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In contrast to prior models, we include the flow rate or velocity dependence of the inter-phase heat and mass transport coefficients.
Unlike previous models, we include weighted vector satellite data at all latitudes by utilising two noise estimators.
In both BC and CRC models, we include compositional factors and other county-level variables representing contextual factors related to both supply and demand.
In the binomial models, we include coercive mobility, percent of the population in the zip code without a high school diploma, percent unemployed, the percent of the population in rural areas, the percent of the population who are over 65 years old, population density, concentrated disadvantage, and the spatial lag of the dependent variable.
In line with previous two-sex models, we include the effect of demographic sex differences.
In all our models, we include a variable for the term that students were enrolled in the class.
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In the BC models we included only females, whereas in CRC models we included both males and females.
In all models we included lynx density, number of FS available, and season in order to control their effects.
In the first step of the models, we included two predictors: the trial number 1-1500) and a variable coding whether a trial was correct (1) or incorrect (0).
In all models, we included a random intercept for the time step of each observation to control for possible autocorrelation among the data points.
In all models, we included an interaction between morph and sex to test whether there are sex-specific associations between morph and antioxidant levels and oxidative stress.
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