Before revision:  For such models, there is typically a wide variation in scales in that the different species and reaction rates vary over several orders of magnitude. Quantifying how different numerical approximation techniques behave in this settingtherefore requires that these scalings be taken into account in an appropriate manner .
After revision:  For such models, there is typically a wide variation in temporal and other quantitative scales. In this multi-scale setting it is typically an extremely difficult task to perform approximations, such as Langevin approximations or law of large number type arguments, to simplify a system. Therefore, numerical methods oftentimes are the only reasonable means by which such models can be understood in real time. In this paper we provide a general framework for understanding the weak error of numerical approximation techniques behave in this settingtherefore requires that these scalings be taken into account in an appropriate manner .