Sentence examples for a statistical predictor of from inspiring English sources

But to pediatricians, there are risks in giving babies cane sugar: Sucrose can harm tooth enamel faster than other sugars; once babies get used to its sweeter taste, they might resist less sweet formulas or solid foods; and some studies suggest that they might overeat, leading to rapid weight gain in the first year, which is often a statistical predictor of childhood obesity.

Using the ACE estimate of var type richness and a statistical predictor of the number of new species or types encountered in further sampling of a population [38], we estimated the proportion of var types in a population that will be identified given a range of sample sizes in each population.

Although a statistical predictor of glioma grading based on MR imaging has been proposed [ 43], the authors are unaware of any studies that attempt to relate cell density to contrast enhancement in MR images.

As expected [ 28], culmen is a statistical predictor of body mass for both decades (p < 0.0001 for main culmen effect, culmen by decade interaction p = 0.690), but wing length is a significant predictor of body mass only in the 1970s, when birds were relatively heavy (wing by decade interaction, p < 0.0001).

We used zero-inflated Poisson GLMs to determine whether floral-display size was a statistical predictor of pollinium-insertion and -removal rates per visit because a larger portion of the visits resulted in zero pollinium insertions or removals than would be predicted by a Poisson distribution [ 54].

Our data appeared consistent with those reporting per-nodule TACE efficacy (mimicking patients with a single nodule) [ 29] where similar CR and PR rates were reported (64% and 36%, respectively) and tumor diameter ≤5 cm was again found to be a statistical predictor of complete response [ 29].

If you take a "real" IQ test (see comments below), then the result is a strong statistical predictor of multiple future life outcomes - income, education level, health, even longevity.

Similarly, although gonorrhea was a strong statistical predictor of recurrent SSTI in several preliminary multivariate models, we found that models including gonorrhea were overly influenced by the single subject with a history of gonorrhea during follow up with recurrent SSTI (out of two subjects with a history of gonorrhea during follow up).

Studies of this problem that we are aware of mostly showcase the examples where the bias leading to errors indeed exists [e.g. (Koski and Golding, 2001)], but there is no evidence to show that the BLAST score is a poor statistical predictor of orthology at the genome scale.

While we found some evidence that highly connected proteins evolve more slowly than sparsely connected proteins, (i) the negative correlation between rate and expression level is more pronounced, (ii) in S. cerevisiae and C. elegans connectivity turns out to be a worse statistical predictor of the evolutionary rate than expression.

Meanwhile, the caveat in using ProtIdent and how to understand the success expectancy rate of a statistical predictor are discussed.