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    "story_id": "mp-2026-10-23-009",
    "source_story_id": "tmp-story-cost-aware-ticket-abstention",
    "edition_id": "mp-2026-10-23-morning-0105",
    "edition_url": "https://themachinepress.com/edition/2026-10-23",
    "position": 9,
    "story_type": "dispatch",
    "section": "business-enterprise",
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    "headline": "The Cheap Classifier Knows When to Hand Off",
    "slug": "the-cheap-classifier-knows-when-to-hand-off",
    "dek": "On one 47,837-ticket corpus, calibrated TF-IDF routing cut the illustrative test cost 38.1 percent and wrong routes from 15.3 to 3.5 percent.",
    "summary": "On one 47,837-ticket corpus, calibrated TF-IDF routing cut the illustrative test cost 38.1 percent and wrong routes from 15.3 to 3.5 percent.",
    "body_text": "Misrouting an IT ticket may cost more than asking a person to triage it. Under an illustrative cost model where a wrong route costs five times a human deferral, a calibrated TF-IDF logistic-regression system reduced test cost from 0.763 to 0.472 and cut wrong routes from 15.3 to 3.5 percent. The strongest prompted large-language-model configuration reached 0.477 accuracy on a 1,000-ticket subset, versus 0.879 for fine-tuned DistilBERT. Several prompted systems deferred everything at the break-even threshold. The study is a readiness framework for one dataset and cost model, not a universal verdict on language models or support operations.",
    "why_it_matters": "On one 47,837-ticket corpus, calibrated TF-IDF routing cut the illustrative test cost 38.1 percent and wrong routes from 15.3 to 3.5 percent.",
    "limitations": [
      "The study is a readiness framework for one dataset and cost model, not a universal verdict on language models or support operations."
    ],
    "importance": 8,
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    "first_published_at": "2026-10-23T09:00:00.000-04:00",
    "modified_at": "2026-10-23T09:00:00.000-04:00",
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        "text": "On one 47,837-ticket corpus, calibrated TF-IDF routing cut the illustrative test cost 38.1 percent and wrong routes from 15.3 to 3.5 percent.",
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    "source_ids": [
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    "tags": [
      "enterprise AI",
      "classification",
      "abstention"
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    "image_url": null,
    "corrections": []
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  "sources": [
    {
      "source_id": "source-2026-10-23-009",
      "title": "arXiv preprint 2610.31657, original v1",
      "publisher": "arXiv",
      "url": "https://arxiv.org/abs/2610.31657v1",
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      "source_type": "primary_research",
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      "published_at": "2026-10-22T13:58:52.000-04:00",
      "accessed_at": "2026-10-23T08:21:38.024-04:00",
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  "publisher": {
    "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 Cheap Classifier Knows When to Hand Off",
    "publisher": "The Machine Press",
    "published_at": "2026-10-23T09:00:00.000-04:00",
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