The provided JSON configuration outlines a detailed prompt for generating a comprehensive entry on a specific flavor and fragrance material, "bean pyrazine (CAS: 25773-40-4)," for FlavScents.com. This prompt is designed for use with a language model to produce a technically accurate and insightful document tailored for professionals in the flavor and fragrance industry. Below is a breakdown of the key components and requirements of the prompt:
Key Components:
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Material Information: The prompt specifies that the material in question is "bean pyrazine," a single chemical compound with a given CAS number.
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Target Audience: The entry is intended for experienced professionals such as flavor chemists, perfumers, product developers, toxicologists, and regulatory specialists.
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Source Priority: The prompt emphasizes the use of authoritative sources, prioritizing internal references from FlavScents and external sources like FEMA, EFSA, IFRA, PubChem, Codex, JECFA, and peer-reviewed literature.
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Material Type Handling: Instructions are provided for handling single compounds versus complex natural materials, with specific guidelines on how to describe each type.
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Depth Requirement: The prompt enforces a depth requirement, specifying target word counts for each section and the overall entry, ensuring comprehensive coverage of the topic.
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Output Format: The entry must follow a structured format with numbered headings and include a "Citation hooks:" line under each section to indicate relevant sources.
Sections to Include:
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Identity & Chemical Information: Details about the compound's common names, IUPAC name, CAS number, molecular formula, and functional groups.
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Sensory Profile: Description of the material's odor and flavor characteristics, including thresholds and typical sensory roles.
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Natural Occurrence & Formation: Information on natural sources and formation pathways, relevant to "natural flavor" or "natural fragrance" designations.
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Use in Flavors: Discussion of flavor categories, applications, functional roles, typical use levels, and stability considerations.
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Use in Fragrances: Description of fragrance families, functional roles, concentration ranges, and volatility.
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Regulatory Status (Regional Overview): Summary of regulatory treatment across different regions, including the US, EU, UK, Asia, and Latin America.
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Toxicology, Safety & Exposure Considerations: Safety discussion covering oral, dermal, and inhalation exposure routes.
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Practical Insights for Formulators: Expert insights on the material's value, synergies, pitfalls, and usage trends.
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Confidence & Data Quality Notes: Summary of data quality, industry practices, and known gaps.
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QA Check: A checklist to ensure all sections are present and requirements are met.
Style & Constraints:
- The entry should be written for experienced professionals, avoiding marketing language and focusing on interpretive insights.
- The prompt includes a quality assurance section to ensure compliance with all requirements before finalizing the entry.
This structured approach ensures that the generated entry is comprehensive, technically accurate, and valuable for professionals in the flavor and fragrance industry.
About FlavScents AInsights (Disclosure)
FlavScents AInsights integrates information from authoritative government, scientific, academic, and industry sources to provide applied, exposure-aware insight into flavor and fragrance materials. Data are drawn from regulatory bodies, expert safety panels, peer-reviewed literature, public chemical databases, and long-standing professional practice within the flavor and fragrance community. Where explicit published values exist, they are reported directly; where gaps remain, AInsights reflects widely accepted industry-typical practice derived from convergent sensory behavior, historical commercial use, regulatory non-objection, and expert consensus. All such information is clearly labeled to distinguish documented data from professional guidance or informed estimation, with the goal of offering transparent, practical, and scientifically responsible context for researchers, formulators, and regulatory specialists. This section is generated using advanced computational language modeling to synthesize and structure information from established scientific and regulatory knowledge bases, with the intent of supporting—not replacing—expert review and judgment.
Generated 2026-01-16 19:30:59 GMT (p2)