Understanding Your Personalized Rankings
How we combine multiple data sources to provide accurate effectiveness predictions
Our Predictive Ranking System
We use a sophisticated weighted algorithm that combines three key data sources, prioritizing information based on its predictive power for your specific needs.
Each prediction is calculated using a weighted combination of three data sources. You can adjust the weights below to see how it affects the ranking:
Digital Twin Analysis
Using advanced machine learning to analyze thousands of similar user experiences
Our digital twin technology creates a virtual representation of your unique characteristics and preferences by analyzing data from users with similar:
- Physical characteristics (age, weight, metabolism)
- Medical conditions and symptoms
- Previous cannabis experiences
- Treatment goals and preferences
Individual Rankings from Digital Twin:
Your Personal Sessions
Direct feedback from your experiences with similar products
We analyze your previous sessions with similar products, considering factors such as:
- Products with similar terpene profiles
- Your response to specific cannabinoid ratios
- Time of day and dosage patterns
- Reported effectiveness for specific symptoms
Rankings Based on Your Sessions:
Scientific Literature
Peer-reviewed research on cannabinoids and terpenes
Our analysis incorporates findings from peer-reviewed studies on:
- Specific cannabinoid effects on various conditions
- Terpene synergies and therapeutic properties
- Clinical trials and systematic reviews
- Population-level effectiveness studies
Rankings Based on Literature:
Relevant Scientific Literature
Key research papers supporting our analysis