It is widely known that correlation does not necessarily imply causation. However, after recognizing that the correlation alone doesn't prove causation, what needs to happen in order to evaluate whether the causation exists? What's the missing ingredient that make some subset of correlations indicative of actual causation.
The following videos discuss the issue, mostly about why you can't infer causation for correlation, but also touch on what's missing:
Both videos state the basic idea that in order to infer causation from correlation, you need to know the causal mechanism. You have to know how the one item caused the other.
This strikes me as incorrect. I would say that in order to distinguish spurious correlation from causative ones you have to investigate which hypotheses generate accurate predictions. I can postulate seemingly plausible mechanisms for many spurious correlations, and I don't need to know the underlying mechanism to infer the existence of a correlation. The only thing that really matters in establishing a hypothesis is the track record of predictions.
Am I on base here? Or is my understanding of the scientific method flawed?