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  "Description": "Performs exhaustive or groupwise (backward elimination)\nvariable selection for binary outcome prediction models using\ncross-validated Net Benefit as the optimization criterion. It\nsupports predictor costs, restricted cubic splines, interaction\nterms, permutation importance, and parallel computation. It\nincludes visualizations for model comparison and variable\nimportance. References include Vickers AJ & Elkin EB (2006)\n<doi:10.1177/0272989X06295361>, Van Calster B et al. (2018)\n<doi:10.1016/j.eururo.2018.08.038>, Vickers AJ et al. (2019)\n<doi:10.1186/s41512-019-0064-7>, and Baker SG et al. (2012)\n<doi:10.1515/1557-4679.1395>.",
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      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/lasaibarrenada/actions/runs/37920735701"
    }
  ]
}