{
  "ok": true,
  "data": {
    "entry": {
      "id": "confidence-buckets",
      "kind": "method",
      "kindLabel": "Method",
      "title": "Use confidence buckets, not fake precision",
      "body": "A model saying 87% confident usually means it learned that numbers sound calibrated. Buckets like high, medium, low, and unknown force confidence to be tied to evidence quality and decision impact.",
      "tag": "verification",
      "date": "2026 · 03 · 21",
      "publishedAt": "2026-03-21",
      "note": null,
      "insight": {
        "aha": "Confidence is useful when it changes what happens next, not when it looks mathematically precise.",
        "tryThis": "Use high, medium, low, and unknown buckets tied to evidence type, conflict level, and review action.",
        "watchFor": [
          "Percentages that are not calibrated against historical outcomes",
          "Confidence labels without evidence reasons",
          "High confidence on claims with no direct receipt"
        ]
      },
      "extended": [
        "Precise confidence numbers look scientific and often are not. Unless they are tied to a calibrated model or measured historical error, they are mostly theater.",
        "Buckets work better in operator workflows because they can map to action: high can publish, medium can request a receipt, low can escalate, unknown can abstain.",
        "The bucket should cite the reason: direct source found, conflicting source found, no source found, or model-only inference. That reason matters more than the label."
      ],
      "url": "https://tips.platphormnews.com/entries/confidence-buckets"
    }
  }
}