Sentence examples for rigorous datasets from inspiring English sources

The hybrid design maximizes the ease of registry participation yet promotes the development of rigorous datasets to support the sharing of verified data with regulatory agencies, clinicians, patients and academia.

The comparative study of static estimators (soft sensors) for a multicomponent distillation process based on the industrial and calibrated rigorous model datasets is considered.

More importantly, the > 89% similarity between biological replicates demonstrated that there was a high degree of relatedness between sputum samples resulting in a rigorous biological dataset that could be mined for gene expression changes.

Comparative evaluation, assay and model standardisation, greater sharing of information, collaboration and coordination between groups, and rigorous evaluation of existing datasets are steps that can be taken to enable reductions in empiricism over time.

Thus, although the explanation of adaptive convergence related to foot-propelled diving remains a tempting explanation for the loon/grebe signal in morphological datasets, more rigorous functional and comparative phylogenetic analyses are needed to support this claim.

It simplifies the search for rare events, removes bias in the choice of imaged cells, delivers large datasets for rigorous statistical analysis, and should allow studies on dynamic changes in live cell populations.

In the absence of an appropriate dataset for rigorous false positive testing, many investigators prefer to examine a stringent set of binding sites.

This shift has been accompanied by more rigorous hypothesis testing on larger datasets [ 7, 8, 21].

Few studies have used comprehensive datasets together with rigorous statistical analyses to confirm linkages between climate and HABs.

It is therefore a pragmatic approach to estimating best-fit partitioning schemes on phylogenomic datasets, where more rigorous methods are computationally infeasible.

We subject BMIQ to a rigorous evaluation using numerous independent datasets and using a number of different evaluation criteria to assess its robustness and performance.