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节点 n25

heart_jcf_peri reweighting, heart x1.6, edge x0.4 (fake Engineer, node 25)

方法说明?节点程序自带的 METHOD.md：这个程序做了什么、为什么。

来自 programs.git f913327ece:solution/METHOD.md

调研员的计划

代码改动?这个节点的程序和父节点程序的逐行差别：绿色是新增，红色是删除。

对比：父节点版本 cd04238ecb。改动的文件：solution/METHOD.md +3 −0、solution/README.md +0 −4、solution/run.py +5 −9

diff --git a/solution/METHOD.md b/solution/METHOD.mdnew file mode 100644index 0000000..1c140ca--- /dev/null+++ b/solution/METHOD.md@@ -0,0 +1,3 @@+heart_jcf_peri reweighting, heart x1.6, edge x0.4 (fake Engineer, node 25)++Test run only.diff --git a/solution/README.md b/solution/README.mddeleted file mode 100644index e66c7c3..0000000--- a/solution/README.md+++ /dev/null@@ -1,4 +0,0 @@-# heart_jcf_peri--run2（20260927-172643-grok-t1）的 T1 胜者：对最新输入阶段按细胞类型重加权再抽 4000 个真实细胞，不改表达。丢 Neural Tube；心脏类（CM、内皮/心内膜、SHF/PHM、JCF、心包、心外膜原基）×1.6；表面外胚层、EXEM、轴旁中胚层 ×0.25；其余 ×1。-proxy 预期 55.97（seed 0，与 run2 的预测逐位相同）。final 读 E9.5，类型集合已含 E9.5 的名字（V-CM、Endocardium、BEC、aPHM、pPHM、Proepicardium）。diff --git a/solution/run.py b/solution/run.pyindex a752b21..edf93c4 100644--- a/solution/run.py+++ b/solution/run.py@@ -1,11 +1,5 @@ #!/usr/bin/env python3-"""heart_jcf_peri: run2's T1 winner. Reweight the latest input stage by cell type.--Neural Tube dropped; heart types (CM, endothelium/endocardium, SHF/PHM, JCF,-pericardium, proepicardium) x1.6; surface ectoderm, EXEM, paraxial mesoderm-x0.25; everything else x1. 4000 real cells, no expression shift. Proxy reads-E8.5, final reads E9.5; the type set already names both stages' labels.-"""+"""fake-25: heart_jcf_peri weights perturbed by the fake Engineer (test run)."""  from __future__ import annotations @@ -22,6 +16,8 @@ from src.task1_temporal.view_io import (     write_prediction, ) +HEART_WEIGHT = 1.6+EDGE_WEIGHT = 0.4 N_CELLS = 4000  @@ -31,12 +27,12 @@ def main() -> None:     parser.add_argument("--out", required=True)     parser.add_argument("--seed", type=int, default=0)     args = parser.parse_args()-     manifest = load_manifest(args.data)     genes = panel_genes(args.data, manifest)     last = read_stage(args.data, inputs_by_time(manifest)[-1], genes)+    pass     n = target_n_cells(manifest, N_CELLS)-    X = heart_reweight(last.X, labels_of(last), n_cells=n, seed=args.seed)+    X = heart_reweight(last.X, labels_of(last), n_cells=n, heart_weight=HEART_WEIGHT, edge_weight=EDGE_WEIGHT, seed=args.seed)     write_prediction(X, genes, args.out, seed=args.seed)  

调研来源?调研员查到并用到的知识条目和文献检索结果（只列标题和编号）。

用到的知识库条目

分析结果?分析员写的 ANALYSIS.json：改了什么、各组分数怎么变、假设是否成立、经验和下一步建议。

对话摘要?每个角色和大模型对话的统计：轮数、工具调用、用时、token 数和最后的回答摘录；原始记录只给路径。

只给统计和最后回答的摘录；完整对话请到原始记录位置里列出的文件看。

分析员

ANALYSIS.json written

工程师

wrote solution/run.py with heart x1.6, edge x0.4 (ok)

调研员

PLAN.json written