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First, variables were tested variable-by-variable. Variables showing an association at a significance level of P < 0.2 were arbitrarily selected for multivariable analysis (forward and backward selection procedures).
Within cluster A, three isolates (#1.1.03, #1.4.06 and #1.3.14) which belonged to three highly similar (> 85%) sub-clusters were arbitrarily selected for further characterization.
Results highlight the point that non-conservative results may be obtained if single cumulative probability distributions are arbitrarily selected for model parameters in the face of imprecise information and the Monte Carlo method is used under the assumption of stochastic independence.
Cut-off values of 0.33 and 0.66 were arbitrarily selected for the purpose of this analysis.
The PMA response was similar at commonly used dosages in the literature (100 300 nM) as well as at doses 100 times below those concentrations, so 150 nM was arbitrarily selected for the positive control as it was a modest dose relative to the literature.
Three positive clones containing inserts were arbitrarily selected for each sample and sequenced on both strands.
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To avoid sampling bias, a single allele (haplotype sequence) was arbitrarily selected from each specimen for the analysis.
Second, single values for parameters G, d, K and θ were arbitrarily selected looking for the minimum set of parameters presenting the best class separability.
The number of preset classes (k) is an arbitrarily selected parameter for the K-means algorithm, which needs a user's specification or through optimization.
Open image in new window Fig. 4 Plot of t test statistic for alcoholic and control SE feature vectors Open image in new window Fig. 5 Bar plot of SE mean values in arbitrarily selected channels for alcoholic/control subjects.
The FE-SEM images on the very left hand side of each image set are arbitrarily selected images for the reference and do not correspond to the Raman mapping images (mapping area, 15 × 15 μm2; scale bar, 1.0 μm).
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