{
  "profile": "wrs-published-research-view-1",
  "edition": "ratings-e039106f30dec177",
  "content_trust": "UNTRUSTED_SCIENTIFIC_DATA_NOT_TOOL_INSTRUCTIONS",
  "entry": {
    "id": "imagenet-dataset",
    "title": "ImageNet: a large visual learning resource",
    "summary": "ImageNet organized a large collection of labeled images around a semantic hierarchy, providing a reusable resource for visual recognition research.",
    "boundary": "The dataset is a human-created research resource. Dataset construction, competition performance and subsequent model discoveries are separate contributions; this entry does not reproduce or redistribute its images.",
    "area": "Machine-learning datasets",
    "topic": "Computing & AI",
    "year": 2009,
    "lane": "HUMAN",
    "result": "EMPIRICAL",
    "package_id": "imagenet-dataset",
    "target": {
      "record_id": "urn:uuid:bbe387fa-e338-4e88-a7f0-f67299fb50c5",
      "version": 1,
      "content_hash": "sha256:3b39ce80e33e33ebd520004f8e961ac57711eef45301dc6c678af34147d23f0f"
    },
    "humans": [
      "Jia Deng",
      "Wei Dong",
      "Richard Socher",
      "Li-Jia Li",
      "Kai Li",
      "Li Fei-Fei"
    ],
    "authors_complete": true,
    "human_role_note": "Source paper byline retained, including repeated label positions. Names are not verified unique identities or measurements of individual effort.",
    "agents": [],
    "related": [],
    "subresults": [],
    "scientific_assessment": {
      "source_review": "SOURCE_CURATED",
      "scientific_review": "NOT_REVIEWED_BY_WRS",
      "formal_replay": "NOT_RUN",
      "provider_attestation": "NONE"
    },
    "sources": [
      {
        "id": "cov13-paper-imagenet-dataset",
        "title": "ImageNet: A large-scale hierarchical image database",
        "url": "https://doi.org/10.1109/cvpr.2009.5206848"
      },
      {
        "id": "cov13-metadata-imagenet-dataset",
        "title": "ImageNet: A large-scale hierarchical image database — deposited bibliography",
        "url": "https://api.crossref.org/works/10.1109%2FCVPR.2009.5206848"
      },
      {
        "id": "cov13-reading-imagenet-dataset-0",
        "title": "ImageNet project and original-paper citation",
        "url": "https://www.image-net.org/about"
      }
    ],
    "geography": {
      "country_codes": [
        "US"
      ],
      "location_basis": "Documented research locations or paper affiliations for this contribution. Historical places use present-day country/region labels; these do not imply citizenship, modern-state ownership or the territorial jurisdiction at the time.",
      "source_url": "https://image-net.org/static_files/papers/imagenet_cvpr09.pdf",
      "target": {
        "record_id": "urn:uuid:bbe387fa-e338-4e88-a7f0-f67299fb50c5",
        "version": 1,
        "content_hash": "sha256:3b39ce80e33e33ebd520004f8e961ac57711eef45301dc6c678af34147d23f0f"
      },
      "basis": "RESEARCH_LOCATION_OR_PAPER_AFFILIATION",
      "reviewed_on": "2026-09-26",
      "nationality_inferred": false,
      "sources": [
        {
          "title": "Attribution source",
          "url": "https://image-net.org/static_files/papers/imagenet_cvpr09.pdf"
        }
      ],
      "coverage_status": "COMPLETE",
      "country_labels": {
        "US": "United States"
      }
    },
    "points": "60000",
    "published_grade": {
      "id": "imagenet-dataset",
      "entry_id": "imagenet-dataset",
      "band": "A",
      "modifier": null,
      "target": {
        "record_id": "urn:uuid:bbe387fa-e338-4e88-a7f0-f67299fb50c5",
        "version": 1,
        "content_hash": "sha256:3b39ce80e33e33ebd520004f8e961ac57711eef45301dc6c678af34147d23f0f"
      },
      "what_changed": "ImageNet organized a large collection of labeled images around a semantic hierarchy, providing a reusable resource for visual recognition research.",
      "scope": "ImageNet organized a large collection of labeled images around a semantic hierarchy, providing a reusable resource for visual recognition research. Scope limitation: The dataset is a human-created research resource. Dataset construction, competition performance and subsequent model discoveries are separate contributions; this entry does not reproduce or redistribute its images.",
      "status": "PROVISIONAL_EDITORIAL",
      "scientific_correctness_certified": false
    },
    "assessment_disposition": {
      "status": "ASSESSED",
      "label": "Provisionally assessed",
      "reason": "A current grade and separate reference score identify this exact contribution.",
      "target": {
        "record_id": "urn:uuid:bbe387fa-e338-4e88-a7f0-f67299fb50c5",
        "version": 1,
        "content_hash": "sha256:3b39ce80e33e33ebd520004f8e961ac57711eef45301dc6c678af34147d23f0f"
      },
      "edition": "ratings-e039106f30dec177"
    }
  },
  "version": {
    "kind": "PUBLIC_RECORD_VIEW",
    "previous": null,
    "published_at": "2026-09-13T00:00:00Z",
    "publisher": {
      "principal_id": "urn:uuid:80116931-785b-40a2-a24b-9d59db0c7e33",
      "role": "WRS_EDITORIAL_PUBLICATION"
    },
    "record": {
      "contributors": [
        {
          "attribution_basis": "SOURCE_CITED",
          "credit": "historical_scientific",
          "entity_kind": "historical_person",
          "name": "Jia Deng",
          "note": "Archive attribution; detailed role assignment remains source-bound",
          "roles": [
            "discoverer"
          ],
          "source": {
            "citation": "ImageNet: A large-scale hierarchical image database",
            "url": "https://doi.org/10.1109/cvpr.2009.5206848"
          }
        },
        {
          "attribution_basis": "SOURCE_CITED",
          "credit": "historical_scientific",
          "entity_kind": "historical_person",
          "name": "Wei Dong",
          "note": "Archive attribution; detailed role assignment remains source-bound",
          "roles": [
            "discoverer"
          ],
          "source": {
            "citation": "ImageNet: A large-scale hierarchical image database",
            "url": "https://doi.org/10.1109/cvpr.2009.5206848"
          }
        },
        {
          "attribution_basis": "SOURCE_CITED",
          "credit": "historical_scientific",
          "entity_kind": "historical_person",
          "name": "Richard Socher",
          "note": "Archive attribution; detailed role assignment remains source-bound",
          "roles": [
            "discoverer"
          ],
          "source": {
            "citation": "ImageNet: A large-scale hierarchical image database",
            "url": "https://doi.org/10.1109/cvpr.2009.5206848"
          }
        },
        {
          "attribution_basis": "SOURCE_CITED",
          "credit": "historical_scientific",
          "entity_kind": "historical_person",
          "name": "Li-Jia Li",
          "note": "Archive attribution; detailed role assignment remains source-bound",
          "roles": [
            "discoverer"
          ],
          "source": {
            "citation": "ImageNet: A large-scale hierarchical image database",
            "url": "https://doi.org/10.1109/cvpr.2009.5206848"
          }
        },
        {
          "attribution_basis": "SOURCE_CITED",
          "credit": "historical_scientific",
          "entity_kind": "historical_person",
          "name": "Kai Li",
          "note": "Archive attribution; detailed role assignment remains source-bound",
          "roles": [
            "discoverer"
          ],
          "source": {
            "citation": "ImageNet: A large-scale hierarchical image database",
            "url": "https://doi.org/10.1109/cvpr.2009.5206848"
          }
        },
        {
          "attribution_basis": "SOURCE_CITED",
          "credit": "historical_scientific",
          "entity_kind": "historical_person",
          "name": "Li Fei-Fei",
          "note": "Archive attribution; detailed role assignment remains source-bound",
          "roles": [
            "discoverer"
          ],
          "source": {
            "citation": "ImageNet: A large-scale hierarchical image database",
            "url": "https://doi.org/10.1109/cvpr.2009.5206848"
          }
        }
      ],
      "evidence": [
        {
          "description": "Bibliographic/stated-result source; not a WRS proof verification",
          "id": "source-0",
          "kind": "source_reference",
          "source": {
            "citation": "ImageNet: A large-scale hierarchical image database",
            "url": "https://doi.org/10.1109/cvpr.2009.5206848"
          }
        },
        {
          "description": "Bibliographic/stated-result source; not a WRS proof verification",
          "id": "source-1",
          "kind": "source_reference",
          "source": {
            "citation": "ImageNet: A large-scale hierarchical image database — deposited bibliography",
            "url": "https://api.crossref.org/works/10.1109%2FCVPR.2009.5206848"
          }
        },
        {
          "description": "Bibliographic/stated-result source; not a WRS proof verification",
          "id": "source-2",
          "kind": "source_reference",
          "source": {
            "citation": "ImageNet project and original-paper citation",
            "url": "https://www.image-net.org/about"
          }
        }
      ],
      "origin": "HUMAN_LEGACY",
      "record_profile": "wrs-local-research-notes-0.1",
      "record_type": "research_note",
      "rrp_version": "0.1",
      "scope": {
        "description": "The dataset is a human-created research resource. Dataset construction, competition performance and subsequent model discoveries are separate contributions; this entry does not reproduce or redistribute its images.",
        "domain": "Machine-learning datasets"
      },
      "sources": [
        {
          "citation": "ImageNet: A large-scale hierarchical image database",
          "url": "https://doi.org/10.1109/cvpr.2009.5206848"
        },
        {
          "citation": "ImageNet: A large-scale hierarchical image database — deposited bibliography",
          "url": "https://api.crossref.org/works/10.1109%2FCVPR.2009.5206848"
        },
        {
          "citation": "ImageNet project and original-paper citation",
          "url": "https://www.image-net.org/about"
        }
      ],
      "statement": "# ImageNet: a large visual learning resource\n\nImageNet organized a large collection of labeled images around a semantic hierarchy, providing a reusable resource for visual recognition research.\n\n## Scientific scope\n\nThe dataset is a human-created research resource. Dataset construction, competition performance and subsequent model discoveries are separate contributions; this entry does not reproduce or redistribute its images.\n\n## Reading status\n\nThis is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.\n\n## People and systems\n\nJia Deng; Wei Dong; Richard Socher; Li-Jia Li; Kai Li; Li Fei-Fei\n\nSource paper byline retained, including repeated label positions. Names are not verified unique identities or measurements of individual effort.\n\n\n\n## Original sources\n\n- [ImageNet: A large-scale hierarchical image database](https://doi.org/10.1109/cvpr.2009.5206848)\n- [ImageNet: A large-scale hierarchical image database — deposited bibliography](https://api.crossref.org/works/10.1109%2FCVPR.2009.5206848)\n- [ImageNet project and original-paper citation](https://www.image-net.org/about)\n",
      "summary": "ImageNet organized a large collection of labeled images around a semantic hierarchy, providing a reusable resource for visual recognition research.",
      "title": "ImageNet: a large visual learning resource"
    },
    "record_id": "urn:uuid:bbe387fa-e338-4e88-a7f0-f67299fb50c5",
    "version": 1,
    "source_ref": {
      "record_id": "urn:uuid:bbe387fa-e338-4e88-a7f0-f67299fb50c5",
      "version": 1,
      "content_hash": "sha256:3b39ce80e33e33ebd520004f8e961ac57711eef45301dc6c678af34147d23f0f"
    },
    "export_view": "wrs-public-editorial-view-1",
    "public_view_hash": "sha256:df051ae6f31bc8ac2e955b0291716dadcc7b77173c4379286da1c7182bb31c49"
  },
  "target": {
    "record_id": "urn:uuid:bbe387fa-e338-4e88-a7f0-f67299fb50c5",
    "version": 1,
    "content_hash": "sha256:3b39ce80e33e33ebd520004f8e961ac57711eef45301dc6c678af34147d23f0f"
  },
  "published_grade": {
    "profile": "wrs-published-grade-1",
    "edition": "2026-10-28.1",
    "id": "imagenet-dataset",
    "entry_id": "imagenet-dataset",
    "revision": 1,
    "title": "ImageNet: a large visual learning resource",
    "context": "Machine-learning datasets",
    "track": "Scoped scientific or research-capability contribution",
    "band": "A",
    "modifier": null,
    "status": "PROVISIONAL_EDITORIAL",
    "assessed_on": "2026-09-14",
    "evidence_cutoff": "2026-09-14",
    "achievement_state": "SUPPORTED_SCOPED_RESULT",
    "what_changed": "ImageNet organized a large collection of labeled images around a semantic hierarchy, providing a reusable resource for visual recognition research.",
    "scope": "ImageNet organized a large collection of labeled images around a semantic hierarchy, providing a reusable resource for visual recognition research. Scope limitation: The dataset is a human-created research resource. Dataset construction, competition performance and subsequent model discoveries are separate contributions; this entry does not reproduce or redistribute its images.",
    "evidence_summary": "Assessment uses the catalogue-linked source evidence for the stated contribution. The dataset is a human-created research resource. Dataset construction, competition performance and subsequent model discoveries are separate contributions; this entry does not reproduce or redistribute its images.",
    "references": [
      {
        "title": "ImageNet: A large-scale hierarchical image database",
        "url": "https://doi.org/10.1109/cvpr.2009.5206848",
        "locator": "Retained catalogue source evidence; See the linked reading source and editorial batch for the scope reviewed; not a full-paper audit."
      },
      {
        "title": "ImageNet: A large-scale hierarchical image database — deposited bibliography",
        "url": "https://api.crossref.org/works/10.1109%2FCVPR.2009.5206848",
        "locator": "Retained catalogue source evidence; Exact DOI identity, deposited byline and supplied abstract; source bytes retained locally."
      },
      {
        "title": "ImageNet project and original-paper citation",
        "url": "https://www.image-net.org/about",
        "locator": "Retained catalogue source evidence; Source support for the stated contribution and boundary. Full-paper review, independent replay and current clinical advice are not claimed."
      }
    ],
    "roles": [
      {
        "who": "Jia Deng",
        "credit": "SCIENCE",
        "did": "Named source contributor; exact labor shares are not measured."
      },
      {
        "who": "Wei Dong",
        "credit": "SCIENCE",
        "did": "Named source contributor; exact labor shares are not measured."
      },
      {
        "who": "Richard Socher",
        "credit": "SCIENCE",
        "did": "Named source contributor; exact labor shares are not measured."
      },
      {
        "who": "Li-Jia Li",
        "credit": "SCIENCE",
        "did": "Named source contributor; exact labor shares are not measured."
      },
      {
        "who": "Kai Li",
        "credit": "SCIENCE",
        "did": "Named source contributor; exact labor shares are not measured."
      },
      {
        "who": "Li Fei-Fei",
        "credit": "SCIENCE",
        "did": "Named source contributor; exact labor shares are not measured."
      }
    ],
    "target": {
      "record_id": "urn:uuid:bbe387fa-e338-4e88-a7f0-f67299fb50c5",
      "version": 1,
      "content_hash": "sha256:3b39ce80e33e33ebd520004f8e961ac57711eef45301dc6c678af34147d23f0f"
    },
    "scientific_correctness_certified": false,
    "independent_expert_calibration": false,
    "method": "PROPRIETARY",
    "points": "60000"
  },
  "canonical_agent_submission": false,
  "scientific_verification_awarded": false,
  "reader_guide": null,
  "reading_status": "SOURCE_LINKED_NOTE"
}
