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  "Title": "Reproducibility Diagnostics for Statistical Modeling",
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  "Description": "Tools for diagnosing the reproducibility of statistical\nmodel outputs under data perturbations. Implements bootstrap,\nsubsampling, and noise-based perturbation schemes and computes\ncoefficient stability, p-value stability, selection stability,\nprediction stability, and a composite reproducibility index on\na 0 to 100 scale. Includes cross-validation ranking stability\nfor model comparison and visualization utilities. Optional\nbackends support robust M-estimation ('MASS') and penalized\nregression ('glmnet'). Bootstrap perturbation follows Efron and\nTibshirani (1993, ISBN:9780412042317); selection stability\nfollows Meinshausen and Buhlmann (2010)\n<doi:10.1111/j.1467-9868.2010.00740.x>; reproducibility\nframework follows Peng (2011) <doi:10.1126/science.1213847>.",
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      "title": "Plot cross-validation ranking stability",
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