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Multi-source AI news clustered, deduplicated, and scored 0–100 across authority, cluster strength, headline signal, and time decay.

  1. Why n=50,000 lied to me: the statistical trap behind a false sector advantage

    An analysis of LLM outputs revealed a statistical trap where a large sample size masked underlying data issues. Initially, 50,000 responses suggested fintech led in spontaneous mentions by AI, but a closer look showed this was due to a single dominant brand, Nubank. The author identified two key errors: treating repeated prompts as independent observations and a flawed leave-one-out validation method that failed to account for the influence of anchor entities. AI

    IMPACT Highlights critical flaws in interpreting LLM-generated data, urging caution in drawing conclusions from large sample sizes without accounting for prompt correlation and entity influence.