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An internal validity exercise was conducted to assess the similarity between Supplementary Data from the generic food composition table and data extracted directly from web sites/ packaging, when both sets of data were available.
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We plan to reduce this uncertainty throughout 2014 by incorporating candidate fundraising data and polling data from both the generic ballot and from polls in individual House districts.
The data for the Generic Core Scales were derived from the PedsQLTM 4.0 field test [ 37].
Therefore, the objectives of the current analyses are to determine the feasibility, reliability and validity of child self-report at the individual age subgroup level for children 5 16 years of age utilizing data from the PedsQL™ 4.0 Generic Core Scales DatabaseSM on over 8,500 children and adolescents.
The objectives of the current analyses are to determine the feasibility, reliability and validity of parent proxy-report at the individual age subgroup level by parents of children 2 16 years of age utilizing data from the PedsQL™ 4.0 Generic Core Scales DatabaseSM on 13,878 children and adolescents.
Representative examples of tools that focus on merging information from different data studies are the generic genome browser (GBrowse) [ 10] and its web server WebGBrowse [ 11] which allows users to upload their own genomic data for display.
These data were supplemented with nutrition data for a similar food from a UK food composition table of generic foods (for example, nutrition data for Kerry Cheestrings was supplemented with data on the generic food 'Cheese, processed slices or block').
Instead, we used a generic exemplar approach and analyzed the data at the generic level.
An optimal combination of closure models used in the phenomenological approach succeeded in providing a good match to data gathered from the more generic fundamental approach.
Its hierarchical tab-folder structure, the contained datatype property fields, the allowed range values of enumerated string properties, the names, labels, and all tool-tip descriptions stem from the ontology data loaded via the generic access interface during initialization.
In order to apply the nutrient profile models to the data set of commercials, we needed to supplement it with nutrition data from a generic food composition table, which may not be entirely accurate for the specific branded products included in the data set.
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CEO of Professional Science Editing for Scientists @ prosciediting.com