This is because prediction probability/loss of spurious instances tend to be lower than that of genuine instances (He and Garcia, 2009).
the Bayesian Uncertainty model (Feinman et al., 2017) defines spurious instances as those that have greater uncertainty (variance) in their stochastic predictions, and the Variational Inference model (Rehbein and Ruppenhofer, 2017;Hovy et al., 2013) expects greater posterior entropy in predictions made for spurious instances.