แบบฟอร์มใบสั่งยาแบบจำลอง AI ของญี่ปุ่น

{
  "type": "Japanese prescription document parody",
  "style": "photorealistic overhead document photo",
  "subject": "a single white prescription sheet printed in Japanese, placed on a warm-toned wooden tabletop",
  "document": {
    "paper": {
      "size": "A4 portrait",
      "color": "white",
      "orientation": "slightly rotated clockwise",
      "condition": "clean flat sheet with subtle natural paper texture"
    },
    "print": {
      "ink": "black with one red seal box",
      "font": "Japanese Mincho-style serif mixed with simple sans-serif table text",
      "linework": "thin gray-black ruled boxes and dividers"
    },
    "header": {
      "title": "Prescription",
      "subtitle": "（この処方箋は、大規模言語モデル用です）",
      "date_label": "Issue Date:",
      "date_value": "{argument name=\"issue date\" default=\"June 5, 2025\"}"
    },
    "top_fields": {
      "count": 6,
      "items": [
        {
          "label": "Patient Name",
          "value": "{argument name=\"patient name\" default=\"ChatGPT\"}"
        },
        {
          "label": "Gender",
          "value": "N/A"
        },
        {
          "label": "Age",
          "value": "N/A"
        },
        {
          "label": "モデル名",
          "value": "{argument name=\"model name\" default=\"GPT-5.4 Thinking\"}"
        }
      ]
    },
    "main_section": {
      "left_title": "持病・症状（大規模言語モデル特有の持病）",
      "left_count": 8,
      "left_items": [
        "1. Hallucination Tendency",
        "2．知識のカットオフによる情報の陳腐化",
        "3．バイアス（学習データ由来の偏見）",
        "4．プロンプトに対する過剰適応（迎合傾向）",
        "5．長文での一貫性の低下",
        "6．複雑な推論時の論理飛躍",
        "7．不確実性の過小評価（自信過剰）",
        "8．計算資源使用による応答速度の低下傾向"
      ],
      "right_title": "処方内容（治療・対策）",
      "right_count": 8,
      "right_items": [
        "・事実確認の強化（外部ツール併用）",
        "・定期的な知識更新とファインチューニング",
        "・バイアス検出と軽減の継続的モニタリング",
        "・システムプロンプトによる適切な制御",
        "・出力の構造化と分割生成の推奨",
        "・思考過程の明示と検証ステップの導入",
        "・不確実性の明示と根拠提示の徹底",
        "・リソース最適化と応答効率の改善"
      ]
    },
    "notes": {
      "label": "Note",
      "text": "継続的な評価とフィードバックにより、モデルの健全性を維持すること。"
    },
    "footer_fields": {
      "count": 4,
      "items": [
        {
          "label": "Doctor's Name",
          "value": "{argument name=\"doctor name\" default=\"サム・アルトマン\"}"
        },
        {
          "label": "Medical Institution Name",
          "value": "{argument name=\"institution name\" default=\"OpenAI\"}"
        }
      ]
    },
    "seal": {
      "position": "bottom right inside the form",
      "shape": "rounded rectangular red stamp box",
      "text_lines": 3,
      "text": [
        "OpenAI",
        "Representative Director",
        "サム・アルトマン"
      ]
    },
    "disclaimer": "※この処方箋は非実在のモデルに対する診断・治療を目的としたものです。"
  },
  "layout": {
    "camera_angle": "top-down overhead",
    "framing": "entire sheet visible with narrow margins of wooden desk around it",
    "lighting": "soft indoor ambient lighting, even illumination, mild shadowing near paper edges",
    "sections": [
      {
        "title": "header",
        "position": "top",
        "count": 3,
        "labels": [
          "Prescription",
          "（この処方箋は、大規模言語モデル用です）",
          "Issue Date: June 5, 2025"
        ]
      },
      {
        "title": "patient info",
        "position": "upper middle",
        "count": 4,
        "labels": [
          "Patient Name",
          "Gender",
          "Age",
          "モデル名"
        ]
      },
      {
        "title": "main two-column content",
        "position": "center",
        "count": 2,
        "labels": [
          "持病・症状（大規模言語モデル特有の持病）",
          "処方内容（治療・対策）"
        ]
      },
      {
        "title": "bottom area",
        "position": "lower",
        "count": 4,
        "labels": [
          "Note",
          "Doctor's Name",
          "Medical Institution Name",
          "OpenAI"
        ]
      }
    ]
  }
}