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The models we made showing the tower completely wrinkly just didn't look tough enough for New York".
To avoid simultaneous use of explanatory variables with large correlations in the models, we made a selection among variables with correlations greater than 0.8 or smaller than − 0.8.
As we needed to decide which ratio between Czech and Spanish training data was the best for training the acoustic models, we made a comparative experiment between the AM_CZ, AM_CZ&es and AM_cz&ES_cross acoustic models (Table 3).
In the final models, we made use of two different sets of confounders.
Then, using the optimized models, we made predictions on a test set of ETOP-treated samples (external validation).
Furthermore, to perform in vivo cell lineage tracing in both mouse models, we made use of the ROSA26 Cre reporter line (R26R) [ 27], which expresses β-galactosidase (β-gal) upon Cre-mediated recombination.
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When we train our models, we make sure the data is balanced".
Contrarily to previous models, we make no assumption about a constant, expression-level independent cluster/monomer ratio or the existence of lipid rafts, thus circumventing controversy surrounding their actuality.
The point is to acknowledge the consequences of phenomenology and guessing for the kinds of models we make.
While we propose here the FIRM structure and have strived to maintain consistency of units across the models, we make no attempt at validation and later we propose approaches to test this important question.
On the dental model, we made occlusal sprint for patients and they used them for three months.
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CEO of Professional Science Editing for Scientists @ prosciediting.com