That works if the thing is something you can remove from the experiment and model separately, then put it back. In CERN many variables are tied to this one huge machine that is one of its kind.
Is there a concrete reason we can't be naive and just bootstrap confidence intervals for example? Of course I defer to the physicists here – but I'm curious whether there's some simple high-level reason the usual tricks don't work.
See also: https://twitter.com/pietrovischia/status/1512174848558219270
This does not seems like bleeding edge, it seems like "Gaussian approximations for everything."
In fact, this is the reference for the technique they used: https://cds.cern.ch/record/183996/files/OUNP-88-05.pdf. (Although the criticism seems to be leveled at the way they estimate the correlations, not that linear estimator specifically?)