Sentence examples for models could correctly from inspiring English sources

For example, such simplified models, could correctly predict the dynamics of the complex genetic network, controlling segment polarity in the development of Drosophila melanogaster [ 135], and a simplified binary model of the genetic network controlling the yeast cell cycle [ 136] realistically modelled the actual situation.

In this case study, we found that the coupled model could correctly predict the occurrence of debris flows.

Simulated results indicate that the model could correctly forecast the flood, submerged area and depths, and water surface elevations along the left side of the channel.

This model could correctly predict the retention of proteins on resins that were not included in the original model and could prove quite powerful as an in silico approach toward designing more effective and differentiated multimodal ligands.

This model could correctly simulate all the observed features and revealed that the degree of the interlayer interaction could be quantitatively reflected by the bright-to-dark size ratio of the bright-dark pair at a lattice site.

In addition, 91.7% of the utterances with no representation in the language model could correctly be rejected.

We also checked whether the model could correctly predict the effect of different knockout of the protein tyrosine phosphatases, Ptp2 and Ptp3.

This model could correctly assign 89.7% of patients to indolent or aggressive disease groups based on Gleason score.

The non-crossvalidated regression value showed a conventional r of 0.962, an F of 250.8, and a standard error of estimation of 0.083 (P<0.0001), suggesting that the model could correctly predict compound activity in 96% of cases.

If a score is significantly higher than expected by chance, it provides statistical evidence that the underlying model could correctly explain a large fraction of diverse but functionally related disease signatures.

It can be seen from Tables 2 and 3 that the CoMFA model could correctly predict the compound affinity with an r of 0.821, an F of 9.117, and a standard error of estimation of 0.281 (P<0.0939), suggesting that the CoMFA model could accurately predict compound activity in 82% of cases.