秩比之和：一种用于研究评估的替代百分位数方法，从突破性研究到主流研究
Sum of rank ratios: an alternative to percentiles for research assessment, from groundbreaking to mainstream research
AI总结：
本文提出了一种基于秩比之和的评估方法，用于评估推动知识边界的突破性研究，该方法通过计算论文的局部秩与全球秩的比值总和，提供了一种更有效的评估指标。
摘要：
评估推动知识边界的突破性研究具有挑战性，因为这类工作极其罕见，仅占所有研究成果的约0.01%。因此，关于如何评估此类研究的知识远不如评估更常见研究结果的已确立方法那样充分。本研究通过使用基于秩的方法来填补这一空白，其中每篇论文被赋予一个唯一的值，等于其局部秩与全球秩的比值。这些比值的累积值，从被引次数最多的论文开始，提供了评估的基础。本文描述的Rn指数使用10个秩比，似乎是最优选项。尽管基于全球秩的研究评估最初是为评估对突破性知识做出最大贡献的国家（如美国和中国）而开发的，但Rn指数有更广泛的应用。本研究证明，Rn指数比使用前10%或前1%的高被引论文数量等最常用的指标更优，这些指标常用于评估很少或从未产生突破性研究的国家。在所有情况下，Rn指数反映了每个国家所生产的最高质量科学。此外，Rn指数可以轻松计算，无需专门的文献计量学培训，并且不受引用次数平局的影响。
英文摘要：
Assessing research that pushes the boundaries of knowledge is challenging because such work is extremely infrequent, accounting for only about 0.01 per cent of all research outputs. Consequently, knowledge about how to evaluate this type of research is far more limited than the well established methods used to assess more common research outcomes. This study addresses this gap by using a rank based approach in which each paper is assigned a unique value equal to the ratio between its local and global ranks. The cumulative value of these ratios, starting from the most cited paper, provides the evaluative basis, and the Rn index described here, using 10 rank ratios, appears to be the best option. Although research assessment based on global ranks was originally developed to evaluate the largest contributors to groundbreaking knowledge, namely, the USA and China, which account for most of the most cited papers, the Rn index has broader applications. This study demonstrates that it is also a better option than the number of top 10 per cent or top 1per cent highly cited papers, which are the most common indicators used to evaluate countries that seldom or never produce cutting-edge research that pushes the boundaries of knowledge. In all cases, the Rn index reflects the highest quality science produced by each country. Furthermore, the Rn index can be easily calculated without specialized training in bibliometrics and is insignificantly affected by ties in citation counts.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
