Sentence examples for unbiased enough from inspiring English sources

But between his comments about race, religion and gender, the people Trump thinks would be unbiased enough to serve may make up a very narrow slice of the population. .

For example, if professionals benefit from administering specific interventions to patients, their societies may not be unbiased enough to recommend that patients should not be treated with specific interventions (such a recommendation would reduce the volume of clientele and financial gains of these professionals).

He prevailed when the district attorney could not muster enough unbiased jurors to sit in judgment of Ed from the Tee-Pee, and the Legislature relaxed laws regarding video poker in taverns.

Now, as this volatile election approaches the final threshold of November, citizens are skeptical about whether our electoral system — particularly the technology used in it — is precise, unbiased or secure enough to produce a fair, accurate vote count.

Americans will respond, if given enough unbiased information over a substantial period of time.

Seventy-two of the videos did feature board-certified physicians, and scored highly on the DISCERN criteria, a tool used to decide whether educational materials provide enough unbiased information to help patients make informed decisions about their health.

However, establishing functionality for each bound TF-promoter combination, or even obtaining a large enough unbiased sampling of such pairs, is clearly unrealistic.

If k-mers bearing enough unbiased signal can be extracted, statistically based comparisons of k-mer spectra can be used to infer phylogenetic relationships or map genetic transfer [ 32, 33].

Thus, in clinical cases where the detection limit of a routine real-time PCR assay is not sensitive enough, an unbiased pre-amplification could be helpful.

This finding means that the estimated propensities calculated from the training set are unbiased and are significant enough to correctly separate the population of positive and negative instances.

If we start close enough to the unbiased prevalence, this method will converge to the unbiased prevalence.