The absolute optimal overlay score can also provide valuable information about the reaction under study. High optimal RMSE overlay scores reflect effects that can lower the confidence in the global reaction order afforded by VTNA, such as noisy kinetic data or insufficient data point density for accurate numerical integration, as well as more complex reaction mechanisms giving changing order values, e.g. catalyst deactivation. To improve the utility of absolute overlay score values, it is necessary to limit the influence of factors other than the degree of concentration profile overlay. For example, to prevent the concentration scale from influencing goodness-offit values, Auto-VTNA normalises the y-axis prior to generating the overlay score. Moreover, the effect of over-and underfitting on the overlay score is limited by employing a flexible 5 th or 7 th degree monotonic polynomial fit (see ESI, Section S3). Lastly, to facilitate the comparison of optimal overlay scores obtained with different datasets, RMSE has been set as the default goodness-of-fit measure. The blue dots illustrate the order combination values with overlay scores within 15% of the optimal point at (1.03,1.02).