Your English writing platform
Discover LudwigExact(60)
The mean expected null MOH is shown in figures as a grey horizontal line (see Supporting Information S1 for calculations).
To explore the mean residual risk per sampling interval and the mean expected QC related cost per time unit using either optimal or predefined QC sampling time intervals I simulated the three analytical systems I to III presented in table 1.
They allowed plastic drivers of migration timing, including river flow, a direct (within-year) effect of temperature, and oceanic factors such as the PDO and the North Pacific Gyre Oscillation (NPGO, Di Lorenzo et al. 2008) to modify the mean expected migration timing as plastic effects.
Deducting 6 years for leading time bias, the mean expected additional life expectancy of the screening group was 6 to 7 years longer than that of the non-screening group.
The grey line shows the mean expected FRic for groups of randomly sampled fishes (see Methods 'Functional richness of more and less attractive species'), and shaded areas represent the standard deviations (more than 1,000 replications).
The power regression line (Equation 3) provides estimates for the mean expected pollen deposition at given distances from the pollen source.
For each population and each population pair we used the mean number of alleles per locus, the mean expected heterozygosity and the mean allelic size variance.
To characterize the mean expected geographic matrix of δDf values for HY scaup, we regressed δDf values from feathers in pre-fledged scaup on the expected δDp values at the sites where the feathers were sampled (Fig. 1).
We used this regression model as way to calibrate the precipitation isoscape to what we would expect for HY feathers, effectively modeling the mean expected feather isoscape for HY scaup [22].
The EVPI is the difference between the mean expected NHB with perfect information from the probabilistic sensitivity analysis and the mean NHB with current information from the primary analysis.
Excess LOS was computed as the difference between observed LOS and the mean expected LOS.
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