Sentence examples for use a score that from inspiring English sources

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Since different networks have different complexities, it is common to use a score that takes into account the network complexity instead of the raw likelihood to compare the networks.

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Furthermore, we rated the functional outcome using a score that does not include objective shoulder function parameters, such as strength and range of motion.

NUPACK performs sequence design using a score that reflects the difference with respect to the target secondary structure for a predicted ensemble of RNA structures.

The scoring system quantifies (weigh) the impacts by using a score that reflects their frequency as well as a severity score that indicates the importance of the specific impact in the daily life of the person.

Consistent results were obtained when interacting proteins were selected from the STRING database using a score that combines different types of evidence including physical interactions, comparative genomics approaches, and gene expression (data not shown).

André de Ridder, conducting with a click track and using a score that incorporated images from the films, held all of the elements together with impressive precision.

Flow quantification was performed using a score that distinguishes between no flow (0), intermittent flow (1), sluggish flow (2), and continuous flow (3), assigning a value to each individual vessel.

That same year, the Goodspeed Opera House staged a production accompanied on two pianos (using a score that Loesser had once commissioned) with such success that the production moved to Broadway's Booth Theatre in 1992 with Spiro Malas as Tony (it ran for 229 performances).

It is worth noting that by using a score that only takes into account the differential expression of a regulator across the different condition clusters, we can simultaneously evaluate and compare mRNA and miRNA candidate regulators.

Because of this, we used a score that most educational institutions use to classify performance: very good (10.0 8.0), good (7.9 6.0), regular (5.9 4.0), bad (3.9 2.0) and very bad (1.9 0.0).

However, this approach to user classification uses a score that weights all components equally, and forces the investigator to subjectively choose cut points in that score.

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