One explanation is that these tokens only appear in pairs in valid SMILES, which indicates that learning how to create a correct molecular SMILES with these tokens is much more difficult than with other equally frequent tokens, as both tokens in each pair must be correctly positioned with respect to each other. Additionally, molecules in GDB-13 (max. 13 heavy atoms) with more than 3 rings have extremely complex topologies. When performing the same analysis for 2-grams same interpretation applies (Figure ): the count is correlated with the average frequency and the most frequent 2-grams (CC, C1, C(, )C, C=) match the SMILES of simple molecules and the less frequent (5o, 3[N+], 7O, 7(, 72) match exclusively molecules with complex topologies and several rings. This implies that the n-grams that appear less times in the database, i.e. in the training set, are not learned correctly and thus have a lower probability of being sampled. Therefore, molecules that contain an increasing number of low probability n-grams in their canonical SMILES, will progressively have a lower probability of being sampled ((Equation ).