Model sensitivity testing (from the variance-based method of Saltelli et al. [11]) reveals that the model is mostly sensitive to stiffness.

<p>Parameter values are varied in a Sobol-distributed fashion according to <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0137289#pone.0137289.t001" target="_blank">Table 1</a>. First order sensitivity, in purple, is the error that would be removed if the parameter was fixed at its nominal value. Total sensitivity, in teal, shows error that would remain if all other parameters were fixed at their nominal values.