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入力 A は有名な料理（写真または料理名）です。料理の完全な材料の内訳、主要な風味化合物、化学的相互作用、および材料がなぜうまく組み合わされるのかという科学的根拠を分析します。
オプションの入力 B はスタイル参照（実験器具 / テック製品パッケージ）です。指定がない場合は、科学的な周期表と Apple 製品のデザイン美学を組み合わせたものを選びます。
目標：周期表構造のグリッド形式のディスプレイ ボード（20 インチ x 16 インチ）で、各材料が料理情報と科学情報の両方でラベル付けされた独自の区画に配置され、風味プロファイルによって色分けされています。
ルール：
ヘアライン加工されたアルミニウム、白色アクリル、またはつや消しガラスの裏板
周期表グリッド レイアウトに 20～30 個の小さな透明な区画
各区画には以下が含まれます：材料の標本、一般名、学名、主要な風味分子
色分けされた境界線：うま味（赤）、甘味（ピンク）、酸味（黄）、苦味（緑）、脂肪（オレンジ）、芳香（紫）
中央の「凡例」セクション：特徴的な化合物の 3D 分子構造図
下隅：ガラスの下に古びた羊皮紙またはパーチメントに書かれた実際のレシピ
アニメーション化された 3D 分子モデルを表示するための AR マーカー
クリーンなサンセリフ書体（Helvetica や Futura など）
余白をたっぷり取ったミニマルなデザイン
比率/重要度を示す各材料の原子スタイルの「数字」を含める
出力：純粋な白い背景に柔らかな影を付けた、4:5 のクリーンな製品写真スタイルの画像 1 枚
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インフォグラフィック / 教育ビジュアル - 食品分析周期表ディスプレイボード
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料理（写真または名前）を科学的な周期表スタイルのディスプレイボードに変えるように設計された複雑な指示プロンプト。出力は、うま味、甘味、酸味、苦味、脂質、芳香といった風味プロファイルごとに色分けされた完全な食材の内訳を示す 20 インチ x 16 インチのグリッドで、3D 分子図や AR マーカーを含む、科学的な周期表と Apple 製品のデザイン美学を融合させたスタイルで表示されます。
A complex instructional prompt designed to generate a visual representation of a dish's flavor profile in the style of a scientific periodic table. It requires analyzing a dish's ingredients and flavor compounds, then rendering a detailed display board with color-coded compartments, molecular structures, and a handwritten recipe, combining chemistry aesthetics with product design.
A complex, multi-step instruction prompt designed to visualize a food item (defaulting to pineapple pizza) as a 'Molecular Gastronomy' acrylic display box set against a void black background. It requires breaking the food down into 'Periodic Table' style ingredients and includes a miniature scientist figure for scale, emphasizing a Dark Mode aesthetic and macro photography.
A complex, structured prompt for generating a 'Culinary Science' diorama photograph, specifically illustrating the chemistry of a food item like chocolate or caramel. The scene features an L-shaped display box, a periodic table background with samples in Petri dishes, a 1:12 scale scientist figure, and massive 3D extruded letters made of the food itself, rendered in a 'Wes Anderson' symmetry.
A complex instructional prompt designed to generate a visual representation of a dish's flavor profile in the style of a scientific periodic table. It requires analyzing a dish's ingredients and flavor compounds, then rendering a detailed display board with color-coded compartments, molecular structures, and a handwritten recipe, combining chemistry aesthetics with product design.
A complex, logic-based prompt designed to create a macro diorama showing the historical trade journey of a specific ingredient. The prompt requires the AI to analyze the ingredient's Golden Age of trade, select period-accurate containers, maps, transport vehicles (like a steam train or camel), and dress figurines in period attire, culminating in a preserved specimen of the ingredient at the center.
A creative prompt for generating an epic 3D scene where a massive broadsheet newspaper is mid-unfold, and its headlines physically erupt into miniature dioramas of the events they describe. It specifies that column text rises as city blocks and the ink smell is almost visible, aiming for an 8K photorealistic result.
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Data collected and processed: IP addresses, Device identifiers, Probabilistic identifiers, Browsing and interaction data, Non-precise location data, Users’ profiles, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Probabilistic identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Probabilistic identifiers, Browsing and interaction data, Non-precise location data
Data collected and processed: IP addresses, Device characteristics, Probabilistic identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Authentication-derived identifiers, Browsing and interaction data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Authentication-derived identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, User-provided data, Non-precise location data, Precise location data
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Authentication-derived identifiers, Browsing and interaction data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, Users’ profiles, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, User-provided data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, Users’ profiles, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device characteristics, Device identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
Data collected and processed: IP addresses, Device identifiers, Probabilistic identifiers, Browsing and interaction data, Non-precise location data, Privacy choices
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