{
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  "_kind": "Workflow",
  "_file": "workflows/workflows/workflows-data-science-deep.yaml",
  "_cluster": "workflows",
  "attributes": {
    "displayName": "Model Explainability Review",
    "workflowKind": "governance",
    "triggerType": "event-driven",
    "typicalCadence": "per-model",
    "complexity": "single-team",
    "description": "Reviews the interpretability and explainability posture of ML models before\ndeployment — generating SHAP/LIME feature importance explanations,\nvalidating that global and local explanations are consistent, verifying\nexplanation latency meets serving SLAs, documenting known blind spots and\nout-of-distribution behavior, and ensuring explanations are surfaced\nappropriately in end-user interfaces. Excludes model training and fairness\nauditing.\n"
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      "attributes": {}
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      "attributes": {}
    }
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  "incomingEdges": []
}