In the second case study, when the auxiliary task is Suzuki R2, MTBO appears to perform poorly -this is likely due to the low reactivity observed in Suzuki R2 and a noisy simulation benchmark (see Figure ). In this case, the best conditions from the training task also do not perform well on the main task, but the yield is moderate enough that it makes further exploration of the chemical space initially difficult in obtaining a better response. This suggests that MTBO may bias the training data in these circumstances when higher yields are possible but not expected, when given very low-yielding auxiliary tasks.