Not surprisingly, there are bigger differences for the larger scale features not specifically encoded in the rules such as the type of ring (Table ). For example, there are many fewer benzene-type rings Table . Number of occurrences of different ring-types the first 1000 structures of the ZINC data set ("ZINC"), and in 1000 structures generate by the GB-GM method using the ZINC probabilities ("GB-GM(62%)" and a probability set where the probability of [*]=[*]-[*] type bonding is increased to 80% ("GB-GM(80%)") Ring-type ZINC GM(62%) GM(80%) ML-based results reported by Yang et al. , while also being orders of magnitude computationally more efficient. Similarly, the GB-GA method finds molecules with maximum J(m)-scores that, depending on the method, often are several units larger than those found with ML-based approaches. These molecules bear little resemblance to the molecules used to construct the initial mating pool, indicating that the GB-GA approach can traverse a relatively large distance in chemical space using relatively few (50) generations.