【摘要】 [目的/意义]提出科技论文中科研贡献点的引用模式，细化科研贡献点的类型，旨在为科研贡献点的识别与量化评估提供可操作的结构化标准，支撑科技论文的自动化分析与评价。[方法/过程]系统梳理科研贡献的定义与分类框架，厘清科研贡献的本质特征，结合大规模英文引文语料，归纳科研贡献点在引用语句中的典型组织结构，提炼出科研贡献点的引用模式，并进一步细化模式中核心要素的分类维度。[结果/结论]构建“科研贡献点=贡献领域+创新工作+影响价值”的逻辑表达式，明确科研贡献点的核心语义组成。其中，创新工作细分为理论创新、方法创新、实践应用创新和认知创新四类，影响价值则从横向两个方面与纵向4个维度进行类型划分。此引用模式及其细化分类框架，为实现科研贡献点的自动化识别与量化评估奠定基础，并为学术评价从传统统计指标向语义分析的转型提供方法论支撑。更多还原

【Abstract】 [Purpose/Significance] This study proposes a citation pattern for identifying research contributions in scientific paper and refines its typology to offer an operational and structured classification standard. The aim is to support the automated analysis and evaluation of scientific papers and to enable the semantic-level quantification of research contributions. [Method/Process] The definitions and classification frameworks of research contributions were systematically reviewed to clarify their essential characteristics. Based on a large-scale corpus of English citation sentences, typical organizational structures of contribution expressions were identified, citation patterns were extracted, and the classification dimensions of the core elements within the pattern were further refined. [Result/Conclusion] A citation pattern for research contributions was established, formulated as: research contribution = contribution field + innovative work + influence value. Innovative work was categorized into four types: theoretical, methodological, applied, and cognitive. Influence value was classified along two horizontal dimensions and four vertical levels. The proposed citation pattern and classification framework provide a foundation for the automated identification and quantitative evaluation of research contributions and offer methodological support for advancing academic assessment from traditional bibliometric indicators to semantic-level analysis.更多还原