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The article outlines six indicators that suggest an experiment should be repeated, such as solid impact results, almost significant p-values, and cases where initial results seem "too good to be true." It emphasizes the importance of revisiting past experiments for better insights and improving statistical power.
The content appears to be corrupted or improperly formatted, making it impossible to extract coherent information regarding building scaled experimentation. As a result, no meaningful summary can be provided.