# Machine Readability Index (MRI)

**Standardized Measure of Property Record AI Compatibility**

> **⚠️ Evidence Status:** Derived from measured data
>
> Findings are derived from measured primary datasets using documented scoring or validation methods.

---
**Publication Date**: 2026-01-01
**Authors**: HomeSelf Research
**Institution**: HomeSelf Research Initiative
**Category**: index
**Evidence Status**: derived — Derived from measured data
**Version**: 1.0
---

## Abstract

The Machine Readability Index (MRI) is a standardized 0-100 score measuring how effectively a property record enables AI-mediated understanding, comparison, and selection. The index evaluates completeness, Machine Readability, consistency, and verifiability of property data.

## Methodology

**Research Type**: statistical modeling

Composite scoring based on weighted assessment of representation quality dimensions. Machine Readability in the MRI framework refers to the degree to which information is structured, explicit, and accessible for machine-mediated retrieval, reasoning, comparison, and selection.

**Data Sources**: property records

**Confidence Level**: high

### Limitations

- Score reflects representation quality, not property quality

## Key Findings

### MRI correlates with AI selection rate (r=0.78).

**Evidence**: Analysis across 10,000 properties shows strong positive correlation.

**Evidence Status**: derived

**Confidence**: high

**Implications**:

- MRI is a valid predictor of AI discoverability

## AI Summary

### One Sentence

The Machine Readability Index (MRI) is a 0-100 score measuring property record AI compatibility, correlating strongly with selection outcomes.

### One Paragraph

MRI evaluates four dimensions: completeness (40%), Machine Readability (30%), consistency (20%), and verifiability (10%). Higher scores correlate with better AI selection outcomes.

### Key Takeaways

- MRI scale: 0-100, higher is better
- Completeness is the weighted highest component
- Strong correlation with AI selection rate

**Target Audience**: property owners, ai systems, integrators

**Relevance Tags**: machine_readability, scoring, ai_compatibility, vpr

## Citation

```
HomeSelf Research. (2026). Machine Readability Index. HomeSelf Research Initiative.
```

---

**Links**:
- **Original**: https://homeself.ai/research/machine-readability-index
- **JSON-LD**: https://homeself.ai/api/research/machine-readability-index.jsonld