Judging value of scholarly outputs quantitatively remains a difficult but unavoidable challenge. Most of the proposed solutions suffer from three fundamental shortcomings: they involve i) the concept of journal, in one way or another, ii) calculating arithmetic averages from extremely skewed distributions, and iii) binning data by calendar year. Here, we introduce a new metric Co-citation Percentile Rank (CPR), that relates the current citation rate of the target output taken at resolution of days since first citable, to the distribution of current citation rates of outputs in its co-citation set, as its percentile rank in that set. We explore some of its properties with an example dataset of all scholarly outputs from University of Jyväskylä spanning multiple years and disciplines. We also demonstrate how CPR can be efficiently implemented with Dimensions database API, and provide a publicly available web resource JYUcite, allowing anyone to retrieve CPR value for any output that has a DOI and is indexed in the Dimensions database. Finally, we discuss how CPR remedies failures of the Relative Citation Ratio (RCR), and remaining issues in situations where CPR too could potentially lead to biased judgement of value.

中文翻译：

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共引百分等级和JYUcite：一种新的网络标准化的输出水平引文影响指标及其使用Dimensions API的实现

从数量上判断学术产出的价值仍然是一个困难但不可避免的挑战。大部分建议的解决方案都具有三个基本缺陷：i）以一种或另一种方式记录日记的概念； ii）从极度偏斜的分布计算算术平均值，以及iii）按日历年度对数据进行分箱。在这里，我们引入了一个新的度量共引用百分比等级（CPR），它将目标输出的当前引用率（自第一个引用之日起的分辨率）与它的共引用集中的当前输出引用率的分布相关联，作为其在该组中的百分等级。我们通过一个跨年度和跨学科的于韦斯屈莱大学的所有学术成果的示例数据集来探索其某些属性。我们还将演示如何使用Dimensions数据库API有效地实现CPR，并提供一个公开可用的Web资源JYUcite，允许任何人检索具有DOI并在Dimensions数据库中建立索引的任何输出的CPR值。最后，我们讨论了心肺复苏如何纠正相对引用比率（RCR）的失败以及在心肺复苏也可能导致价值判断有偏差的情况下仍然存在的问题。