Quantitative Prediction of Computational Quality (so the S and C Folks will Accept it)

Our choice of title may seem strange but we mean each word. In this talk, we are not going to be concerned with computations made "after the fact", i.e. those for which data are available and which are being conducted for explanation and insight. Here we are interested in preventing S&C design problems by finding them through computation before data are available. For such a computation to have any credibility with those who absorb the risk, it is necessary to quantitatively PREDICT the quality of the computational results.