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Our simulation compares performance of an Oppnet with a baseline case in which no Oppnet is used.
> -wrap-foot> The baseline case in which no class is closed ("No closure") has a zero cost in terms of lost school days.
The scenario with AV treatment is compared to the baseline case in which no intervention is considered, i.e. the probability of treatment is set equal to 0 in all countries.
Examples are given relative to Fig. 1(A), a baseline case in which morbidity onset occurs at age X and death occurs at age Y. Figure 1(B) shows the scenario posited by Fries whereby morbidity onset is delayed to a greater extent than increases in survival.
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For example, the effect of DA over time is compared with the pre-DA baseline; in cases in which the concentration of DA was increased to achieve >50% inhibition, the firing rates are compared with the baseline before any DA was added to the superfusate.
The only numeric glycemic target was if HbA1c exceeded 13.5%, the mean +2 SD of the cohort's baseline value, in which case treatment was intensified independent of whether the subject had symptoms.
In addition to comparisons of the randomized therapy groups, the data set can be utilized to conduct cost-effectiveness analyses by comparing groups defined by nonrandomized baseline factors, in which case the randomization no longer plays any part and confounding factors generally need to be adjusted for.
It can be considered either as a part of the longitudinal response, and thus the response vector has 7 elements corresponding to the times 0, 1,..., 6 years, or as a baseline covariate, in which case the response vector has 6 elements.
The strategy usually employed is to provide a few cases in which the proposed classifier outperforms baseline classifiers according to some performance measure.
It might be a "current baseline," in which case it represents observable, present-day conditions.
Such relabeling would not change anything, for we would still have to distinguish between those cases in which B is harmed relative to both the fairness baseline and the no-transaction baseline and those cases where B is harmed only by reference to the fairness baseline but not by reference to the no-transaction baseline.
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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