Thanks, that's a useful alternative framing of CaSc!
FWIW, I think this adversarial version of CaSc would avoid the main examples in our post where CaSc fails to reject a false hypothesis. The common feature of our examples is "cancellation" which comes from looking at an average CaSc loss. If you only look at the loss of the worst experiment (so the maximum CaSc loss rather than the average one) you don't get these kind of cancellation problems.
Plausibly you'd run into different failure modes though, in particular, I guess the maximum measure is less smooth and gives you less information on "how wrong" your hypothesis is.