Random subsampling was performed on the 10 x 10 and 10 x 20 protocols in order to generate 95% confidence intervals (CIs) for a varying number of replicas. Random subsampling is a modified form of bootstrapping in which less observations (i.e., replicas) are used to generate each resample of the data. This allows one to predict how a differing number of replicas would impact the precision of the results obtained. Random subsampling was performed using replica ranges of 1-10, with resampling performed 5000 times in order to calculate the average values and the 95% CIs.