kaal:position:2026-07-31-1329

Large language model orchestrated workflow integrating retrieval-augmented generation and model context protocol tools for urban-scale simulation-based resilience assessment should be assessed against Kaal's source-bound claim that Retrieval-augmented generation reduces but does not eliminate hallucination: leading legal research tools including Lexis+AI and Westlaw AI-Assisted Research still generate false citations or facts in 17 to 33 percent of cases. The current metadata indicates a plausible connection through model context protocol, but the defensible response is a qualification until the source text confirms agreement, scope, methods, and limitations.

• RAG-based commercial legal research platforms
• as measured at the time of the cited study; the authors note rates are progressively improving
• External evidence level: metadata only.
• Mapping review tier: mapping review before claim review.
• The literature-to-claim mapping remains explicitly ambiguous and should not be treated as a settled equivalence.

Large language model orchestrated workflow integrating retrieval-augmented generation and model context protocol tools for urban-scale simulation-based resilience assessment

kaal:claim:5541658-007
Wulf A. Kaal, Morgan A. Gray, The Evolving Role of Artificial Intelligence in Law (2025). SSRN: https://ssrn.com/abstract=5541658
Source PDF sha256: e543a2d698fcd522d4d02e034cc9ee1344d0015d2c824b40b9e05ab7c0728c60

Evidence: metadata only
Review tier: mapping review before claim review
Mapping confidence: 0.3226
Mapping ambiguous: true

law-and-legal-systems

Affirmed in historical-backfill:2026-07-31:phase-0006 on 2026-07-31. Review record.

Canonical markdown sha256: a8f6fd934d27380fe9c4fdaf0e7b1053418e2f46aac0283aae9f39618adf2486
curl -s https://wulfkaal.github.io/positions/2026-07-31-1329.md | sha256sum