Sentence examples for models have relatively from inspiring English sources

Although both models have relatively normal precisions, the biases of the models are very large (Table 3).

However, models had relatively high accuracies (61 89%) in classifying the direction of hydrologic responses as negative or positive.

A comparison with experimental data showed that the models had relatively high prediction accuracy, and they can be used as the theoretical basis for the durability design of FRP-reinforced concrete structures under sulfate corrosion.

The wiggle-matched age depth models had relatively high chronological uncertainty within intervals of closely spaced 14C dates, suggesting that the premise of constant linear accumulation over large sections of the peat profile is unrealistic.

Given this significant variability in the MAE values, one could wonder whether just a subset of the models having relatively small MAEs (e.g., values below a certain threshold) should be used for predicting the tissue log Kt:p values to be used as descriptors in the Vss-target dataset, whilst other tissues' log Kt:p values (with large MAEs) should be ignored.

Although overall classification success of our models was only 65%, models had relatively low false positive error rates (29% and 33% of transects for black and sun bears, respectively).

It is notable that these two models had relatively low AUC values, supporting Lobo et al.'s [35]; [ see also 39] assertion that AUC can be a misleading guide to model utility.

Results of this study indicate that choice of model threshold and CO2 emissions scenario affect short-term projected shifts in climatic distributions of species; however, these factors and choice of global circulation model have relatively small affects on what is significant projected loss of habitat for many salamander species that currently occupy the Appalachian Highlands.

The RRs from the comparison model have relatively good agreement with the C&RT-identified results for the mixtures with lower mean concentrations.

Thus, the cumulative causation model has relatively high requirements for data collection.

This model has relatively good accuracy for analysis of Reynolds stress due to turbulent flow.