False negatives include for the residual variance to be negative and the coefficient of determination r-squared to be negative, after modelling. To avoid these false negatives, in the case of the variance, conduct a Bayesian-based modelling by assigning a prior distribution to the residual variance. With data available update this distribution into a posterior distribution and obtain Bayes estimate of the variance., and so on.