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 "text": "AgenticCyOps: Securing Multi-Agentic AI Integration in Enterprise Cyber Operations should be assessed against Kaal's source-bound claim that Managing machine learning assets and complying with laws such as GDPR and CCPA becomes significantly harder under decentralized governance, because distributed data and operations complicate tracking data flows, enforcing privacy controls, and demonstrating compliance during audits. 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.",
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  "identifier": "https://orcid.org/0009-0008-7840-1847"
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  "decentralization",
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  "External evidence level: abstract indexed.",
  "Mapping review tier: ambiguity triage before claim review.",
  "The literature-to-claim mapping remains explicitly ambiguous and should not be treated as a settled equivalence."
 ],
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  "name": "AgenticCyOps: Securing Multi-Agentic AI Integration in Enterprise Cyber Operations",
  "url": "https://www.semanticscholar.org/paper/7ab1fc7d527c62330ba9bb1d818b6843b2a9d53c"
 },
 "extends": {
  "identifier": "kaal:claim:4796714-032",
  "url": "https://wulfkaal.github.io/claims/4796714-032",
  "citation": "Wulf A. Kaal, AI Governance (2024). SSRN: https://ssrn.com/abstract=4796714",
  "paper": "AI Governance",
  "authors": [
   "Wulf A. Kaal"
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  "ssrn": "https://ssrn.com/abstract=4796714",
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 "recordTypeNote": "Dated commentary position extending a scholarly corpus claim. Not a verbatim claim extracted from the paper.",
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 "mappingWhyRelevant": "Shared high-information concepts: operations, over, management, data, compliance, gdpr, design. Scope: applies to decentralized ML governance spanning multiple stakeholders and locations; concerns stringent privacy regimes such as GDPR and CCPA.",
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  "api": "https://api.semanticscholar.org/graph/v1/paper/search/bulk",
  "query": "model context protocol",
  "queryId": "concept:9c5da690faad",
  "page": 1,
  "sourceRank": 468,
  "retrievedAt": "2026-07-31T13:58:04.059Z",
  "citationCount": 2,
  "venue": "arXiv.org",
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