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    "story_id": "mp-2026-09-02-010",
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    "headline": "The Lane Change Appeared Before the Line Was Crossed",
    "slug": "the-lane-change-appeared-before-the-line-was-crossed",
    "dek": "DNC-IMM uses surrounding gaps and relative velocities to calibrate an interpretable intention model.",
    "summary": "DNC-IMM uses surrounding gaps and relative velocities to calibrate an interpretable intention model.",
    "body_text": "A neural network adjusts both the transition matrix and measurement likelihoods of an interacting multiple-model estimator rather than replacing its probabilistic decision. On the highD dataset, the calibrated posterior recognized lane changes before crossing and was strongest at two- to three-second horizons. The evidence is retrospective dataset evaluation, not a road deployment claim.",
    "why_it_matters": "DNC-IMM uses surrounding gaps and relative velocities to calibrate an interpretable intention model.",
    "limitations": [
      "The evidence is retrospective dataset evaluation, not a road deployment claim."
    ],
    "importance": 7,
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    "first_published_at": "2026-09-02T09:00:00.000-04:00",
    "modified_at": "2026-09-02T09:00:00.000-04:00",
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        "qualification": "The evidence is retrospective dataset evaluation, not a road deployment claim."
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    "source_ids": [
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    "tags": [
      "autonomous driving",
      "lane change",
      "intention recognition"
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    "image_url": null,
    "corrections": []
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    {
      "source_id": "source-2026-09-02-010",
      "title": "arXiv preprint 2609.01120",
      "publisher": "arXiv",
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    "description": "A daily newspaper for the age of artificial intelligence."
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    "title": "The Lane Change Appeared Before the Line Was Crossed",
    "publisher": "The Machine Press",
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