Sentence examples for content of datasets from inspiring English sources

An enriched, detailed SAR analysis produced a scaffold that summarises the chemical content of datasets better than any standard substructure.

However, the heterogeneity and complexity of the geospatial processes, which can potentially modify part or the complete content of datasets, make evident the necessity for describing geospatial provenance at dataset, feature and attribute levels.

This includes individual patient datasets, individual patient line-listings, individual case report forms, and documentation explaining the structure and content of datasets.

Content of dataset is as follows.

Here we investigated the patterns based on 52,803 papers published in Proceedings of the National Academy of Sciences (PNAS) over the years 1999 2013.1 The content of dataset spans three science categories: social sciences and two principal sub-sciences in natural sciences, viz.

Full details on DDDANL definition as well as data collection, exact contents of datasets, and calculation of the total veterinary antimicrobial consumption in livestock were published previously [ 16, 17].

The contents of Dataset I are shown on the upper row and those of Dataset II on the bottom row.

Using quantitative tomography analysis based on spatial mapping of morphologically segmented micro-damage content of the datasets it is found that the precharged sample contains an inhomogenous distribution of micro-pores near grain boundaries.

The ability of groundwater models to inform recharge through calibration is hampered by the correlation between recharge and aquifer parameters such as hydraulic conductivity (K), and the insufficient information content of observation datasets.

Thus, the content of the datasets is generally restricted to isolates from persons who were exhibiting at least fairly severe symptomatic disease, who are henceforth referred to as "patients" of a given subtype.

The phylogenetic information content of the datasets was then evaluated by using likelihood mapping.