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After the validation by tests, the model is used to predict the ultimate resistance of connections at both ambient and elevated temperatures.
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By testing the model for a range of incentives, we demonstrate its capability to inform and evaluate policy options.
We calibrate the sigmoid loss function by testing the model on a set of cross-validation examples taken out of the training set before optimizing the model.
The fidelity of the model has been evaluated by testing the model against experimental data from a braking system test bed.
The importance of taking into account the influence of the droplets on the fluctuations is demonstrated by testing the model with and without the corresponding terms.
By testing the model's sensitivity to the relevant parameter, we find that the pace of electrification will significantly contain the spiking of carbon prices because electricity can be produced from carbon-free or less carbon-intensive technologies.
This result was supported partially by testing the model constrained to a single latent factor.
The validity of the approach was then established by testing the model on 129 different VFM datasets.
Validation of the model was performed by testing the model code and checking results and this was performed by a second analyst.
The diagnostic value of CVD risk estimates derived using default risk factor values was investigated by testing the model in the Health Survey for England of 2003 [ 5].
The replication analysis confirms the robustness of the relationships in a statistical model developed with one data set by testing the model with other data sets.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com