For scientific progress to be made in the cG×E field, it is crucial to begin to differentiate the true cG×E effects from the false. How can this be accomplished? One step forward would be to encourage authors to submit and editors to accept null reports in order to reduce the publication biases present in the field, but incentives to publish positive reports are unlikely to change for either authors or editors anytime soon. Perhaps a more realistic way to begin discerning true results in the cG×E field is to acknowledge that false positive results are a natural consequence of the incentive structure that exists in modern science, and that because of this, authors, consumers, editors, and reviewers should recalibrate their views on what constitutes an important scientific contribution. Given the likely high false positive rate among novel findings (19) and indirect replications (36, 37) and the low false positive rate among direct replications (36), well-powered studies conducted with the express purpose of closely replicating previous findings should be viewed as more scientifically important than novel “groundbreaking” cG×E results or indirect
