this post was submitted on 17 Oct 2024
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Yeah, reviewing is about making sure the methods are sound and the conclusions are supported by the data. Whether or not the data are correct is largely something that the reviewer cannot determine.
If a machine spits out a reading of 5.3, but the paper says 6.2, the reviewer can't catch that. If numbers are too perfect, you might be suspicious of it, but it's really not your job to go all forensic accountant on the data.