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To evaluate the model performance, this model was applied to simulate the interaction between a large bubble and many suspended small bubbles in 2D vertical channels under different bubble shape regimes.
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The Job Demand Control Support model performance in this study predicted service employees' WLC and tested two job strain hypotheses (i.e., iso-strain and buffering hypotheses).
The extremely rare occurrence of competition was associated with poor model performance for this concept.
Despite certain drawbacks [ 43, 44], the most popular approach for evaluating model performance in this context is cross-validation.
Inappropriate selection of variables is an important and common cause of poor model performance in this situation.
Footnotes Model performance in this table is measured using the area under the receiver operator characteristic curve (C-statistic) and Nagelkerke's Pseudo-R.
The "R" score was used to assess model performance: (3) This expression compares experiments and simulations in terms of the relative changes in the final concentration of given metabolites.
Footnotes Model performance in this table is measured using the area under the receiver operator characteristic curve (C-statistic) and Nagelkerke's Pseudo R. Administrative data includes age, sex, comorbid conditions (COPS2), admission type (emergency or elective), and admission diagnosis.
North (2012) introduces a RASP-based formalism for the analysis of agent-based model performance and uses this formalism to prove that the total asymptotic time and space performance of a specific Mars Rover model is computationally optimal.
A recent study using state-space models suggested that pre-filtering of ARGOS data improves the model performance [16], and this seems to be confirmed by another recent study which used a classical speed filter prior to using the state-space model [38].
The results demonstrate predictive skill using a stringent validation procedure, however, indicating strong model performance even with this relatively limited observation dataset.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com