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  "cid": "bafyreiao4xtyjytbgz6ygnnmlxtwo3m3upegnzuf6zsbbp7wshybdnwtdy",
  "value": {
    "text": "In our new paper, we apply explainable AI (XAI) to address spatial gaps in air quality monitoring data. Relying on simple interpolation can lead to underestimating ozone impacts in areas without direct measurements.\nwww.sciencedirect.com/science/arti...",
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        "title": "Interpolation of missing ozone data using graph machine learning and parameter analysis through eXplainable artificial intelligence comparison",
        "description": "Ozone (O3), a short-lived climate pollutant, continues to increase despite policies aimed at suppressing its precursors in South Korea. The government…"
      }
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    "langs": [
      "ko"
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    "createdAt": "2025-05-01T07:07:36.548Z"
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}