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…
I havent looked at the details here, but if you make a prediction model and if that prediction model is robust enough to explain with great accuracy something with 2 or 3 variables, it's not going to be "biased", it's just going to be robust and right more often than not using only these few variables (as long as the training data was broad enough).