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In Table 3 the three first columns (o.m, o.i, and m.i top-means) are retrieved after only one run, since there is no variation in the LDA coefficients as the dataset is stable in these cases.
The SW-loci corresponding to portions of the DNA that are amplified or deleted with a p-value smaller than 0.05 are removed recursively from the null dataset, until the null dataset is stable and there is no more amplified or deleted SW-locus in the null data set.
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The URIs for representing entities in the linked datasets are stable and are chosen by the LODD participants.
Using a large number of independent datasets, we showed that the stratification is stable across different datasets, regardless of which dataset is employed to derive the gene sets with which to perform the stratification.
In total, we identified 12,914 clusters of unique core genes in our dataset that are stable over all orthoMCL runs performed.
The performance of the MGA is stable and exceeds the others also in this dataset, especially in Clostridium acetobutylicum.
The results indicate that the system is stable (AROC = 0.928±0.004), rendering it suitable for predictions on the test dataset.
The country is stable.
Officer Koch is stable.
Its democracy is stable.
The rupee is stable.
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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