Refinement with the alternative model could resolve more erroneous regions than refinement from the original model. Thus, the initially best model is not always the best starting point for refinement. This raises Applying residue-based analysis metrics (see Methods) we found that moderately incorrect residues were the most likely to be refined. The residues that experienced the most improvements may have RMSD deviations between 2.5 to 5 Å, or S-scores between 0.5 and 0.8 (Figure ). Similarly, in terms of the residuewise lDDT score, residues that have values between 0.5 and 0.8 had the highest chance of being refined.