The authors propose changing the default threshold for statistical significance from 0.05 to 0.005 for claims of new discoveries. They argue that the current threshold, associated with a P-value of 0.05, results in a high rate of false positives, even in the absence of other experimental, procedural, and reporting issues. The proposed change would improve the reproducibility of scientific research by reducing the false positive rate. The authors provide a detailed explanation of the relationship between P-values and Bayes factors, showing that a P-value of 0.005 corresponds to substantial to strong evidence in favor of the alternative hypothesis. They also address potential objections, such as the increased false negative rate and the need for alternative statistical methods, emphasizing that the change is a complementary step to other reforms. The authors conclude that the change is actionable and will immediately improve reproducibility in many fields.The authors propose changing the default threshold for statistical significance from 0.05 to 0.005 for claims of new discoveries. They argue that the current threshold, associated with a P-value of 0.05, results in a high rate of false positives, even in the absence of other experimental, procedural, and reporting issues. The proposed change would improve the reproducibility of scientific research by reducing the false positive rate. The authors provide a detailed explanation of the relationship between P-values and Bayes factors, showing that a P-value of 0.005 corresponds to substantial to strong evidence in favor of the alternative hypothesis. They also address potential objections, such as the increased false negative rate and the need for alternative statistical methods, emphasizing that the change is a complementary step to other reforms. The authors conclude that the change is actionable and will immediately improve reproducibility in many fields.