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  "bibtex": "https://research.draconitic.com/paper/eazs4we3fcp7q.bib",
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  "doi": "10.1175/aies-d-25-0090.1",
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  "language": "en",
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  "licence_label": "Licence not stated",
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  "pdf_url": "https://arxiv.org/pdf/2509.17601",
  "pmcid": null,
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  "published": "2026-07-01",
  "publisher": "American Meteorological Society",
  "ris": "https://research.draconitic.com/paper/eazs4we3fcp7q.ris",
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      "origin": "openalex:1902|Meteorological Phenomena and Simulations",
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  "title": "FastNet: Improving the Physical Consistency of Machine Learning Weather Prediction Models through Loss Function Design",
  "title_text": "FastNet: Improving the Physical Consistency of Machine Learning Weather Prediction Models through Loss Function Design",
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  "updated_at": "2026-11-08T13:20:53Z",
  "url": "https://research.draconitic.com/paper/eazs4we3fcp7q",
  "venue": "Artificial Intelligence for the Earth Systems",
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