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Table 2 presents a summary of the cases which form the empirical basis for this categorization.
Training data for this categorization process require ground truth tags, indicating the positiveness or negativeness of a given sentence.
Crash data are subject to misclassification of farm equipment involved in a crash, since first responders at the scene are responsible for this categorization.
The criteria used for this categorization are described in the Technical Appendix.
For this categorization, releases were defined as procedures performed to influence the alignment of the leg in extension.
They describe the microarray, which has emerged as the most effective and broadly used tool for this categorization.
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The results of this categorization for siRNAs and shRNAs and correlation coefficients between secondary structure stability of target RNAs and silence efficiency are presented in Figure 2A B.
For New Zealand schools, this categorization is based on the SES of families within a school's catchment area, calculated from census data relating to household income, educational qualifications, and occupation of adults within the household, household crowding, and income support provided to the household.
For phototransduction genes, this categorization was determined by the cell type in which a given gene is expressed.
This categorization for each site was calculated using the 'dnaml' tool from PHYLIP v. 3.8.0.
Several classification systems have been used for this superfamily categorization.
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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