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Similarly, the model predicted less number of deaths caused by macrovascular events in the group treated with SAXA + MET than in the SU + MET one (149.6 vs. 152.8).
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At its worst, if the model predicts less than a 5% chance of success, the picture is forbidding.
The MOMA model predicts less growth and more secretion, but also exhibits a trade-off between the two.
A single exception exists for the first two on-treatment measurement times for BSAP after administration of 30 mg Q3M, where the model predicts less suppression than observed.
This could be attributable partly to exposure misclassification: LUR models predicted less of the variance of outdoor concentrations of PMcoarse (average R of models = 71%) than of NOx (R = 86%) (Beelen et al. 2013; Eeftens et al. 2012a).
There was no difference in range fluctuations for species in different movement categories (p = 0.4612) It is therefore the wide-ranging, ubiquitous and arid species that have the most marked difference between climate and weather area predictions, the weather models predicting less area, and the least fluctuation across months.
These models predict less or no orientation costs for relatively small rotations which preserve parts and their spatial relations (and, therefore, the same structural description), but they do predict costs for larger rotations which perturb the spatial relations between parts [2], [23].
In general, theoretical models predict less of an evolutionary response to harvesting if fishing mortality is lower (Law and Grey 1989; Ernande et al. 2004; Brown et al. 2008).
Based on the fact that previous FE models of TKAs predicted less bone resorption when the femoral reconstruction was less rigid or fully unbonded (van Lenthe et al. 2002), we developed a sliding stem mechanism.
At the end of the 1988 epizootic, the model predicted that less than 5% of the population had not been infected by PDV, while 60% had died of the disease, and 35% recovered.
The model that included only WBAL predicted less severe but still important reductions in its potential distribution.
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