7. Running a whole cohort

Background. A real study has tens to hundreds of subjects. Running them is a scheduling question, not a scientific one: the backend and run policy change speed and failure handling, never the habitat labels.

Purpose. Run the same study on the serial and process backends and check the labels match; see what happens when one subject fails (on_subject_failure), resume from checkpoints, set a per-subject timeout, cap workers to the GPUs, and learn when parallel is actually worth it (on a tiny cohort serial can be faster because Windows spawn start-up dominates).

Running the same study on each backend