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Revenue split estimates range from 80% – 110% to Yahoo (higher in the beginning), and there is likely a hefty guaranteed revenue component so assuage the Yahoo board of directors.
Dating5 tended to produce the most extreme results, with inferred basal split estimates similar to those from Multidivtime, but some derived split estimates younger than those from PATHd8.
Similar to the results for the D1 split, estimates of divergence for the D2 node did not display a predictable pattern under increased taxon sampling, although the estimates obtained from balanced and unbalanced topologies were more homogeneous than those of the D1 divergence (Fig. 4D).
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Since this information is not part of macroeconomic statistics, it could be estimated using process inventory databases like ecoinvent (www.ecoivent.org), the bilateral flows of cobalt embedded in the different commodity groups determined by Nansai et al. (2014), and the end-use sector split estimated by Harper et al. (2012).
We split estimated and actual scores into tertiles (top, middle and bottom) to see whether differences existed between high and low performers.
A recent divergence and a large effective size of the ancestral population could explain the large differences in the time of split estimated by phylogenetic and coalescent-based methods.
We also investigated how different choices of genes, species tree models (with and without gene flow) and mutation rates can affect the split time estimates.
We also showed that the extrapolation of non-specific rates or the use of simpler models would lead to very different split time estimates.
For example, the most commonly used calibration point (the Papio/Macaca split) produces estimates that are too young when used tightly bound around the fossil date (6-8 Mya, Table 3).
Here, we obtained lineage-specific mutation rates of these loci from a higher-level phylogeny with a reliable fossil record and investigated how different choices of mutation rates and species tree models affected the split time estimates.
We showed here that the estimation of specific mutation rates for each locus and for the lineage of interest is a crucial aspect of a robust dating strategy since the extrapolation of mutation rates from other mammalian groups and loci may lead to very different split time estimates.
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