Finally, we evaluated the effect of QM methodology on product distributions by performing MLP uplifts to different levels of theory. Uplift corresponds to performing single point energy and force evaluations on ACE AL configurations (PBE0/def2-SVP) at different levels of theory and then retraining the ACE potential to propagate classical NVE trajectories from the respective TSs. For the product distributions in Fig. , MLPs can be obtained at the desired level of theory in 100s CPUh by applying uplifts, compared with > 200,000 CPUh without uplifts. It was found that some levels of theory require more AL iterations than others, suggesting that the overlap of the configuration space within the training set may not be optimal. For example, while the product distributions are unchanged for B3LYP on additional AL, M06-2X distributions continue changing upon further AL iterations, affording ≈ 10% more product R2 P2 after 5 iterations. Product distributions vary considerably between QM methodology, with the major state varying from the reactant to R2 P2 , and the proportion of R2 P1 varying from 1% to 10% (Fig. ). This evidences the large influence that the level of theory has on the propagated dynamics and consequently on the product distribution. The differences are significantly more important than those observed when comparing classical MD and RPMD results.