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The average number of triphone templates was 181,601 per speaker for the five doctors.
Based on Poisson distribution, the expected average number of mutant templates per reaction is estimated using a formula (Poisson distribution) f(0) = e−x, where x is the average number of mutants per reaction [7].
Pause density, ρpause, is defined as the average number of pauses per bp of template transcribed.
In general, the average number of words increases between the No Template and the other template conditions, as shown in Fig. 7.
The average numbers of hsp70i template copies per blastomere were calculated from the isolated cells (not all cells of dissected 8-cell embryos could be recovered) and compared to the average per blastomere values obtained from whole embryos.
In template compression, the number of Gaussian components in each new GMM was 16, the same as the GMMs of the baseline; the average number of GMMs generated for the compressed template representatives was 1,048 per doctor (the baseline was 1,905 GMMs per doctor).
In common with the first two studies, the average number of words used does vary between the different templates, although for this study the average number of words is much higher in the Profile Template condition compared to the No Template condition; the Titles Template condition had the lowest.
A differences from Study 1 is seen for the Profile Template condition, where the average number of materials, equipment, and actions is significantly decreased in the 'What did you do in the experiment?' or procedural section of the template compared to the procedural information recorded in the other two conditions.
The ER is the average number of errors per merged read (excluding gaps) with respect to the template sequence.
As shown in Fig. 1, the average number of words used by the students to record their experiments is higher in the Template condition compared to the No Template condition consistent with the expectation that the Template condition would lead to the capture of more information.
b Average number of iterations.
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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