41 Chapter 2: Motivation Even worse the phrase ‘surface emission’ leads to a Boolean mindset: Is there surface emission or not? This is not a useful question for a qualitative, let alone quantitative study of data; a better question would be ‘How biased are the jets?’ Surface emission as a term will not be used further in this thesis. Theoretical sensitivity quantifies the change in a model-predicted observ- able given a change in the input parameter(s). Sensitivity is a slippery slope that may easily slide into the idea of an insensitive model. Just this type of Boolean thinking led to ironic conclusions from [306] who claimed that their calculation of R$_{AA}$ became insensitive to increases in ˆ q . But by quantifying the decrease in R$_{AA}$ as a function of ˆ q in a very similar model [310] found a power law relationship in the ‘insensitive’ results, R$_{AA}$ ∼ ˆ q − 1 / $^{2}$. In this way a fixed fractional change in ˆ q leads to a fixed fractional decrease in R$_{AA}$ , which Figure 2.8: Examples of surface bias in different nuclear geometries. Simplified nuclear geometries such as hard spheres, and especially hard cylinders, create greater surface bias.