{
  "$type": "site.standard.document",
  "description": "A trained machine learning model identifies that a real-world apparatus has a failed component, which trained machine learning model has been trained with a training corpus that includes content generated by synthesizing a plurality of synthesized operating examples for a given apparatus, wherein…",
  "path": "/patents/1381077",
  "publishedAt": "2026-04-16T00:00:00.000Z",
  "site": "at://did:plc:oql6ds5vnff4ugar6rruliwd/site.standard.publication/3mn3ohu7oxx5w",
  "tags": [
    "G06N20/00",
    "General Electric Company"
  ],
  "textContent": "A trained machine learning model identifies that a real-world apparatus has a failed component, which trained machine learning model has been trained with a training corpus that includes content generated by synthesizing a plurality of synthesized operating examples for a given apparatus, wherein at least some of the plurality of synthesized operating examples are generated via a simulation modeling environment that receives as input characterizing information that corresponds to any of a variety of failure states for a component of the given apparatus.",
  "title": "Method and Apparatus for Training and Employing a Machine Learning Model to Identify Failed Components"
}