Sentence examples for model discrepancy as from inspiring English sources

We found (Fig. 8B) that the relative discrepancy between the AQLV model and data is larger (i.e., the data/model viscoelastic ratio is lower) at small initial elongations (this is not necessarily true for the absolute model discrepancy, as the forces at play are higher at large lengths).

Several empirical models have been conceived to account for this discrepancy, as well as the effect of block sequence.

This paper proposes a new robust CEDO model for Bayesian calibration with field response and incorporates various sources of model uncertainty such as surrogate model uncertainty, numerical discretization error, and model discrepancy, into CEDO.

Many model discrepancies likely result from poorly characterised biological processes.

Based on the results from the model evaluation, we identified main errors and discuss possible sources of discrepancies, as well as the inherent limitations to Boolean modeling.

At the individual level, algorithms presented in this study may include some discrepancies from one model to another, as was indicated in the above example.

Application of these techniques to the circadian regulatory network in Arabidopsis has uncovered a number of discrepancies within established models as well as novel regulatory interactions.

Considering the approximations of the model, this discrepancy is very low.

Additionally, we compared the results from this analysis with the results from the simpler CTE and CTU models [6], [7], as well as the VDM [25] to examine the discrepancies among model predictions.

Similar discrepancies between AS and HS have also been reported in TNF-transgenic and other experimental models of arthritis.

The discrepancies were as follows.