Citation metrics are the best tools for research assessments. However, current metrics are misleading in research systems that pursue simultaneously different goals, such as the advance of science and incremental innovations, because their publications have different citation distributions. We estimate the contribution to the progress of knowledge by studying only a limited number of the most cited papers, which are dominated by publications pursuing this progress. To field-normalize the metrics, we substitute the number of citations by the rank position of papers from one country in the global list of papers. Using synthetic series of lognormally distributed numbers, we developed the Rk-index, which is calculated from the global ranks of the 10 highest numbers in each series, and demonstrate its equivalence to the number of papers in top percentiles, P top 0.1% and P top 0.01% . In real cases, the Rk-index is simple and easy to calculate, and evaluates the contribution to the progress of knowledge much better than commonly used metrics. Although further research is needed, rank analysis of the most cited papers is a promising approach for research evaluation. It is also demonstrated that, for this purpose, domestic and collaborative papers should be studied independently.

翻译：引文指标是科研评估的最佳工具。然而，在同时追求多种目标（如科学进步与渐进式创新）的科研体系中，当前的指标具有误导性，因为这些体系的论文具有不同的引文分布。通过仅研究有限数量的被引最高论文——这些论文主要由追求知识进步的出版物主导——我们估算了其对知识进步的贡献。为对指标进行领域归一化，我们用论文在各国全球论文列表中的排名位置替代引文数量。利用对数正态分布数的合成序列，我们提出了Rk指数，该指数由每个序列中10个最高值的全球排名计算得出，并证明了其与顶级百分比论文数（前0.1%和前0.01%）的等效性。在实际案例中，Rk指数简单易算，且对知识进步贡献的评估远优于常用指标。尽管仍需进一步研究，但被引最高论文的排名分析是一种有前景的科研评估方法。此外，研究表明，出于此目的，国内论文与合作论文应分别独立研究。