Similar prediction markets have been used for many years for elections, mimicking the movement of the betting line in sports. Basically, the results in this instance indicated that informed scientists were clear from the get-go that what they were reading would not hold up.

So yes, that’s a problem. There has been resistance to fixing it, some of which has come from prominent researchers at leading universities. But many, if not most, scientists are aware of the seriousness of the replication crisis and fear its corrosive effects on public trust in science.

The challenge is what to do next. One potential solution is preregistration, in which researchers beginning a study publish their analysis plan before collecting their data.

Preregistration can be seen as a sort of time-reversed replication, a firewall against “data dredging,” the inclination to go looking for results when your first idea doesn’t pan out.

But it won’t fix the problem on its own.

The replication crisis in science is often presented as an issue of scientific procedure or integrity. But all the careful procedure and all the honesty in the world won’t help if your signal (the pattern you’re looking for) is small, and the variation (all the confounders, the other things that might explain this pattern) is high.

From this perspective, the crisis in science is more fundamental, and it involves moving beyond the existing model of routine discovery.