Sentence examples for models is adequately from inspiring English sources

One of the major concerns in studies on preterm labor, especially on uterine contractile activity is that practically none of the models is adequately sufficient and easy to use – mice uteri lack V1a vasopressin receptor [ 4], rats present with spontaneous uterine contractility [ 5] and labor in ginea pigs is characterized by the desensitization of the progesterone receptor [ 6].

The results revealed that the empirical models were adequately fitted to the experimental data (p < 0.0001).

As the capability to automatically generate code from different models becomes more sophisticated, it is critical that these models be adequately tested for quality assurance prior to code generation.

Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed.

Because there was little variability in adjusted-R, RMSE, or prediction RMSE under leave-one-day-out cross-validation, we concluded that our models were adequately powered and robust (Table 3).

As such, the user can construct their own values by evaluating the VQSR and BQSR reports produced by the GATK to determine whether (i) the Gaussian mixture models were adequately trained to distinguish between variants of differing reliability, and (ii) whether the empirically determined base quality score recalibrations appear reasonable for the sequencing platform.

According to REACH (Annex XI) [3] a QSAR model is valid if: The model is recognized as scientifically valid; The substance is included in the applicability domain of the model; Results are adequate for classification and labeling and for risk assessment; The model is adequately documented.

It is shown that the model is adequately validated by our experiment.

A scaled simplified nose landing gear model is also measured as a benchmark test, results reveal that noise radiated from the model is adequately higher than the background noise for a wide frequency range and remarkably consistent with other results from literatures.

If the model is adequately parameterized to estimate basin discharge in unimpaired locations, then the model can be used to assess nearby locations with similar physical watershed characteristics that are ungaged.

With larger datasets, ML yields increasingly accurate estimates of nuisance parameter values; as sequence length approaches infinity, the likelihood of the true phylogeny (with the correctly estimated branch lengths) is guaranteed to exceed that of any other phylogeny (with any branch lengths), so long as the model is adequately parameterized and identifiable [9], [13].