Demonstrated ownership of a production pipeline incident that caused silent data loss, corrupt data, or an unavailable downstream dataset, including detection, root cause, recovery or backfill, and a test or monitor that prevented recurrence. Success means a model behavior can be traced through its dataset, run, software, calibration, commands, interventions, outcomes, and hardware state—and that dataset revisions remain reproducible rather than becoming ungoverned data volume.