Before revision:  Large amounts of data , which are necessary to rank CVs with confidence, are cheaply generated by a deep neural network (DNN) surrogatemodel of the underlying process. The DNN predictions are made explainable by the GSA so that the DNN can be deployed to close design loops.
After revision:  Large amounts of data , which are necessary to rank CVs with confidence, are cheaply generated by a deep neural network surrogate. Subsequently, the GSA is used to explain the network predictions, and the surrogate is deployed to close design loops.