That's a sweeping over-generalization. More like "many inferences based on statistics are not as strong as they appear to be many are not even true". That article is important (and well known) for a certain type of life sciences publications; it's a problem that is being addressed already. That's another good thing about science, you can measure how wrong you are.

And how did that research come to the conclusion that most research comes out wrong? Statistically-rigorous research.

Second: it remains a question of degree. Most preliminary medical research, for example, suffers from heavy biases, but it remains far more predictive than the "alternative medicine" beliefs that are more than 90% incorrect.