Why Cauchy as prior for residual error in ODE models?


I always have wondered why is so common to give a Cauchy prior to the residual error (\sigma) in ODE models.

From the prior choice recommendations page, I know that a Cauchy distribution can be considered as a weak prior. However, why not give another weakly informative prior to \sigma? Is there a special consideration for this case?.

Thanks in advance!