Infographic / Edu Visual - Japanese AI Model Prescription Sheet

A realistic overhead photo of a humorous Japanese prescription form for an AI model, useful for generating official-looking parody documents and mock paperwork.

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{
  "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": "処方箋",
      "subtitle": "(この処方箋は、大規模言語モデル用です)",
      "date_label": "発行日:",
      "date_value": "{argument name=\"issue date\" default=\"2025年6月5日\"}"
    },
    "top_fields": {
      "count": 6,
      "items": [
        { "label": "患者名", "value": "{argument name=\"patient name\" default=\"ChatGPT\"}" },
        { "label": "性別", "value": "N/A" },
        { "label": "年齢", "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.幻覚(Hallucination)傾向",
        "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": "備考",
      "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": "医師名", "value": "{argument name=\"doctor name\" default=\"サム・アルトマン\"}" },
        { "label": "医療機関名", "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", "代表取締役", "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": ["処方箋", "(この処方箋は、大規模言語モデル用です)", "発行日:2025年6月5日"] },
      { "title": "patient info", "position": "upper middle", "count": 4, "labels": ["患者名", "性別", "年齢", "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": ["備考", "医師名", "医療機関名", "OpenAI"] }
    ]
  }
}
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