In Step III of the procedure, the significance of the network measures is assessed by means of a random graph null model. This is important, as often the measured values depend, in unknown ways, on the CRN size, its edge density and other intrinsic system properties. For this reason, it is common in network science to compare statistics on a given network to randomized versions of the same network, to see whether they stand out, i.e., are significant. In other words, these so-called random graph null models allow the interpretation of all possible network statistics by comparing the statistic on the data to the statistic on the randomized versions with the same intrinsic network properties. This approach has proven extremely successful in e.g., metabolic, genetic and protein networks, and we propose it can be applied to out-of-equilibrium networks relevant to systems chemistry.