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Using Finite Element Method (FEM) models, we select the best design, able to generate the highest plate displacement amplitude as possible.
When selecting one of these models, we select the model that comes from the largest cluster and has the best c-score.
For each of these models, we select a percentage of the population to serve as the individuals who introduce the virus in the population; specifically we chose to infect 11 individuals.
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For the purpose of evaluating the candidate secular variation models, we selected 87 INTERMAGNET magnetic observatories; see Fig. 5.
In those cases where nested models occurred within the 90% confidence set of models, we selected the most parsimonious model for inference (for an overview of 90% confidence set of models, see Additional file 5).
With e-pharmacophore III giving the best possible BEDROC and RIE score among the other pharmacophore models, we selected this pharmacophore model for our prepared virtual database of Asinex.
From this set of models, we selected the most parsimonious (i.e., the model with the lowest AICc).
To test this, among nine different domain-peptide complex models we selected a single structure that had the highest correlation with SPOT data (the best complex model).
Since the opinion of epidemiologists and clinical researchers had to be incorporated based on pre-existing experiences with collaboration models, we selected researchers who had been previously exposed to different incentives to collaborate.
From the above models, we selected the best performing model based on the Akaike Information Criterion statistic.
For the Rab9 model, we selected 94 Opisthokonta species, and for the metazoan models, we selected 53 species (see Additional file 3).
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