Various multi-authorship indices have been proposed in the literature, however, there is a continuous discussion in the scientific community which multi-authorship index performs better for the ranking of authors. So far, multi-authorship indices are assessed on very small datasets mostly single authors or the publication record of less than 10 authors. Furthermore, the indices are evaluated on different datasets, making it difficult to assess the true contribution and importance of each multi-authorship index over the others. To identify the individual performance of each multi-authorship index, we employ a comprehensive dataset of Civil Engineering domain, rank the authors according to each index and calculate the correlation between the ranked lists obtained by these indices. It is found that the correlation values vary between very strong correlation and very weak correlation and the negative correlation also exists between some of the indices. Secondly, to evaluate the ranking, the occurrence of award winners is found in the author ranked lists of these indices. The award winners of four most renowned societies of Civil Engineering were considered as benchmark. In top 10% of the ranked list, g_f-index remained successful in bringing most of the awardees i.e. around 67% of total awardees. Overall, none of the multi-authorship index remained successful in bringing 100% of award winners in the list of top ranked authors.

文献中已经提出了多种多作者指数，但是，科学界一直在讨论哪种多作者指数对作者排名有更好的影响。到目前为止，多作者索引是根据非常小的数据集（主要是单作者或少于10位作者的出版记录）进行评估的。此外，这些索引是在不同的数据集上进行评估的，因此很难评估每个多作者索引在其他方面的真实贡献和重要性。为了确定每个多作者索引的个人表现，我们使用了土木工程领域的综合数据集，根据每个索引对作者进行排名，并计算由这些索引获得的排名列表之间的相关性。发现相关值在非常强的相关性和非常弱的相关性之间变化，并且在一些指标之间也存在负相关性。其次，要评估排名，可以在这些指数的作者排名列表中找到获奖者的出现。四个最著名的土木工程学会的获奖者被视为基准。在排名的前10％中，g _f指数仍然成功吸引了大多数获奖者，即约67％的获奖者。总体而言，没有一项多作者索引能够成功地将100％的获奖者带入排名最高的作者名单。