Sentence examples for model predictions assessed from inspiring English sources

An uncertainty analysis of the model predictions assessed the spatial distribution of prediction uncertainty and the contribution of different error sources to that uncertainty.

Model predictions are assessed against observations through an implausibility measure that rules out model inputs that are considered implausible given the quantified uncertainty.

Calibration of the model predictions was assessed by plotting observed proportions versus predicted probabilities; where a 45° line denotes perfect calibration.

Model predictions were assessed against experimental data.

Several materials were processed with the device, model predictions were assessed experimentally and the quality of the dispersive mixing achieved was estimated for two more complex polymer systems.

Model predictions were assessed using in vitro proliferation assays in panels molecularly characterized cell lines, and clinical relevance using publicly available cancer genomic data.

In addition, the validity of the model predictions was assessed on the basis of the proportion of patients classified correctly (see, eg, Soini and colleagues 15).

Model predictions were assessed against empirical data measuring the appearance and disappearance of multiple FVa degradation intermediates as well as prothrombinase activity changes, with plasma proteins derived from multiple preparations.

We divided the trial populations into quarters of pre-intervention risk on the basis of model predictions and assessed them for discrimination, calibration, Pearson's median skewness coefficient, and the median:mean risk ratio.

Model predictions were assessed against empirical time course data measuring the appearance and disappearance of multiple FVa degradation intermediates as well as prothrombinase activity changes, with experiments done multiple times, with plasma proteins derived from multiple preparations.

Additionally, an experimental rolling contact fatigue study is performed and the results are compared to the model predictions to assess the accuracy of the proposed contact fatigue methodology.