百分位数等级评分计算中分数评分相关性的经验证据
Empirical Evidence for the Relevance of Fractional Scoring in the Calculation of Percentile Rank Scores
摘要：
分数评分已被提出，以避免不一致的归属出版物的百分位等级类。百分位数等级评价中的不确定性和模糊性可以用小数据集最容易地证明。但是对于较大的数据集，通常大量具有相同引用计数的论文会导致相同的不确定性和模糊性，这可以通过分数评分来避免。这是证明了四个不同的经验数据集与几千个出版物，每个被分配到6个百分位数的排名类。只有通过分数评分，所有论文的总分才能准确地再现每种情况下的理论值。
英文摘要：
Fractional scoring has been proposed to avoid inconsistencies in the attribution of publications to percentile rank classes. Uncertainties and ambiguities in the evaluation of percentile ranks can be demonstrated most easily with small datasets. But for larger datasets an often large number of papers with the same citation count leads to the same uncertainties and ambiguities which can be avoided by fractional scoring. This is demonstrated for four different empirical datasets with several thousand publications each which are assigned to 6 percentile rank classes. Only by utilizing fractional scoring the total score of all papers exactly reproduces the theoretical value in each case.
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。
