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Both datasets and the models based on them are shown together in Fig. 3.
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The results are checked against large datasets and the model is finally used to discuss on the influence of the various parameters on the governing shear-transfer actions.
Note that both the dataset and the models are accessed indirectly via URIs, so the only data transferred on input and output are those URIs, not actual content.
We then selected the best derivation dataset and the models with the highest predictive performance.
Each validation resource for example, contains information about the dataset and the model, so the underlying procedures can be invoked.
Akaike's information criterion is used when comparing models fitted to the same dataset and the model with the lower AIC is generally preferred.
The AIC is used when comparing models with different numbers of parameters fitted to the same dataset and the model with the lower AIC is generally preferred.
Indeed, the obtained dataset and the model code are made freely available from the authors and can be used for hydrological and satellite soil moisture products validation studies.
One field plot at a time was excluded from the dataset, and the model was fitted based on n-1 plots to predict the AGB of the left out plot.
The datasets and the benchmarked models are available on the Online Chemical Modeling Environment (http://ochem.eu).eu
Many data mining techniques have been applied to activity and ADMET datasets and the resulting models are being used to understand quantitative structure activity relationships and design new libraries.
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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