Independent Retrieval Authority Validation (IRAV v1.0)
Executive Abstract: The Independent Retrieval Authority Validation (IRAV) protocol establishes a forensic standard for auditing "Answer Engine" visibility. Unlike traditional SEO, which optimizes for list-based retrieval (Search Engine A), IRAV measures the probability of Single Entity Selection (LLM Retrieval B).
By quantifying "Hallucination Drift" and "Ground Truth Anchoring" against the bound interval of the 35/25/40 framework, IRAV provides a deterministic score for Brand Authority in non-deterministic AI systems.
Mathematical Foundation
The 35/25/40 Significance Distribution
The nDCG (Normalized Discounted Cumulative Gain) for Generative Optimization is calculated across three bounded integrity intervals:
Entity Salience
Dominance in Knowledge Graph structure (Wikidata/Google KG).
Citation Freshness
Velocity of high-authority mentions in the trailing 90-day window.
Brand Weights
Latent co-occurrence vectors in the model's training data.
DCG_p = Σ (i=1 to p) [rel_i / log₂(i+1)] where rel_i ∈ {0,1}
Evidence: Search vs. Retrieval
| Metric | Search Engine A (Traditional) | LLM Retrieval B (Generative) |
|---|---|---|
| Success Metric | Click-Through Rate (CTR) | Direct Selection Rate (DSR) |
| Output Format | 10 Blue Links | Synthesized Answer |
| User Intent | Exploration / Research | Verification / Action |
| Authority Source | Backlink Volume | Entity Integrity (IRAV) |
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