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输入 A 是一个著名菜肴（照片或菜肴名称）。分析该菜肴的完整食材分解、主要风味化合物、化学相互作用以及食材协同作用的科学依据。
可选输入 B 是一个风格参考（实验室设备 / 科技产品包装）。如果缺失，则选择科学元素周期表与 Apple 产品设计美学相结合的风格。
目标：制作一个网格状展示板（20 英寸 x 16 英寸），采用元素周期表结构，每个食材都有独立的隔间，标明烹饪和科学信息，并按风味特征进行颜色编码。
规则：
拉丝铝、白色亚克力或磨砂玻璃背板
20-30 个小型透明隔间，呈元素周期表网格布局
每个隔间包含：食材样本、俗名、学名、主要风味分子
颜色编码边框：鲜味（红色）、甜味（粉色）、酸味（黄色）、苦味（绿色）、脂肪（橙色）、芳香（紫色）
中央“图例”部分：招牌化合物的 3D 分子结构图
左下角：玻璃下方的陈旧羊皮纸或牛皮纸上手写食谱
用于扫描以查看动画 3D 分子模型的 AR 标记
简洁的无衬线字体（如 Helvetica 或 Futura）
极简设计，留有充足的留白
为每个食材包含原子风格的“数字”，显示比例/重要性
输出：一张图片，采用 4:5 的纯净产品摄影风格，在纯白色背景上带有柔和的阴影
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信息图 / 教育视觉图 - 食品分析元素周期表展示板
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一个复杂的指令提示，旨在将一道菜肴（通过照片或名称）转化为科学的、元素周期表风格的展示板。输出是一个 20x16 英寸的网格，显示完整的食材分解，按风味特征（鲜味、甜味、酸味、苦味、脂肪、芳香）进行颜色编码，并采用科学元素周期表与 Apple 产品设计美学相结合的风格，包括 3D 分子图和 AR 标记。
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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