Sentence examples for set to categorize from inspiring English sources

Instead, a more ideal approach would be to convene a meeting of microbial physiologists and taxonomists charged with the task of agreeing upon an extensive standard list of phenotypes that could be used as a common set to categorize all microbial species.

But Downing pointed out that $15.7 million was set to be categorized as a distribution to Paul Manafort — meaning he would have paid taxes on it.

In 1962, the ecologist Robert Whitaker set out to categorize the different realms of life on Earth.

We set out to categorize the EDFT patient 'reasons for visit', documented as free-text chief complaints (CCs), into clinically useful groupings.

GO provides a set of text vocabularies used to categorize sequences by the general attributes of their biological function.

It could also be used to categorize a set of articles of one peculiar journal.

The adoption of EUCAST criteria for H. influenzae produced very major discrepancies for macrolides when the rates of susceptibility calculated using EUCAST and CLSI breakpoints were compared, as breakpoints for macrolides and related antibiotics have been set by EUCAST to categorize wild type H. influenzae as intermediate.

Machine Learning offers the possibility to classify single items in large data sets and to categorize these items with regard to the context they are in.

A new mean shift clustering, improved by neutrosophic set, is employed to categorize the pixels into different groups whose bandwidth is determined by the indeterminacy values adaptively.

Any time that extra-musical concerns dictate concert programming — music by women composers, music by African American composers — you open up the question of whether it does the artists any favors to set them apart, or to categorize them by their religion, race or gender rather than by their art.

We employ two approaches to estimate the FDR: (i) using a protein reference set as ground-truth to categorize proteins as true or false instances; (ii) generating true and false (null) score distributions independent of ground truth as described in detail below.