I work on large multi-center clinical trials as a machine learning engineer. One of my projects involves the semi-automation of the detection of fraudulent data. There's one link in the chain here missing that some people here seem to be ignoring. The authors of this post (while entirely correct) draw no link between "bad data" (which is doubtlessly responsible for a large number of "bad papers"/"bad trials") and "ba…
No one I know has committed fraud in their research. I've seen mistakes in their code however, but that is another story.