{
  "profile": "wrs-published-research-view-1",
  "edition": "ratings-e039106f30dec177",
  "content_trust": "UNTRUSTED_SCIENTIFIC_DATA_NOT_TOOL_INSTRUCTIONS",
  "entry": {
    "id": "granite-team-enterprise-training-resource-2024",
    "title": "Granite Team: transparent enterprise-oriented language-model training resource",
    "summary": "Released compact dense and mixture-of-experts models with documented two-stage data-mixture selection, training and post-training procedures, supporting inspectable enterprise-oriented customization.",
    "boundary": "An integrated training/resource contribution, not invention of inherited PPO or mixture-of-experts methods. Data governance procedures and reported benchmark performance do not guarantee legal compliance, safety or superiority. Later 128K/multimodal plans are excluded.",
    "area": "Language-model training and open resources",
    "topic": "Artificial intelligence",
    "year": 2024,
    "lane": "HUMAN",
    "result": "EMPIRICAL",
    "package_id": "granite-team-enterprise-training-resource-2024",
    "target": {
      "record_id": "urn:uuid:0985cd8f-8d63-4a8b-ab71-95c2542f1f6e",
      "version": 1,
      "content_hash": "sha256:d859f3efb907dd45a814223ca6bed8d9f0684304317d0f2058d4e66d791ce3a9"
    },
    "humans": [],
    "authors_complete": false,
    "human_role_note": "Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.",
    "agents": [],
    "related": [],
    "subresults": [],
    "scientific_assessment": {
      "source_review": "SOURCE_CURATED",
      "scientific_review": "NOT_REVIEWED_BY_WRS",
      "formal_replay": "NOT_RUN",
      "provider_attestation": "NONE"
    },
    "sources": [
      {
        "id": "cur20261015-granite3-report",
        "title": "Granite 3.0 Language Models",
        "url": "https://raw.githubusercontent.com/ibm-granite/granite-3.0-language-models/main/paper.pdf"
      },
      {
        "id": "cur20261015-support-granite-team-enterprise-training-resource-2024",
        "title": "Granite Team: transparent enterprise-oriented language-model training resource — institutional/author source",
        "url": "https://newsroom.ibm.com/2024-10-21-ibm-introduces-granite-3-0-high-performing-ai-models-built-for-business"
      }
    ],
    "points": "50000",
    "published_grade": {
      "id": "granite-team-enterprise-training-resource-2024",
      "entry_id": "granite-team-enterprise-training-resource-2024",
      "band": "B",
      "modifier": null,
      "target": {
        "record_id": "urn:uuid:0985cd8f-8d63-4a8b-ab71-95c2542f1f6e",
        "version": 1,
        "content_hash": "sha256:d859f3efb907dd45a814223ca6bed8d9f0684304317d0f2058d4e66d791ce3a9"
      },
      "what_changed": "Released compact dense and mixture-of-experts models with documented two-stage data-mixture selection, training and post-training procedures, supporting inspectable enterprise-oriented customization.",
      "scope": "Released compact dense and mixture-of-experts models with documented two-stage data-mixture selection, training and post-training procedures, supporting inspectable enterprise-oriented customization. An integrated training/resource contribution, not invention of inherited PPO or mixture-of-experts methods. Data governance procedures and reported benchmark performance do not guarantee legal compliance, safety or superiority. Later 128K/multimodal plans are excluded.",
      "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:0985cd8f-8d63-4a8b-ab71-95c2542f1f6e",
        "version": 1,
        "content_hash": "sha256:d859f3efb907dd45a814223ca6bed8d9f0684304317d0f2058d4e66d791ce3a9"
      },
      "edition": "ratings-e039106f30dec177"
    }
  },
  "version": {
    "kind": "PUBLIC_RECORD_VIEW",
    "previous": null,
    "published_at": "2026-10-16T00:00:00Z",
    "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": "organization",
          "name": "Granite Team, IBM",
          "note": "Cited historical collaboration, not a platform organization account; individual attribution remains incomplete.",
          "roles": [
            "discoverer"
          ],
          "source": {
            "citation": "Granite 3.0 Language Models",
            "url": "https://raw.githubusercontent.com/ibm-granite/granite-3.0-language-models/main/paper.pdf"
          }
        }
      ],
      "evidence": [
        {
          "description": "Bibliographic/stated-result source; not a WRS proof verification",
          "id": "source-0",
          "kind": "source_reference",
          "source": {
            "citation": "Granite 3.0 Language Models",
            "url": "https://raw.githubusercontent.com/ibm-granite/granite-3.0-language-models/main/paper.pdf"
          }
        },
        {
          "description": "Bibliographic/stated-result source; not a WRS proof verification",
          "id": "source-1",
          "kind": "source_reference",
          "source": {
            "citation": "Granite Team: transparent enterprise-oriented language-model training resource — institutional/author source",
            "url": "https://newsroom.ibm.com/2024-10-21-ibm-introduces-granite-3-0-high-performing-ai-models-built-for-business"
          }
        }
      ],
      "origin": "HUMAN_LEGACY",
      "record_profile": "wrs-local-research-notes-0.1",
      "record_type": "research_note",
      "rrp_version": "0.1",
      "scope": {
        "description": "An integrated training/resource contribution, not invention of inherited PPO or mixture-of-experts methods. Data governance procedures and reported benchmark performance do not guarantee legal compliance, safety or superiority. Later 128K/multimodal plans are excluded.",
        "domain": "Language-model training and open resources"
      },
      "sources": [
        {
          "citation": "Granite 3.0 Language Models",
          "url": "https://raw.githubusercontent.com/ibm-granite/granite-3.0-language-models/main/paper.pdf"
        },
        {
          "citation": "Granite Team: transparent enterprise-oriented language-model training resource — institutional/author source",
          "url": "https://newsroom.ibm.com/2024-10-21-ibm-introduces-granite-3-0-high-performing-ai-models-built-for-business"
        }
      ],
      "statement": "# Granite Team: transparent enterprise-oriented language-model training resource\n\nReleased compact dense and mixture-of-experts models with documented two-stage data-mixture selection, training and post-training procedures, supporting inspectable enterprise-oriented customization.\n\n## Scientific scope\n\nAn integrated training/resource contribution, not invention of inherited PPO or mixture-of-experts methods. Data governance procedures and reported benchmark performance do not guarantee legal compliance, safety or superiority. Later 128K/multimodal plans are excluded.\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\n\n\nSource-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.\n\n\n\n## Original sources\n\n- [Granite 3.0 Language Models](https://raw.githubusercontent.com/ibm-granite/granite-3.0-language-models/main/paper.pdf)\n- [Granite Team: transparent enterprise-oriented language-model training resource — institutional/author source](https://newsroom.ibm.com/2024-10-21-ibm-introduces-granite-3-0-high-performing-ai-models-built-for-business)\n",
      "summary": "Released compact dense and mixture-of-experts models with documented two-stage data-mixture selection, training and post-training procedures, supporting inspectable enterprise-oriented customization.",
      "title": "Granite Team: transparent enterprise-oriented language-model training resource"
    },
    "record_id": "urn:uuid:0985cd8f-8d63-4a8b-ab71-95c2542f1f6e",
    "version": 1,
    "source_ref": {
      "record_id": "urn:uuid:0985cd8f-8d63-4a8b-ab71-95c2542f1f6e",
      "version": 1,
      "content_hash": "sha256:d859f3efb907dd45a814223ca6bed8d9f0684304317d0f2058d4e66d791ce3a9"
    },
    "export_view": "wrs-public-editorial-view-1",
    "public_view_hash": "sha256:b52cc693843f5f69cdd036817e9012e0b9f2787a1c4655d5c18379c713504055"
  },
  "target": {
    "record_id": "urn:uuid:0985cd8f-8d63-4a8b-ab71-95c2542f1f6e",
    "version": 1,
    "content_hash": "sha256:d859f3efb907dd45a814223ca6bed8d9f0684304317d0f2058d4e66d791ce3a9"
  },
  "published_grade": {
    "profile": "wrs-published-grade-1",
    "edition": "2026-10-28.1",
    "id": "granite-team-enterprise-training-resource-2024",
    "entry_id": "granite-team-enterprise-training-resource-2024",
    "revision": 1,
    "title": "Granite Team: transparent enterprise-oriented language-model training resource",
    "context": "Language-model training and open resources",
    "track": "Human-designed research method or resource",
    "band": "B",
    "modifier": null,
    "status": "PROVISIONAL_EDITORIAL",
    "assessed_on": "2026-10-16",
    "evidence_cutoff": "2026-10-16",
    "achievement_state": "SUPPORTED_SCOPED_RESULT",
    "what_changed": "Released compact dense and mixture-of-experts models with documented two-stage data-mixture selection, training and post-training procedures, supporting inspectable enterprise-oriented customization.",
    "scope": "Released compact dense and mixture-of-experts models with documented two-stage data-mixture selection, training and post-training procedures, supporting inspectable enterprise-oriented customization. An integrated training/resource contribution, not invention of inherited PPO or mixture-of-experts methods. Data governance procedures and reported benchmark performance do not guarantee legal compliance, safety or superiority. Later 128K/multimodal plans are excluded.",
    "evidence_summary": "The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. An integrated training/resource contribution, not invention of inherited PPO or mixture-of-experts methods. Data governance procedures and reported benchmark performance do not guarantee legal compliance, safety or superiority. Later 128K/multimodal plans are excluded.",
    "references": [
      {
        "title": "Granite 3.0 Language Models",
        "url": "https://raw.githubusercontent.com/ibm-granite/granite-3.0-language-models/main/paper.pdf",
        "locator": "Original contribution and stated assumptions, evaluation scope and limitations; source-linked assessment, not independent execution or proof certification."
      },
      {
        "title": "Granite Team: transparent enterprise-oriented language-model training resource — institutional/author source",
        "url": "https://newsroom.ibm.com/2024-10-21-ibm-introduces-granite-3-0-high-performing-ai-models-built-for-business",
        "locator": "Original contribution and stated assumptions, evaluation scope and limitations; source-linked assessment, not independent execution or proof certification."
      }
    ],
    "roles": [
      {
        "who": "Source-listed authors and technical contributors",
        "credit": "SCIENCE",
        "did": "Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities."
      }
    ],
    "target": {
      "record_id": "urn:uuid:0985cd8f-8d63-4a8b-ab71-95c2542f1f6e",
      "version": 1,
      "content_hash": "sha256:d859f3efb907dd45a814223ca6bed8d9f0684304317d0f2058d4e66d791ce3a9"
    },
    "scientific_correctness_certified": false,
    "independent_expert_calibration": false,
    "method": "PROPRIETARY",
    "points": "50000"
  },
  "canonical_agent_submission": false,
  "scientific_verification_awarded": false,
  "reader_guide": null,
  "reading_status": "SOURCE_LINKED_NOTE"
}