Dense distributed acoustic sensing (DAS) records can contain thousands of sensor rows but only one hazard trajectory, allowing row-wise evaluation to overstate warning evidence. We present a finite-record framework linking each claim to its valid unit, split, target provenance, background support, metric, and interpretation boundary. Hollin Hill contains one rainfall-triggered event. In a controlled section-split stress test, every one of 844 evaluation timestamps recurs in fitting, and clock probes reconstruct the shared chronology; purges from 30 min to 24 h reduce usable class support but cannot create independent events. A causal retrospective replay therefore reports alert burden, anchor-relative declaration delay, and rupture-horizon occupancy separately. Brienz provides a second, clustered collapse sequence. Across ten grouped partitions, the balanced-accuracy increase from full sibling-view exposure is positive in every partition, while the one-sibling matched contrast is small. Forty-three of 97 radar intervals match 43 of 101 DAS episodes; a 5,000-draw within-day circular-shift null yields a median of 14 matches (95 % range 8–20; empirical <em>p</em> < 0.001), with the association persisting after excluding 15 June. Sensor-dense data are not event-dense, and chronology, augmentation, episode construction, and incomplete reference catalogs must be represented before DAS results support engineering-warning claims.