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Since the number of female speakers in the corpus is very small, we used only the male speakers test set for voice analysis.
Because the potato (S. tuberosum) mRNA database was small, we used potato ESTs in mapping.
Since the sample size was relatively small, we used all data in the training set.
When the numbers of events were small, we used Fisher's exact test.
If the femoral head was too small, we used the resected femoral shaft, after the osteotomy was complete.
Because any such expression variation may be small, we used the sensitive and quantitative qRT-PCR assay.
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Eugenie Teasley: We've piloted different projects that have different types of impact – again, as we are small, we use tech to reach thousands of people.
Considering the fact that the number of the false matches is usually very small, we use the following process to identify these false matches.
In the case of individual sequence models, as the number of observations is small, we use a single component mixture for each state.
As the number of tumor sample is too small, we use stratified 10-fold cross validation in all our experiments.
Although the number of such incomplete sets due to either scenario should be small, we use an approach of Huberman and Langholz [ 51] to accommodate both problems.
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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