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In 2002, a Swedish magazine claimed its tests found that three gasoline-powered Volvo models produced high E.M.F.
Our RF regression models produced high accuracies when using both internal and independent hold-out datasets for validation (Supplementary Table 2).
The two GS models produced high prediction accuracies for PCA1 with 0.72 ± 0.001 and 0.71 ± 0.001 for RR-BLUP and GRR, respectively.
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The case-crossover models produced higher effect estimates than time series models.
However, all three models produce high quantities of excess electricity given their dependence on variable wind and solar coupled with storage.
Applying the derived scaling values for the temporal pattern of the summer season in a hydrodynamic sewer network model produced high percentage change of peak flow between the current and future climate.
Likewise, there were 283 examples of ADRs for which the model produced high AUC scores.
Compared with other predictors, our models produce higher SN and comparable SP on bound, unbound, and independent datasets.
However, peaks in rainfall differed slightly, and the model produced higher rainfall values, predominantly in areas with high elevations.
From initial listening tests, it has been clear that using a number of bands around 8 for our model produced high-quality resynthesis without loss of the objective of the initial recording.
In the male sample, the MFP model produced higher mortality estimates for subjects at the low end of the normal category.
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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