MMLU-Redux

As a competition benchmark, MMLU-Redux is a corrected slice of MMLU: it inherits MMLU's contamination and frontier convergence, so it does not differentiate top models — saturated by CLAUDE.md's definition (usefulness as a model-differentiating eval). Its ENDURING value is different and non-competitive: it remains an actively-used forensic reference and audit methodology for measuring label noise. Status here reflects the eval role; the still-active reference role is documented in prose. saturated_date is set to its launch — it described an already-saturated parent from birth.