Optimal Multiple Hypothesis Testing Corrections // Implements the optimal multiple hypothesis testing correction from Viviano, Wuthrich, and Niehaus (2026) doi:10.48550/arXiv.2104.13367. Derives the optimal per-test significance level from the economic incentives of research production, providing a correction that lies between Bonferroni (too conservative) and unadjusted (too permissive). Supports two cost models: a Linear one calibrated to United States Food and Drug Administration (FDA) clinical-trial costs, and a Cobb-Douglas one calibrated to Abdul Latif Jameel Poverty Action Lab (J-PAL) project costs. Reports optimal, Bonferroni, Holm, Benjamini-Hochberg (BH), and unadjusted results side by side.