If the target molecule t matches any reaction outcome p within the set, the precursor set is said to be "cycle-consistent". For the purpose of this case study, n is taken to be 2. This number was chosen according to the forward synthesis model. In this case study, an unbiased model was selected known as WLDN5 . Herein, unbiased refers to any model architecture that is different from the benchmarked retrosynthesis frameworks. In doing so, we suggest that the forward model should not implicitly favour any of the three retrosynthesis categories. WLDN5 is seen to have a competitive accuracy with a top-1 and top-2 accuracy of 85.6% and 90.5%, respectively. Since there is a significant improvement in model accuracy between the top-1/2 accuracy, n was selected accordingly (n=2). Theoretically, n can assume any number larger than 1. However, this comes with increasing computational demand with decreasing marginal utility. The round-trip was scored through the round-trip accuracy as shown in Equation . The accuracy measures the percentage of predictions, for which the precursor set i is found to be "cycle-consistent". A double-sum is employed to average over all T targets in the dataset of k reactant sets: