Citation metrics are the best tools for research assessments. However, current metrics may be misleading in research systems that pursue simultaneously different goals, such as to push the boundaries of knowledge or 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, simulating citations, we developed the 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 and P. In real cases, the index is simple and easy to calculate, and evaluates the contribution to the progress of knowledge better than less stringent 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.

中文翻译：

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最受引用出版物的排名分析，研究评估的新方法

引文指标是研究评估的最佳工具。然而，当前的指标可能会在同时追求不同目标的研究系统中产生误导，例如突破知识的界限或渐进式创新，因为它们的出版物具有不同的引用分布。我们通过仅研究有限数量的被引用最多的论文来估计对知识进步的贡献，这些论文主要由追求这一进步的出版物主导。为了对指标进行字段标准化，我们用一个国家的论文在全球论文列表中的排名位置代替引用次数。使用对数正态分布数字的合成系列，模拟引用，我们开发了该指数，该指数是根据每个系列中前 10 个最高数字的全球排名计算得出的，并证明了其与最高百分位数 P 和 P 中的论文数量的等价性。真实案例中，该指标简单易算，比不太严格的指标更好地评估对知识进步的贡献。尽管还需要进一步的研究，但对被引用次数最多的论文进行排名分析是一种很有前途的研究评估方法。还表明，为此目的，国内论文和合作论文应该独立研究。