{
  "id": "https://doi.org/10.5281/zenodo.21943877",
  "doi": "10.5281/ZENODO.21943877",
  "url": "https://zenodo.org/doi/10.5281/zenodo.21943877",
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    "schemaOrg": "Report",
    "resourceType": "",
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  "creators": [
    {
      "name": "Jacobs, Tim",
      "nameType": "Personal",
      "givenName": "Tim",
      "familyName": "Jacobs",
      "affiliation": [
        {
          "name": "KTS Global"
        }
      ],
      "nameIdentifiers": [
        {
          "nameIdentifier": "0009-0008-7130-1448",
          "nameIdentifierScheme": "ORCID"
        }
      ]
    }
  ],
  "titles": [
    {
      "title": "Machine Entity Comprehension: A Black-Box Conformance Framework for Identity, Context and Change"
    }
  ],
  "publisher": {
    "name": "KTS Global"
  },
  "container": {},
  "subjects": [
    {
      "subject": "Machine Entity Comprehension"
    },
    {
      "subject": "Geometry Intelligence"
    },
    {
      "subject": "Geometry Intelligence Infrastructure"
    },
    {
      "subject": "Governed Relational Geometry"
    },
    {
      "subject": "Black-box evaluation"
    },
    {
      "subject": "AI assurance"
    },
    {
      "subject": "Identity persistence"
    },
    {
      "subject": "Entity disambiguation"
    },
    {
      "subject": "Material change"
    },
    {
      "subject": "Contradiction handling"
    },
    {
      "subject": "Conformance testing"
    },
    {
      "subject": "TEVV"
    },
    {
      "subject": "Evidence governance"
    },
    {
      "subject": "Web4"
    },
    {
      "subject": "Sovereign systems"
    },
    {
      "subject": "Formal methods"
    }
  ],
  "dates": [
    {
      "date": "2026-08-15",
      "dateType": "Issued"
    }
  ],
  "publicationYear": 2026,
  "language": "en",
  "identifiers": [
    {
      "identifier": "oai:zenodo.org:21943877",
      "identifierType": "oai"
    }
  ],
  "version": "Final Manuscript 1.0",
  "rightsList": [
    {
      "rights": "Creative Commons Attribution 4.0 International",
      "rightsUri": "https://creativecommons.org/licenses/by/4.0/legalcode",
      "schemeUri": "https://spdx.org/licenses/",
      "rightsIdentifier": "cc-by-4.0",
      "rightsIdentifierScheme": "SPDX"
    }
  ],
  "descriptions": [
    {
      "description": "Machine Entity Comprehension defines a black-box conformance framework for evaluating whether a system can preserve entity identity, distinguish contextually similar entities, maintain relevant relationships and constraints, respond coherently to material changes, contain contradiction and produce repeatable outcomes under equivalent declared state.\n\nThe paper establishes the conformance layer for Geometry Intelligence Infrastructure, a proposed class of evidence-governed, model-independent AI infrastructure. It converts the field definition in Paper 1 and the formal model in Paper 2 into externally observable behavioral requirements.\n\nThe framework uses pre-registered evidence sets, policy profiles, declared system state, controlled perturbations, reference outcomes, negative controls and retained adjudication records. Nine profiles cover identity persistence, entity disambiguation, relationship invariance, material-change response, contradiction handling, repeatability, multi-node outcome equivalence, disconnected continuity and retrieval-baseline differentiation.\n\nIndividual profiles use MEC-1 through MEC-9. Aggregate reporting uses MEC-C0 through MEC-C4 to avoid identifier collision. Conformance is reported as a capability vector and evaluator-independence class rather than as consciousness, general intelligence or universal understanding.\n\nThe framework is implementation-neutral. It can evaluate proprietary, open, symbolic, geometric, graph-based, model-based and hybrid systems without requiring mandatory disclosure of protected internal mechanisms.\n\nThe paper also specifies public formats for test cases, evidence records, adjudication records and conformance reports, together with a proposed synthetic pilot benchmark. Publication of the benchmark design does not constitute an executed conformance result.\n\nThis is Paper 3 of the Geometry Intelligence Foundational Series. Paper 1 defines the field, Paper 2 defines governed relational transformation, Paper 3 defines external conformance, and Paper 4 develops an optional sovereign Web4 federation architecture.\n\nFinal Manuscript 1.0. Published by KTS Global. Licensed under CC BY 4.0.",
      "descriptionType": "Abstract"
    }
  ],
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