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Using GPT-5.6 Sol Pro, Edgar Dobriban disproved a long-standing conjecture that the Benjamini-Hochberg procedure controls the false discovery rate for correlated two-sided Gaussian tests, showing it fails at a small but real level. The result is conceptual with limited practical impact but resolves a central question in statistics.
SafeImpute proposes a reliable imputation framework for irregular clinical data using graph neural networks and conformal selection to control the false discovery rate of clinically unacceptable errors.