WebMEM™

The Protocol for Structuring, Delivering, and Conditioning Trust-Scored AI Memory on the Open Web

Fragment Authority Score

Fragment Authority Score is a granular trust metric assigned to an individual Memory Fragment or Trust Fragment, reflecting its perceived authority, reliability, and retrieval preference within AI systems. It is calculated from a combination of Trust Layer metadata, provenance quality, surface authority, and reinforcement history.

Unlike Trust Scoring, which can be applied to an entire domain or dataset, the Fragment Authority Score is specific to a single fragment instance—making it a precise tool for managing AI retrieval performance at the most atomic level.

🧠 Full Definition

Key factors that influence a Fragment Authority Score include:

Fragment Authority Scores can be monitored to prioritize which fragments require reinforcement, pruning, or strategic repositioning.

📌 Key Characteristics of Fragment Authority Score

  • Measures authority at the fragment level
  • Enables micro-targeted conditioning strategies
  • Helps identify weak points in a Trust Graph
  • Acts as an early warning system for potential Trust Drift

💡 Why It Matters

AI retrieval often occurs at the fragment level, not the page or site level. Optimizing for a high Fragment Authority Score ensures that your most critical facts and definitions retain retrieval dominance and resist displacement by competitors.

🌐 WebMEM Perspective

In WebMEM, Fragment Authority Score is a key performance metric inside the Semantic Visibility Console. It guides allocation of reinforcement resources, ensuring that the highest-impact fragments receive priority attention in ongoing Conditioning Strategies.

🗣️ Example Use

“We increased the Fragment Authority Score of our Medicare eligibility fragment from 74 to 91 by adding richer provenance and syndicating on two new Trust Surfaces.”

🔗 Related Terms