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Each model was compared to its template to verify that the modeling step had not significantly altered backbone and side chain conformations.
Quota models were fitted to the dynamics of each simulated species with the three different approaches and the performance of each model was compared.
To explore the role of the training data sets size in determining the performance of predictive models, PVE for each model was compared with data set size (Fig. 6).
The performance of each model was compared using independent data from the SOCCAR trial.
The ROC AUC of each model was compared using the DeLong test [ 21].
The fit of each model was compared against that of a saturated model of the observed data.
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However, Cornell and co-workers [ 19] showed that there is little difference between the two modelling methods when the annotations of protein pairs found using each model were compared.
Under the same thermal and mechanical conditions, the properties of each model are compared in terms of temperature fields, residual thermal stresses and the strain energy densities.
In addition to comparing the capabilities of the four models, the results generated by each model were compared with the experimentally determined complete stress strain curves for the Swedish Ävrö granite for different porewater conditions.
The dynamic characteristics, dynamic response and failure mode of each model were compared and analyzed.
The values of the time dependent MOE and also specific prestress losses from each model were compared.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com