Yup. The results look beautiful. My first question here was how do we know the results are not 'hallucinated' or infilled by the ML system? The fact that it

Yup. The results look beautiful. My first question here was how do we know the results are not 'hallucinated' or infilled by the ML system? The fact that it was fed simulated data makes this really circular. If the goal is to get hard real-world data to validate the simulations, then training the machine that generates an "improved" data set on the simulation data itself would greatly increase the likelihood that the results will match the inputs, but not because that is what is actually out in reality. Obviously, the people doing this are vastly more expert than I am, but it'd be good to see an explanation of how they are avoiding this fundamental issue.