You've heard the phrase, "if something is too good to be true, then it probably is" - the same thing applies in research. The quickest way to be exposed as a fraud is to submit data, for example a graph, which exactly fits the theoretical predictions with absolutely no error (or to use a recent example to submit graphs from two different experiments which have exactly identical noise profiles). In other words if you have too perfect a specimen then that will raise some cackles somewhere.
But that isn't the case here. The evidence isn't conclusive and is debatable.