We need something akin to the international geophysical year, but for data integrity. Make it an interdisciplinary priority to clean house and root out papers that are hanging by a thread of included / excluded outliers, biased samples, and outright fraud. It would be humbling, but we'd be in much better shape afterwards.
We need something akin to the international geophysical year, but for data integrity. Make it an interdisciplinary priority to clean house and root out papers that are hanging by a thread of included / excluded outliers, biased samples, and outright fraud. It would be humbling, but we'd be in much better shape afterwards.
My read is that the model had too much variance; more regularization was needed.