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1. Use a non-institutional email address, or have a hospital affiliation, 2. Have no international co-authors.
And they acknowledge 86% sensitivity and 44% specificity. It's a coin-toss which biases massively against research from outside the US and Western Europe.
This "paper" is bigoted nonsense.
Strange world
The metrics used in this paper are... deeply flawed, to the point that the authors admit that they label nearly half of known good papers in a curated sample as "fake" -- and particularly likely to generate false positives for researchers whose institutions don't, say, run their own email systems (as is common in large chunks of the world). Here's a rundown of the flaws from an epidemiologist with a sideline in scien…
Adding new tools to 'detect' that don't solve the original problem, they might reduce the second-order problem, but do not touch the source problem. These are band-aids trying to stop a flood of bad science
You'd need to use some obfuscated correspondence email to complete the loop.
Unfortunately, it's an open secret that fake or low-effort almost useless papers are very common in every area of scientific research. Typically, it doesn't affect people working in that specific area - they develop/have a sixth sense to detect bullshit papers - it comes with experience but depends on several factors including the authors reputation, their institution (for the first screening), what journal/conferenc…
The metrics used in this paper are... deeply flawed, to the point that the authors admit that they label nearly half of known good papers in a curated sample as "fake" -- and particularly likely to generate false positives for researchers whose institutions don't, say, run their own email systems (as is common in large chunks of the world). Here's a rundown of the flaws from an epidemiologist with a sideline in scien…
Kinda similar to those researchers years back who proved how easy it was to go into certain social science journals as long as you copied their ideology.
> Sabel’s tool relies on just two indicators — authors who use private, noninstitutional email addresses, and [...] Uh huh. I didn't realize until today that all my papers are fake because I give contact information that won't go stale in 3 years, instead of my work email.
The researchers in this paper use an astonishingly biased "fake paper detector", requiring only two conditions to be met for any paper to be considered "fake": 1. Use a non-institutional email address, or have a hospital affiliation, 2. Have no international co-authors. And they acknowledge 86% sensitivity and 44% specificity. It's a coin-toss which biases massively against research from outside the US and Western Eu…
If you know the true prevalence of a disease in a population, and the sensitivity and specificity of your test, you can predict how many positive measurements you obtain. Vice versa, from the (flawed raw) measurement, given sensitivity and specificity, you can estimate the true prevalence.
Furthermore, they’re explicitly saying that “red flagging” by their simple indicator doesn’t mean that the paper is fake, but that it merits higher scrutiny.
ETA: I mean, it could still all be bullshit (by virtue of some bias or so), but you’ll need to argue a bit harder to establish that.
ETA2: Actually, not sure that’s what they’ve done. They might have just reported the raw (very bad) measurement (that they call “potential red flagged fake paper”), without doing the obvious next step outlined above, and without applying any confidence intervals. So, it might actually be a pretty crap paper (though possibly technically correct) coupled with some mediocre reporting layered on top. Isn’t basic statistics taught anymore?