Core Vitality LabHow We Research Supplements
Our rigorous, AI-powered methodology ensures every supplement recommendation is backed by the highest quality scientific evidence available.
Our 5-Step Research Process
A systematic approach to evidence-based supplement research
Data Collection
Our AI continuously scans authoritative scientific databases and journals
AI Analysis
Advanced algorithms analyze study quality, methodology, and statistical significance
Evidence Synthesis
Multiple studies are synthesized to determine overall strength of evidence
Clinical Validation
Human clinical trials and real-world evidence are prioritized
Continuous Updates
Research database is updated daily with new scientific publications
Quality Assurance Standards
Rigorous criteria ensure only the highest quality research influences our recommendations
Study Design Quality
Only high-quality research designs are included in our analysis
- Randomized controlled trials
- Systematic reviews
- Meta-analyses
- Cohort studies
- Case-control studies
Sample Size Requirements
Studies must have adequate statistical power
- Minimum 20 participants per group
- Power analysis conducted
- Appropriate statistical tests
- Confidence intervals reported
- Effect size calculations
Publication Standards
Research must meet rigorous publication standards
- Peer-reviewed journals
- Indexed in major databases
- Conflict of interest disclosure
- Funding source transparency
- Research ethics compliance
Transparency & Accountability
Open Methodology
Complete transparency in our research process and decision-making criteria
Source Citations
Every recommendation includes full citations and links to original research
Bias Mitigation
Multiple safeguards against bias in research selection and interpretation
Independent Review
All recommendations undergo independent expert review before publication
Our AI Research Platform
Studies analyzed
Analysis accuracy
Monitoring active
Languages supported
Advanced AI Capabilities
Our proprietary AI system uses state-of-the-art natural language processing and machine learning to extract meaningful insights from complex scientific literature:
Natural Language Processing
- • Automated study abstract analysis
- • Key finding extraction
- • Methodology assessment
- • Statistical significance evaluation
Machine Learning Models
- • Study quality classification
- • Bias detection algorithms
- • Evidence strength scoring
- • Research trend analysis
Experience Evidence-Based Research
See how our rigorous methodology translates into trustworthy supplement recommendations that you can confidently rely on for your health journey.