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Our model generates intuitive comparative statics that describe the optimal expansiveness or restrictiveness of equity.
Figure 3 shows the participation rates our model generates are nicely scattered.
Our model generates competition between two featureless teams, and the Markov model provides a data-driven mechanism by which some pairs of teams may behave as if they have small or large differences in latent skill.
Our model generates new income for them and brings bumper crops of dimpled and off-color fruits and vegetables into our urban kitchen.
Our model generates individuals from an equal number of mothers and fathers.
Our model generates numerical results and it is tempting to regard the predictions as definite.
Similar(47)
We make predictions about drugs that may target ABL1 from our model generated via the gene-disease-drug association which must satisfy two conditions: There exists a gene-disease-drug path in Chem2Bio2RDF The calculated association score for the gene-drug pair should be less than a certain threshold.
In general, our models generate very different predictions of structural change, as discussed in the following.
In this paper, we report the validity of our models generated using functional feature hypotheses and topological descriptors.
Our modeling generated global structures for the domain with a similar core region between the models for the two secondary structures.
According to our experiments on single and multi-core processors, our prediction model generates highly accurate estimations for unsampled points in the design space and show the robustness for the worst-case prediction.
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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