Sentence examples for model predictions more from inspiring English sources

Approximately 50% of the observed magnetopause crossings have deviations from the model predictions more than 1Re.

Model predictions more closely matched current species distributions when the liberal threshold was used (81.04%, sd = 21.25 vs. 62.83% sd = 25.89, for the strict threshold; Table S1).

However, to validate our model predictions more rigorously, we performed new time-lapse migration studies in which we tracked cell migration on soft and stiff ECMs at a much higher temporal resolution, which in turn enabled us to quantify and statistically analyze trailing-edge protrusion-retraction cycles.

In the case of a fat-tailed kernel, the model still predicted higher numbers of clinical and affected holdings than were observed, though to a lesser extent than without restrictions (Figure 4E and 4G and Figure 5), while in the case of the FMD kernel, the model predictions more closely matched those with either the Gaussian or exponential kernels (Figure 4G and 4H and Figure 5).

We are exploring ways to measure the actual heat of reaction for the entire siRNA-RISC complex formation reaction and the other parameters to make the model predictions more accurate.

The spatial model predictions were more accurate than the regression model predictions at locations <200 m from sample locations.

Model predictions are more consistent for upper air as a result of using FDDA reanalysis nudging and the reducing influence of underlying surface with altitude.

Although the high train use adjustment gravity model predicts a slight bias towards coastal fadeouts, it corrects for most of the bias in the initial, unadjusted gravity model predictions and more accurately reflects the observed data.

However, using the resultant deflected trajectory as training data and updating the dynamics model online brings the arm nearer to the target with each new trial as the internal model predictions become more accurate for the new condition.

Because we are able to exhaustively sample the parameter space, a consistency between new experimental results and model predictions is more likely to be indicative of the design architecture of the biological system rather than reflect a particular choice parameter values.

Because population structure can increase type-one error rates (false-positives) in association studies, model predictions are more credible with population structure removed.