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To make the calculated TScs applicable for the final inferences, the achieved TScs need some kind of manipulation.
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The aim of the comparisons with these two methods is to show how the different parameters affect the final inference for the mobile tracking.
By contrast, at early stages, this influence may be vital to the final inference result.
Not much is known about the strength of the influence of omitting or including interactions on the final inference.
However, the second step is just as crucial and non-trivial, but much less attention has been paid to the final inference of the methylation states.
After discarding the burn-in phase the final inference was based on a total of 200 000-225 000 samples from the posterior for all conducted Bayesian analyses.
This is followed for each of the three focus groups separately, and final inferences were drawn by synthesizing inferences from all these groups.
Final inferences were based on 1000 approximately independent draws from the posterior (after discarding burn-in samples and thinning to de-correlate samples 26).
We believe that this approximation is not crucial for our final inferences.
Although some of the applied methods suggested that a low proportion of HS was present inside Great Egret nests, those results were not consistent among methods, thus, were not taken into account for our final inferences.
For the final phylogenetic inference, we compared support inferred from FcLM with ML bootstrap support.
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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