Correspondence Analysis, Kruskal Wallis multiple comparison of mean ranks for all groups, frequency tables with Chi-Square tests and indicator species analysis were used.
It gives the mean rank for each discretization algorithm based on median difference, such that the algorithm with high averaged accuracy may not be in the first rank.
The mean rank for 2-class experiments is accompanied by the coverage metric, which is very important to avoid misinterpretation of the results.
To understand this difference, we calculated the mean rank for these methods without their 'original' datasets and put the results in parenthesis.
Observe that SentiStrength and Sentiment140 exhibited the best mean ranks for these experiments, however both present very low coverage, around 30% and 40%, a very poor result compared with Semantria and OpinionLexicon that achieved a worse mean rank (4.61 and 6.62 respectively) but an expressive better coverage, above 60%.
The smaller dots signify the ranks reported by the individuals, while the larger diamonds signify the mean ranks for all the participants Fig. 10 Averages and standard deviations of friction forces and apparent coefficients of friction among all of the participants.
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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