 One way to escape the extrapolator’s circle is to black box the mechanisms being compared and instead treat the problem of extrapolation as a statistical problem (cf. Cook and Campbell 1979). This method avoids the circle because it eliminates the need to know if two mechanisms are similar. All that matters is that two outcomes are produced to a statistically significant degree, given the same intervention. For this reason, statistically significant outcomes in clinical trials are at the top of the evidence hierarchy in biomedical research (Sackett et al. 1996). One problem with relying merely on statistics to solve the problem of extrapolation, however, is that it cannot show that an observed correlation between model and target is the result of intervention and not a confounder.  