{
  "schema": "lod2-simple-overview-v1",
  "primary_method": "graph_20000_long_s20261031",
  "buildings": 200,
  "conditions": 12,
  "methods": [
    {
      "id": "raw",
      "label": "原始基线",
      "recipe": "保留全部输入点，直接交给 Roofer 重建。",
      "buildings": 200,
      "fixed_denominator": 2400,
      "primary_capped_loss_10m": 1.094044631553961,
      "ridge3d_confirmed_f1": 0.5411725439075514,
      "native_lod2_success_count": 2369,
      "native_failure_or_fallback_count": 31,
      "clean_individual_harmed_over_2cm": 0,
      "new_failures_vs_raw_count": 0
    },
    {
      "id": "geometry",
      "label": "几何规则",
      "recipe": "用局部平面、法向、邻域支持和连通性筛点，再交给 Roofer。",
      "buildings": 200,
      "fixed_denominator": 2400,
      "primary_capped_loss_10m": 1.104115773374105,
      "ridge3d_confirmed_f1": 0.5449900013276858,
      "native_lod2_success_count": 2369,
      "native_failure_or_fallback_count": 31,
      "clean_individual_harmed_over_2cm": 1,
      "new_failures_vs_raw_count": 0
    },
    {
      "id": "global_3500_s20261031",
      "label": "全局点网络 · 3.5k",
      "recipe": "逐点编码 → 全局最大池化 → 预测保留概率 → Roofer。",
      "buildings": 200,
      "fixed_denominator": 2400,
      "primary_capped_loss_10m": 0.5577044871398497,
      "ridge3d_confirmed_f1": 0.6496828285309381,
      "native_lod2_success_count": 2367,
      "native_failure_or_fallback_count": 33,
      "clean_individual_harmed_over_2cm": 2,
      "new_failures_vs_raw_count": 2
    },
    {
      "id": "graph_3500_s20261031",
      "label": "局部图网络 · 3.5k",
      "recipe": "16 邻点局部边特征 → 两层图网络＋全局上下文 → 保留概率 → Roofer。",
      "buildings": 200,
      "fixed_denominator": 2400,
      "primary_capped_loss_10m": 0.5141727665313772,
      "ridge3d_confirmed_f1": 0.6589003365510712,
      "native_lod2_success_count": 2369,
      "native_failure_or_fallback_count": 31,
      "clean_individual_harmed_over_2cm": 1,
      "new_failures_vs_raw_count": 0
    },
    {
      "id": "graph_20000_long_s20261031",
      "label": "局部图网络 · 20k 长训练",
      "recipe": "与 3.5k 图网络同架构；训练建筑增加到 20k，训练步数由 24k 增至 48k。",
      "buildings": 200,
      "fixed_denominator": 2400,
      "primary_capped_loss_10m": 0.5123316077996095,
      "ridge3d_confirmed_f1": 0.6609475685500079,
      "native_lod2_success_count": 2369,
      "native_failure_or_fallback_count": 31,
      "clean_individual_harmed_over_2cm": 0,
      "new_failures_vs_raw_count": 0
    }
  ],
  "source": "native/index.json",
  "selection": "All DL rows use the pre-existing fixed seed 20261031; primary was selected on source validation, not this test.",
  "views": [
    {
      "id": "controlled",
      "label": "受控测试 · 200 栋",
      "url": "native/?compact=1"
    },
    {
      "id": "real",
      "label": "真实点云 · 荷兰 20 栋",
      "url": "studies/scaling/real/raw_quality_preview_dl_qualitative.html"
    },
    {
      "id": "us",
      "label": "美国试验 · 120 栋",
      "url": "viewer/?chapter=tree"
    }
  ]
}