I think by "good" studies, they mean "the findings align with the rest of what we see, and the prognostics informed by the paper are accurate" rather than "we read the paper carefully and the investigators appear to have done the right experiment correctly."
That makes sense, but I'm still a bit confused about the specifics. So the idea is: Watson reads papers and develops a model of human biology, is asked what to do in a certain situation, gives a prescribed therapy, then is fed back the results when they try it on someone so that he can decide if the specific studies he used to make the prediction are true in practice?
http://arstechnica.com/science/2014/03/ibm-to-set-watson-loose-on-cancer-genome-data/
Can anyone more informed about Watson or Machine Learning in general comment on this application? Specifically, I'm interested in an explanation of this part:
It sounds like Watson will be trained through some standard formatted input data and then it's going to read plaintext articles and draw conclusions about them? It sounds like they're anticipating that Watson will be able to tell which studies are "good" studies as well, which sounds incredible (in both senses of the word).