Explanatory Filter

The Explanatory Filter is a method for distinguishing meaningful patterns from random noise. It works by first filtering out noise to see if a pattern remains; if a pattern survives this step, it's likely meaningful. Then, it assesses whether the pattern is simple enough to be trustworthy—favoring explanations that are concise and elegant. If it clears both tests, the pattern is considered a valid explanation. Essentially, it's a systematic way to separate true insights from false clues by checking for noise, simplicity, and consistency.