Because of the poor correlation between individual errors and the standard deviation, researchers have explored other metrics for benchmarking the relationship between uncertainty and errors. For example, if we instead plot the ratio of the random errors and the standard deviations (|Z| = |ϵ|/σ; Figure ) we see that their distribution (which is independent of σ) follows a normal distribution with a standard deviation of 1. The extent to which the Z-distribution differs from the normal distribution can be quantified by comparing their areas, and the difference is known as the miscalibration area (A mis ; Figure ). However, a systematic over and under estimation of the uncertainties at certain σ-ranges can lead to cancellation of errors and small values for A mis (Figure ).