Illuminating ‘the ugly side of science’: fresh incentives for reporting negative results

"New data repositories and alternative journals and workshops offer routes for sharing negative results — which could help to solve the reproducibility crisis and give machine learning a boost [...]

One factor that is leading some researchers to revisit the problem is the growing use of predictive modelling using machine-learning tools in many fields. These tools are trained on large data sets that are often derived from published work, and scientists have found that the absence of negative data in the literature is hampering the process. Without a concerted effort to publish more negative results that artificial intelligence (AI) can be trained on, the promise of the technology could be stifled [...]"