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Measurement & Assessment Layer

Measurement & Assessment Layer

Provides frameworks and metrics for assessing representation quality, system performance, and economic outcomes.

3 primitives1 established2 emerging

Layer Principles

  • •Four-Layer Architecture: Framework for analysis
  • •Machine Readability Index: AI-readiness scoring
  • •Representation Efficiency: Cost reduction measurement
  • •Evidence Hierarchy: Measured > experimental > observational

Primitives in this Layer

Measurement & Assessment LayerFrameworkEstablished

Four-Layer Architecture

The Four-Layer Architecture is a framework for understanding AI-mediated markets as four interconnected layers.

1 source
Measurement & Assessment LayerMetricEmerging

Machine Readability Index (MRI)

MRI is a 0-100 score that measures how well an entity can be understood by AI systems.

1 source
Measurement & Assessment LayerMetricEmerging

Representation Efficiency Score (RES)

RES measures how efficiently an AI system can reason about an entity representation.

1 source

Related Layers

Representation Layer

Encodes market-relevant information in machine-readable form optimized for AI reasoning rather than human browsing.

Discovery & Reasoning Layer

Processes representations to reach decisions through AI-mediated reasoning, intent resolution, and selection.

Layer Architecture

The seven layers form an interconnected architecture. Primitives in this layer connect to Representation Layer and Discovery & Reasoning Layer.