{
  "id": "scope-boundary:mle-bench.scope",
  "_kind": "ScopeBoundary",
  "_file": "sourceref-scope/scope-boundaries/mle-bench.yaml",
  "_cluster": "sourceref-scope",
  "attributes": {
    "subjectId": "benchmark:mle-bench",
    "inScope": "End-to-end machine-learning engineering tasks drawn from 75 Kaggle\ncompetitions — agents must produce a submission CSV scored against\nheld-out leaderboards. Tasks use Python, common ML libraries\n(PyTorch, scikit-learn, pandas), and run inside a Docker sandbox.\n",
    "outOfScope": "Pure code-generation tasks (use HumanEval/SWE-bench), data-engineering\n(ETL) tasks without an ML objective, foundation-model pre-training,\ninteractive/UI-driven ML workflows, and tasks requiring proprietary\nGPU clusters beyond a single accelerator.\n",
    "outOfScopeReasonIds": [
      "out-of-scope-reason:future-phase",
      "out-of-scope-reason:implementation-detail"
    ]
  },
  "outgoingEdges": [
    {
      "from": "scope-boundary:mle-bench.scope",
      "to": "benchmark:mle-bench",
      "kind": "bounds_subject"
    }
  ],
  "incomingEdges": []
}