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'model uncertainty' is an acceptable phrase in written English.
It is used to refer to the uncertainty of the assumptions or parameters used to develop a model. For example, economists must often account for model uncertainty when making predictions about the economy.
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PLSR model uncertainty was estimated by jack-knifing33.
Vertical error bars indicate model uncertainty calculated by jack-knifing.
Consequently, model uncertainty inevitably arises.
Gal, Y. & Ghahramani, Z. Dropout as a Bayesian approximation: representing model uncertainty in deep learning.
The assumption of a D decay model results in an additional model uncertainty.
Students will be able to formulate and evaluate parametric and nonparametric methods for determining model uncertainty.
At present it is unclear how to assign an average model uncertainty.
The third error in the results given below is due to Dalitz model uncertainty.
The publications listed below show a variety of quantification and propagation approaches for characterizing model uncertainty.
This can lead to spurious conclusions when experimental and model uncertainty is not taken into account.
An unknown amount of model uncertainty should be added to the final error.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com