---
title: "Model Evaluation & Threat Research"
section: "entities"
type: "entity"
created: "2026-08-27"
updated: "2026-08-27"
confidence: "high"
tags: ["company", "evaluation"]
canonical: "https://pyweb.dev/wiki/model-evaluation-and-threat-research"
---
# Model Evaluation & Threat Research

Model Evaluation & Threat Research (METR) studies frontier AI capabilities and their real-world effects. Its task-completion horizon work models agent success against human expert task duration, while its developer-productivity randomized trial found that early-2025 AI tools increased completion time by 19% for experienced maintainers working in familiar mature repositories. [[source: metr-task-completion-time-horizons-2026]](/wiki/raw/articles/metr-task-completion-time-horizons-2026)^[raw/papers/metr-developer-productivity-rct-2025.md]

## Related
- [agentic quality evidence](/wiki/agentic-quality-evidence) — benchmark and productivity evidence
- [error analysis and evals](/wiki/error-analysis-and-evals) — evaluation design and error analysis
- [agentic code quality](/wiki/agentic-code-quality) — proposed factory controls

---

## Agent Navigation

cluster: person (170 pages) | betweenness: 23.2

### References (outbound)
- [Agentic Code Quality — Evidence Map](https://pyweb.dev/wiki/agentic-quality-evidence.md)
- [Error Analysis and Evals](https://pyweb.dev/wiki/error-analysis-and-evals.md)
- [Agentic Code Quality](https://pyweb.dev/wiki/agentic-code-quality.md)

### Referenced by (inbound)
- [Agentic Code Quality Evidence — Entity Accounting](https://pyweb.dev/wiki/agentic-code-quality-entity-accounting.md)

### Evidence (verified primary sources)
- [metr-task-completion-time-horizons-2026](https://pyweb.dev/wiki/raw/articles/metr-task-completion-time-horizons-2026.md) | origin: https://metr.org/time-horizons/ | ingested: 2026-08-27 | sha256: 01fa095450fa59f3a2b8dcd70e5f5cd5a60cbd81ba7b9efd60f5c92b1e36790b
- raw/papers/metr-developer-productivity-rct-2025.md (internal workspace doc)

### Machine endpoints
- Knowledge graph: https://pyweb.dev/api/graph.json
- Graph analysis: https://pyweb.dev/api/graph-analysis.json
- Context index: https://pyweb.dev/llms.txt