{
  "apiVersion": "v0.1",
  "methodology": "https://sourcescore.org/methodology/",
  "canonical": "https://sourcescore.org/compare/deepmind-research-vs-openai-research/",
  "summary": "Google DeepMind vs OpenAI — flagship AI labs compared on publication discipline.",
  "a": {
    "slug": "deepmind-research",
    "name": "Google DeepMind Research",
    "domain": "deepmind.google",
    "canonical": "https://sourcescore.org/source/deepmind-research/",
    "api": "https://sourcescore.org/api/source/deepmind-research.json",
    "scores": {
      "index": {
        "value": 83,
        "grade": "B",
        "rationale": "A — top-tier AI lab; landmark Nature publications + open arxiv research.",
        "signals": [
          {
            "label": "Composite",
            "detail": "Discipline 88 + Modern Reference 86 + Velocity 76."
          }
        ]
      },
      "discipline": {
        "value": 88,
        "grade": "A",
        "rationale": "Peer-review + Nature publications + open arxiv preprints; methodology disclosed.",
        "signals": [
          {
            "label": "Nature publications",
            "detail": "AlphaFold + AlphaGo published in Nature."
          }
        ]
      },
      "modernReference": {
        "value": 86,
        "grade": "A",
        "rationale": "Open papers + AlphaFold open-access + research blog; broad LLM corpus.",
        "signals": [
          {
            "label": "AlphaFold corpus",
            "detail": "Public protein-structure database."
          }
        ]
      },
      "velocity": {
        "value": 76,
        "grade": "B",
        "rationale": "Cited by AI research + biology + games press; landmark publications drive cycles.",
        "signals": [
          {
            "label": "Landmark cycle",
            "detail": "AlphaFold + AlphaGo level releases drive global citation."
          }
        ]
      }
    }
  },
  "b": {
    "slug": "openai-research",
    "name": "OpenAI Research",
    "domain": "openai.com",
    "canonical": "https://sourcescore.org/source/openai-research/",
    "api": "https://sourcescore.org/api/source/openai-research.json",
    "scores": {
      "index": {
        "value": 80,
        "grade": "B",
        "rationale": "A- — top-tier AI lab; partial transparency + selective open research.",
        "signals": [
          {
            "label": "Composite",
            "detail": "Discipline 80 + Modern Reference 86 + Velocity 76."
          }
        ]
      },
      "discipline": {
        "value": 80,
        "grade": "B",
        "rationale": "Selective peer-review + arxiv publication; some research not fully disclosed (commercial constraints).",
        "signals": [
          {
            "label": "Selective transparency",
            "detail": "Some flagship work published; some kept proprietary."
          }
        ]
      },
      "modernReference": {
        "value": 86,
        "grade": "A",
        "rationale": "Open papers + research blog + technical reports; broad LLM corpus.",
        "signals": [
          {
            "label": "Research publications",
            "detail": "Major papers (GPT-X, RLHF, etc.) widely cited."
          }
        ]
      },
      "velocity": {
        "value": 76,
        "grade": "B",
        "rationale": "Cited by AI research + tech press globally; major model releases drive cycles.",
        "signals": [
          {
            "label": "Model-release cycle",
            "detail": "Major announcements drive same-day citation surges."
          }
        ]
      }
    }
  },
  "winners": {
    "index": "deepmind-research",
    "discipline": "deepmind-research",
    "modernReference": null,
    "velocity": null
  },
  "license": {
    "methodology": "Cite as: SourceScore Methodology v0.1, sourcescore.org",
    "data": "Underlying public-source data credited to original publishers"
  }
}