AI & Multimodal Vision Disclaimer
Probabilistic Nature of AI Recognition
Unitrition employs computer vision and voice recognition models to accelerate meal logging. However, AI parsing is a PROBABILISTIC ESTIMATION. It is not a calibrated scale or a chemical lab sensor. You must always visually inspect detected ingredients and calibrate portions to match your actual meal plate.
1. Where AI is Used in Unitrition
Visual ingredient segmentation and volume-to-weight approximation from meal photos.
Natural language transcription mapped directly to USDA and Open Food Facts database items.
2. Inherent Limitations of Vision Models
Artificial intelligence models possess well-documented technical boundaries:
- Hidden Ingredients: AI cannot measure cooking oils, dissolved sugars, hidden marinades, or sodium levels invisible to the lens.
- Density vs Weight: Weight estimation from a 2D photograph is a volumetric approximation and may vary from true scale measurements.
- Allergens & Cross-Contamination: Never rely on AI vision to verify safety against life-threatening allergens (gluten, nuts, shellfish cross-contact).
3. User Responsibility & Calibration
The user retains sole responsibility for reviewing AI-suggested items before adding them to the Meal Builder plate or relying on totals for Bread Unit (ХЕ) calculations.
4. Research Methodology & Educational Content
Educational blog publications and nutritional guides on Unitrition are compiled utilizing advanced scientific literature synthesis models (such as Gemini Deep Research and structured Gemini Notebook analysis) reviewing peer-reviewed primary sources: PubMed, USDA FoodData Central, Open Food Facts, and published standards from international dietary associations (ADA, KDIGO, ESPEN).
In accordance with Article 50 of the European Union AI Act (Regulation 2024/1689) and FTC consumer transparency standards, we openly disclose that literature research synthesis utilizes algorithmic AI tools. All material is provided strictly for educational and dietary self-monitoring purposes and must be independently evaluated by the user and their healthcare professional.