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The publications listed below show a variety of quantification and propagation approaches for characterizing model uncertainty.
We highlight recent developments of the STM technique that will help further the elucidation of understanding of catalysts in the working state, and illustrate how the level of insight gained from characterizing model systems has advanced to a stage where the insight and ideas may lead to the design of new and improved high-surface-area catalysts.
As in the previous case study, we began our analysis characterizing model input/output.
We introduce LLARRMA as an approach for characterizing model uncertainty when working within the frequentist paradigm.
Scarafone et al. tackled this problem by creating and characterizing model polyQ proteins consisting of the β-lactamase BlaP and polyQ tracts inserted at position 197 [ 16].
Until recently, essentially all models of metabolic pathway systems were developed according to the first strategy, that is, by characterizing model components and processes one at a time and subsequently merging all "local" information about kinetic reaction steps into one comprehensive dynamic model.
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Accordingly, the processes involved in injecting and storing CO2 in such formations still need to be better quantified and methods for characterizing, modeling and monitoring this type of CO2 storage in such formations must be rapidly developed and refined.
Despite considerable efforts in semantically representing and characterizing models [ 50, 56- 58], such an integration has not yet been achieved.
Sparse grid stochastic collocation is employed to statistically characterize model predictions of post-operative hemodynamics in models with and without PA stenosis.
Improving biogeochemical models therefore requires to properly characterize model uncertainties and their consequences.
We characterized model uncertainty by creating corresponding maps of the coefficient of variation in Random Forest shrub biomass estimates.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com