A concise quantitative method is established for identifying ‘seed’ papers in sciences. The method is set up following h-type metrics based on co-citation network analysis. With defining original-seed (O-Seed) and dominant-seed (D-Seed) by measurable h-strength and second-order h-type degree centrality, O-seed resembles to be a ‘root’ and D-seed develops to become ‘stem’. Using dataset from Web of Science (WoS), the ‘seed’ papers in research fields of graphene, genome editing, and h-set studies are identified. Graphene D-Seed paper and genome editing D-Seed paper are representative outputs of the 2010 Nobel Prize in Physics and the 2020 Nobel Prize in Chemistry respectively. H-set O-Seed and D-Seed are the same paper that first proposed the concept of h-index. The ‘seed’ papers are characterized by not only high citations, but also network structure and core function in sciences.

建立了一种简洁的定量方法来识别科学中的“种子”论文。该方法是根据h-type度量基于共引网络分析而建立的。通过可测量的h强度和二阶h型程度中心来定义原始种子（O种子）和优势种子（D种子），O种子看起来像是“根”，D种子发展为成为“干”。使用来自Web of Science（WoS）的数据集，可以识别石墨烯，基因组编辑和h-set研究领域中的“种子”论文。石墨烯D种子论文和基因组编辑D种子论文分别是2010年诺贝尔物理学奖和2020年诺贝尔化学奖的代表。H-set O-Seed和D-Seed是最早提出h-index概念的同一篇论文。“种子”论文的特点不仅在于引用率高，