The provided JSON configuration outlines a detailed prompt for generating a comprehensive entry for a flavor and fragrance material, specifically Citric Acid (CAS: 77-92-9), for FlavScents.com. The prompt is designed to guide a technical research assistant in creating an expert-level document that includes various sections such as Identity & Chemical Information, Sensory Profile, Natural Occurrence & Formation, Use in Flavors, Use in Fragrances, Regulatory Status, Toxicology, Safety & Exposure Considerations, Practical Insights for Formulators, and Confidence & Data Quality Notes. Each section requires specific information and citation hooks to ensure the entry is well-researched and authoritative.
The prompt emphasizes the importance of clarity, accuracy, and relevance to formulation, with a focus on exposure-based safety context. It also enforces a depth requirement, specifying target word counts for each section and the overall entry, depending on whether the material is a single compound or a complex natural material. The prompt includes a QA Check section to ensure all required elements are present and correctly formatted.
The configuration also specifies model defaults, such as using the GPT-4.1 model with a low temperature setting for precision and a maximum token limit to control the length of the output. The rendering settings indicate that the output should be in markdown format with numbered headings.
Overall, this prompt is a comprehensive guide for generating a detailed and technically accurate entry for Citric Acid, ensuring that all relevant aspects are covered and supported by authoritative sources.
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 2026-02-13 08:59:40 GMT (p2)