The data was sound. They formed a hypothesis. They got a better explanation. Now they have a better hypothesis for the data anamoly. I don't think it's fair to fault them or to discredit the effort.
What the authors did falls into the trap of a very stereotypical criticism of data science and doesn't do data science any favors.