I would like to see a comparison between random generated uniform features and these features. Can you fit the noise and come up with "statistically significant

I would like to see a comparison between random generated uniform features and these features. Can you fit the noise and come up with "statistically significant" predictions? If so, is anyone doing any better than can be done on random data? If no one is doing better than that, what is the likelihood that these aren't any better than monkey with a dartboard? I would love to see peer reviewed articles from numerai with some of their behind the scenes results.