Coverage then decreased slightly for the initial sequence methods (≈ 64%). We note that further downward bias can be introduced by truncating time series with MSER methods prior to calculating confidence intervals, as done here; by definition, MSER picks the truncation point which minimises the estimated standard error. This bias will be greater for methods which are more prone to over-discarding. As shown by Equation 18, Chodera's method of maximising the effective sample size is closely related to MSER, so the issue of downwards-biased uncertainty estimates also applies. When using generalised MSER or maximum effective sample size truncation metrics, users should be aware that they may be introducing additional downwards bias to subsequent uncertainty estimates. This is without even considering that single runs often become stuck in local minima in configuration space, an issue which multiple runs may help to diagnose.