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 "name": "Streaming Understanding Agent Governance Technology Approaches E68042Af3F",
 "text": "Understanding agent governance technology approaches presents the following source proposition: Agent artificial intelligence (AI) automates AI using the reasoning power of large language models (LLMs) to make decisions without human intervention. This proposition is pertinent to Kaal's source-bound claim that The Shenzhen courts illustrate a workable three step human-in-the-loop design for generative judicial AI: the judge decides first, the LLM generates the supporting reasoning, and the judge then revises that output to finalize the judgment. The proposed response is an extension: the relationship should remain limited to the retrieved source proposition and the mapped Kaal claim unless fuller source review supports a broader conclusion.",
 "author": {
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  "name": "Wulf A. Kaal",
  "identifier": "https://orcid.org/0009-0008-7840-1847"
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  "External evidence level: abstract indexed.",
  "Mapping review tier: moderate-confidence claim review.",
  "Primary mapping confidence: 0.4854.",
  "The source-to-claim mapping remains explicitly ambiguous and is published with that limitation."
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  "name": "Understanding agent governance technology approaches",
  "url": "https://doi.org/10.69554/uxen1437"
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  "identifier": "kaal:claim:5541658-010",
  "url": "https://wulfkaal.github.io/claims/5541658-010",
  "citation": "Wulf A. Kaal, Morgan A. Gray, The Evolving Role of Artificial Intelligence in Law (2025). SSRN: https://ssrn.com/abstract=5541658",
  "paper": "Wulf A. Kaal, Morgan A. Gray, The Evolving Role of Artificial Intelligence in Law",
  "authors": [
   "Wulf A. Kaal"
  ],
  "year": "2025",
  "ssrn": "https://ssrn.com/abstract=5541658",
  "source_pdf_sha256": "e543a2d698fcd522d4d02e034cc9ee1344d0015d2c824b40b9e05ab7c0728c60"
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 "mappingWhyRelevant": "Shared high-information concepts: artificial, intelligence, reasoning, llms, make, decisions, human. Scope: Chinese courts using LLMs to draft judicial opinions.",
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