Sentence examples for cross-validating data from inspiring English sources

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Despite these limitations, surveys are key to answering specific questions about alcohol use and harms in the absence of suitable archival data and are central for cross-validating data gleaned from other sources.

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These results suggest that cross-validating information obtained from structured data with that obtained from clinical narrative can reduce false-positive findings from either data sources and improve the noise environment through which a surveillance system must operate to uncover disease clusters.

By cross-validating information on alternative splicing between the ENSEMBL and the ASD databases, we discarded a large proportion of humans and mice genes (>30%) from our dataset, because of incongruent annotation in the two databases.

When asked about the main drivers for data reuse, the respondents highlighted the strengths of combining, synthesizing, and cross-validating diverse data sets to generate scalable, rigorous, and reliable scientific results as well as produce unique and critical insights.

Some studies have tried to address this issue by cross-validating children's data with data from parents (e.g., the aforementioned study by Merckelbach et al. 1996b) with the result that verbal information did not emerge as an important pathway to fear.

This study presents data cross-validating several indicators of malingering on neuropsychological tests, as well as on tests of malingering and via behavioral observations.

The workshop is divided into three parts: (1) reviewing the state of the technology on UAV types, sensor configurations, and data acquisition methods; (2) exploring GIS and remote-sensing software tools for analyzing super-high-resolution spectral data acquired by fixed-wing drones; (3) cross-validating drone products against Lidar data and satellite imagery.

The results demonstrate that our algorithm improves the registration of functional architecture across subjects, as indexed by cross-validating generalization to movie-viewing data and by generalization to data from the face and object perception experiment.

The standard form of submission of collections of data, the SDF file, allows the user to map the data fields to predefined CVSP fields for the purpose of cross-validating associated SMILES and InChIs with the connection tables contained within the SDF file.

As discussed earlier the standard form of submission of collections of data, the SDF file, allows the user to map the data fields to predefined CVSP fields for the purpose of cross-validating associated SMILES and InChIs with the connection tables contained within the SDF file.

Data will be triangulated to find convergence or agreement by cross-validating results.

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