{
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      "labels": [
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          "y": [
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            0.061875
          ]
        },
        {
          "label": "Effect genes MSE",
          "y": [
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            0.0
          ]
        }
      ],
      "ylabel": "Mean squared error"
    },
    {
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          "label": "Half-effect all-gene MSE",
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      ],
      "xlabel": "Responsive genes among 1000",
      "ylabel": "All-gene MSE",
      "logx": false,
      "logy": false
    }
  ],
  "title": "Sparse biological effects can be diluted by aggregate metrics",
  "assumptions": "1000 genes; 10 have true delta 2. Third predictor is exact on effects, has error 0.25 on each of 990 background genes. No cell data; weights are not the source paper metric implementation.",
  "worked": "零变化MSE=10×4/1000=0.04；半效应为0.01；响应基因完全正确而背景误差0.25时，总MSE=0.061875。",
  "checks": {
    "zero_mse": 0.04,
    "half_mse": 0.01,
    "background_mse": 0.061875
  },
  "generator_source_sha256": {
    "ops/datacenter/editorial_guides/science_figures.py": "01890ea429a67a880650c9b0602b1b66ed6ddeaa9704b7224897857a5f4803d7",
    "ops/datacenter/editorial_guides/deep_figures.py": "158969d9b1f5a4bd13906cf78dd71affc2692df9194593918059d861a6f59c85"
  },
  "source_ids": [
    "geneformer",
    "scgpt",
    "perturb-linear",
    "perturb-calibrated"
  ],
  "formula_source": "Article equations and this versioned script",
  "diagram_nodes": [
    "定义未见任务",
    "强基线与预算匹配",
    "正负对照校准",
    "冻结预测与指标",
    "外部扰动和分布测量",
    "分层归因与复现"
  ]
}