[southern_cross]

Sadly, once the statistical methods being used here and the types of anomalies being found become well-known, it's probably not too hard for fakers to adjust their "results" so that such anomalies are far more difficult (if not impossible) to detect. For example, if an analysis would show that your experimental data is maybe a bit too clean, in a way that wouldn't normally turn up in the real world and would therefore cast doubt on its validity, then you just need to make sure that you dirty it up a little before publication.