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We have successfully tested our model with a set of robustness exercises.
In the third study, we tested our model in an experimental design.
Using a survey design, we tested our model with a sample of 545 managers and professionals.
We tested our model using 264 subjects in an experimental setting.
We tested our model using annotated corpus data and found that it inferred pairings between words and object concepts with higher precision than comparison models.
We tested our model by creating a classifier for variable stars from four astronomical catalogs: MACHO, SAGE, 2MASS and UBVI and compared the results with the results obtained with classifiers learned with a subset of those catalogs.
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We tested our models on the i2b2/VA relation classification challenge dataset.
We tested our models using leave-one-PDZ-domain-out cross-validation, as domain sequence is important for performance.
We first decided to test our model for seasonal variation by comparing our microplastic concentrations (measured in July September 201515) against modelled concentrations averages for the July September periods of 2000 to 2012.
We test our model using a two-study design.
We conduct different lab experiments to test our model.
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