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Models were subsequently ranked in order of descending GPI.
These velocity models were subsequently used as inputs in prestack depth migration.
Mean fragment size (MFS) prediction models were subsequently developed using multiple linear regression (MLR) analysis technique.
The statistically most reliable models were subsequently subjected to validation testing in a local antenatal population.
Numerical shearing tests on stratified rock models and discrete fractures network (DFN) models were subsequently conducted.
These models were subsequently validated using test set comprising 60 derivatives.
Regression models were subsequently trained to objectively predict the consumer liking scores of the green tea model systems.
These models were subsequently used to predict the properties of virtual solar cells libraries highlighting interesting dependencies of PV properties on MO compositions.
These models were subsequently studied in more detail in [28], with a further focus on two-dimensional models and travelling waves.
These models were subsequently combined into model ensembles using (1) greedy optimisation (1,000 iterations), and (2) model stacking (Table 3).
Microbial habitat models were subsequently used to estimate microbial measures for a larger regional headwater riparian wetland dataset (n = 87), where edaphic property information was compiled.
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