Sentence examples for model discrepancy in from inspiring English sources

Here, we have incorporated the uncertainty in the meteorological forcing through the model discrepancy in the implausibility measure.

It is argued that mixtures of experts are often insightful for describing model discrepancy and ways in which the computer model can be improved.

The adoption of radiosonde measurements to describe the atmospheric structure at the volcanoes therefore introduces uncertainties into the model solutions which are quantified in the model discrepancy.

In contrast, the top three MAQC models show discrepancy in performance when the datasets used for training and test were swapped especially in the case of the MAQC_GeneGo model, which has the largest difference in performance (0.25) between the FXD and BXD analysis.

We note that Kuhlbrodt and Gregory (2012) emphasized the dominant role of the Southern Ocean and found the importance of eddy-induced transport in the model discrepancies of global ocean heat uptake.

As shown here, comparisons between gene essentiality predictions can be useful in identifying model discrepancies which can lead to updated and improved models, as well as identification of unique metabolic features, which allow for discovery of possible phenotypic differences between two organisms.

Indeed, a particular problem with the use of the Claus model is the discrepancy in results obtained when using the published tables [ 30], compared with computerised versions of the model [ 27- 29, 39].

However, the model showed some discrepancy in predicting the gas solid flow behavior in the riser operating in dense suspension up-flow and low density fast fluidization regimes.

In particular, for the SAHS and ARIC models, the discrepancies in terms of FPG and measures of adiposity (BMI or waist circumference) were no longer statistically significant.

It is generally the case that the CCSM3 model produces the highest discrepancy in all four seasons.

RMSEA is a parsimonious fit index that evaluates the overall discrepancy in model-to-data fit while also taking into account the model's simplicity.