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We provide details of the models performance in predicting hourly NO X –NO2 O3 concentrations over a detailed (20 m × 20 m) grid in London in 2006.
The country used for the study is Italy, a large European country that provides the necessary geographic and population heterogeneity to assess the models' performance in the case of highly-structured populations.
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The forecast horizon is selected as 2, 10, and 40 days ahead to evaluate the models' performances in longer horizons.
In contrast to both models, performances in the MWM task and LTP are surprisingly enhanced in the Ts1Yah mice.
Dots represent the model performance in the low (red), moderate (green) and high (blue) performer classes.
Sylvester et al. [ 33] performed bootstrap resampling of all the IPD available and then examined model performance in these samples, leading to a bias-corrected C-statistic.
The model performance in different scales can be evaluated better.
This probably caused the bad modeling performance in the work cited above [45].
Validation of clinical prediction models traditionally refers to the assessment of model performance in new patients.
Several statistical measures were applied to quantify the model performance in and above the breathing zone.
The model performance in terms of network latency, energy consumption, and scalability is analyzed through simulation.
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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