Sentence examples for much less selection from inspiring English sources

On the other hand, this scenario has been shown earlier to exhibit much less selection pressure when actuators were evolved [57].

Thus, the approach is likely to provide PROs data with much less selection bias than separate surveys and other separate outcome assessments.

Improving the participation rates may have the added benefit that there is much less selection bias as a larger subsection of the general population will participate [ 32].

A consequence is that control measures specifically aimed at these reproductively successful females will generate much less selection pressure for them to evolve resistance than measures that also target younger females that have not achieved as large a proportion of their expected lifetime reproductive success.

While loci that have been fixed in all domesticated cattle relative to their auroch forbears will still not appear on this assay due to the requirement that the putative SNP must have been predicted to have been variable in the sequence data for at least one breed, there was much less selection for SNPs with high MAF in numerous breeds in the design of this assay relative to the BovineSNP50.

LRTs of M0 M3 and M1 M2 are heavily affected, while LRT of M7 M8 is much less (positive selection was falsely detected in only 20% of replicates).

By analyzing the complexity in terms of flops, we showed that the proposed analog beam selection algorithm provides much less complexity than the optimum analog beam selection algorithm.

From Figs. 5 and 7, we can notice that the performance loss of the proposed analog beam selection algorithm is not significant compared to the optimum analog beam selection while the proposed analog beam selection algorithm has much less complexity than the exhaustive search based optimum analog beam selection.

When working with large datasets including hundreds of multi-categorical variables, classification trees can be used to perform a much less computationally demanding pre-selection of variables which can be then included in logistic regression analysis or any other.

We compare the complexity to show that the proposed analog beam selection algorithm has much less complexity than the exhaustive search-based optimum analog beam selection while the performance loss of the proposed analog beam selection algorithm is not significant compared to the optimum analog beam selection, which is shown by the numerical results.

Kim Sterelny (1996) has invoked the distinction between superorganisms and trait groups to argue that group selection is a much less significant force in directing evolution than proponents of group selection have thought.