Suggestions(1)
Exact(1)
Different parametric demographic models (a constant population size, exponential and logistic growth) and a nonparametric Bayesian skyline plot (BSP) were compared under strict and relaxed clock conditions, and the best models were selected by means of a Bayes factor (BF, using marginal likelihoods) implemented in Beast as already described [ 28].
Similar(59)
Pace clock condition: Two pace clocks were set up on the left side of the road at the locations indicated by half-green/half-red circles in Figure 1.
Two independent runs of 120 million generations were performed, under constant-clock conditions with a constant coalescent model of species evolution.
As expected, the combined condition obtained the highest scores, followed by the pace-clock condition, then the narrow-lane condition, and the baseline condition.
The intensity in the pace-clock condition started to increase first, followed by the combined condition and then the narrow-lane condition.
The narrow-lane condition produced the longest on-road glance duration, whereas the shortest on-road glance duration occurred under the baseline condition, with glances in the pace-clock condition and the combined condition falling in between.
Average off-road glance duration when drivers drove in the demand zone varied only across driving demands, whereby the baseline condition and the pace-clock condition produced longer off-road glances than the narrow-lane condition and the combined condition.
However, this was not the case for the latter: In-zone on-road glance duration was equivalent to that in the pace-clock condition but shorter than that under the narrow-lane condition.
For example, the pace-clock condition represented more discrete, but less predictable (the timing when the arm would move to the green portion of the clock was random), demands, whereby drivers needed to monitor the clocks as they were approaching them and could read messages at other times.
Moreover, ground Pi2 onsets recur under low IMF clock angle conditions.
All five genes simulated under these clock-like conditions showed surprisingly high estimated rate variation among the 27 lineages for both Bayesian and ML analyses (Figures 4 and 5).
Write better and faster with AI suggestions while staying true to your unique style.
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