Ioannidis John P A, Klavans Richard, Boyack Kevin W
Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, California, United States of America.
Stanford Prevention Research Center, Department of Medicine and Department of Health Research and Policy, Stanford University School of Medicine, Stanford, California, United States of America.
PLoS Biol. 2016 Jul 1;14(7):e1002501. doi: 10.1371/journal.pbio.1002501. eCollection 2016 Jul.
Many fields face an increasing prevalence of multi-authorship, and this poses challenges in assessing citation metrics. Here, we explore multiple citation indicators that address total impact (number of citations, Hirsch H index [H]), co-authorship adjustment (Schreiber Hm index [Hm]), and author order (total citations to papers as single; single or first; or single, first, or last author). We demonstrate the correlation patterns between these indicators across 84,116 scientists (those among the top 30,000 for impact in a single year [2013] in at least one of these indicators) and separately across 12 scientific fields. Correlation patterns vary across these 12 fields. In physics, total citations are highly negatively correlated with indicators of co-authorship adjustment and of author order, while in other sciences the negative correlation is seen only for total citation impact and citations to papers as single author. We propose a composite score that sums standardized values of these six log-transformed indicators. Of the 1,000 top-ranked scientists with the composite score, only 322 are in the top 1,000 based on total citations. Many Nobel laureates and other extremely influential scientists rank among the top-1,000 with the composite indicator, but would rank much lower based on total citations. Conversely, many of the top 1,000 authors on total citations have had no single/first/last-authored cited paper. More Nobel laureates of 2011-2015 are among the top authors when authors are ranked by the composite score than by total citations, H index, or Hm index; 40/47 of these laureates are among the top 30,000 by at least one of the six indicators. We also explore the sensitivity of indicators to self-citation and alphabetic ordering of authors in papers across different scientific fields. Multiple indicators and their composite may give a more comprehensive picture of impact, although no citation indicator, single or composite, can be expected to select all the best scientists.
许多领域都面临着多作者情况日益普遍的问题，这给评估引用指标带来了挑战。在此，我们探讨了多个引用指标，这些指标涉及总影响力（引用次数、赫希H指数[H]）、共同作者调整（施赖伯Hm指数[Hm]）以及作者顺序（作为单篇论文作者的总引用次数；单篇或第一作者；或单篇、第一或最后作者）。我们展示了这些指标在84116名科学家（在这些指标中至少有一项在某一年[2013年]影响力排名前30000的科学家）之间以及在12个科学领域中各自的相关模式。这些相关模式在这12个领域中各不相同。在物理学领域，总引用次数与共同作者调整指标和作者顺序指标高度负相关，而在其他科学领域，仅在总引用影响力和作为单篇论文作者的引用次数之间存在负相关。我们提出了一个综合得分，该得分是这六个对数转换指标的标准化值之和。在综合得分排名前1000的科学家中，只有322人在基于总引用次数的前1000名中。许多诺贝尔奖获得者和其他极具影响力的科学家在综合指标中排名前1000，但基于总引用次数排名会低得多。相反，在总引用次数排名前1000的作者中，许多人没有单篇/第一/最后作者的被引用论文。当按综合得分对作者进行排名时，2011 - 2015年的更多诺贝尔奖获得者在顶级作者之列，而不是按总引用次数、H指数或Hm指数排名；这些获奖者中有40/47至少在六个指标中的一项上排名前30000。我们还探讨了不同科学领域论文中指标对自引和作者字母顺序排列的敏感性。多个指标及其综合指标可能会给出更全面的影响力图景，尽管没有任何一个引用指标（单个或综合的）能够选出所有最优秀的科学家。
