Resonance Metrics

Affinity Scoring for FCS 4.0

Principle

Sponsors selected by semantic affinity, not behavioral tracking or click-through rates.

ResonanceScore Formula

ResonanceScore(query, sponsor) =
  wave_interference(query, sponsor) × trust_coefficient × user_preferences

Where:

wave_interference = |ψ_query · ψ_sponsor|
  // Dot product of wave functions
  // ψ_query = semantic embedding as wave
  // ψ_sponsor = sponsor content as wave
  // Result: constructive interference = high affinity

trust_coefficient = CALT_verified ? 1.0 : 0.5
  // Verified sponsors weighted higher

user_preferences = explicit_settings[category]
  // User-declared preferences (no tracking)
  // Default: 1.0 (neutral)

Metrics NOT Used

• ❌ Click-through rate (CTR)
• ❌ Conversion rate
• ❌ User behavior history
• ❌ Demographic targeting
• ❌ Surveillance data

Metrics Used

• ✅ Semantic affinity (wave interference)
• ✅ Trust lineage (CALT verification)
• ✅ User-declared preferences
• ✅ Content quality signals

API

POST /beacons/score
Content-Type: application/json

{
  "query": "best cloud database for ML workloads",
  "sponsors": [
    {"domain": "aws.amazon.com", "content": "..."},
    {"domain": "cloud.google.com", "content": "..."}
  ]
}

Response:
{
  "scores": [
    {
      "domain": "aws.amazon.com",
      "resonance_score": 0.89,
      "components": {
        "wave_interference": 0.92,
        "trust_coefficient": 1.0,
        "user_preferences": 0.97
      }
    },
    {
      "domain": "cloud.google.com",
      "resonance_score": 0.85,
      "components": {
        "wave_interference": 0.88,
        "trust_coefficient": 1.0,
        "user_preferences": 0.97
      }
    }
  ],
  "selected": "aws.amazon.com",
  "method": "highest_resonance"
}

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