Sentence examples for predictions is first from inspiring English sources

In this effort, the number of correct (and incorrect) predictions is first summed over all test sequences, and then the measurements were computed from those sums for the exon and base level measurements, respectively.

The model predictions are first verified against experimental observations.

The model predictions are first validated against experimental observations.

The model predictions are first illustrated in a uniaxial test under quasistatic loading conditions.

The model predictions are first confirmed with experimental data obtained from an equivalent film coating pan using a machine vision system.

The predictions are first validated by comparing the Newtonian and non-Newtonian power consumptions and mixing times against literature experimental data.

These predictions are first formulated and then validated for a range of wettable and non-wettable filter media in combination with 4 mineral oils of different viscosity.

Model predictions were first compared against experimental data obtained from the literature and subsequently used in a parametric study for investigating scale-up effects associated with both process and photoreactor variables.

Coiled-coils, which correspond to regions that often fool some predictors into giving wrong predictions, were first identified by visual inspection of the HCA plot and then confirmed using the Multicoil program [47].

Model predictions were first linearly rescaled between 0 to 100, applied to each 1-km2 grid cell, and mapped across the Intermountain West as oil and gas development potential where 0 =  low potential and 100 =  high potential (Fig. 1A).

One extension of this method is the Multi-Label Hierarchical Classification method (MLHC) [15], [16] where predictions are first made by SVM, independently per Gene Ontology (GO) [17] term, which are then made consistent with the GO hierarchy by using a Bayesian Network. Lee et. al. [18] combined the appealing properties of MRF and SVM methods into Kernel Logistic Regression (KLR).