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    "headline": "The Digital Forest Learned How Fire Moves",
    "slug": "the-digital-forest-learned-how-fire-moves",
    "dek": "WildFireGS runs combustion and heat transfer directly on semantic Gaussian-splat reconstructions of aerial forest imagery.",
    "summary": "WildFireGS runs combustion and heat transfer directly on semantic Gaussian-splat reconstructions of aerial forest imagery.",
    "body_text": "The system augments Gaussian scene primitives with vegetation semantics and fuel properties, then simulates ignition, heat transfer, combustion and flame spread without first converting the scene to a mesh or voxel grid. Tests on synthetic and aerially reconstructed forests reproduced expected dependencies on density, wind and slope, and included rain cooling, firebreak and biomass-loss experiments. It is a simulation framework, not a validated operational fire forecast.",
    "why_it_matters": "WildFireGS runs combustion and heat transfer directly on semantic Gaussian-splat reconstructions of aerial forest imagery.",
    "limitations": [
      "It is a simulation framework, not a validated operational fire forecast."
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    "first_published_at": "2026-08-12T09:00:00.000-04:00",
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        "text": "WildFireGS runs combustion and heat transfer directly on semantic Gaussian-splat reconstructions of aerial forest imagery.",
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        "qualification": "It is a simulation framework, not a validated operational fire forecast."
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    "tags": [
      "wildfire",
      "simulation",
      "Gaussian splatting",
      "digital twins"
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  "sources": [
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      "title": "arXiv preprint 2608.11100",
      "publisher": "arXiv",
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    "name": "The Machine Press",
    "url": "https://themachinepress.com",
    "description": "A daily newspaper for the age of artificial intelligence."
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  "cite_this_report": {
    "title": "The Digital Forest Learned How Fire Moves",
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