Another bibliometric index (c-index) is presented which quantifies the scholarly output of a researcher or a source based on the quantity and quality of the received citations [12]. The authors have described the quality of a citation as the collaboration distance between the citing and the cited authors. Although there is no standard norm of assigning credits to coauthors in respect of authors sequence, the generally adopted trend is that the coauthors appear in the sequence of a decreasing level of contribution. Such a norm is called a \"sequence-determines-credit (SDC)\" approach [13]. Thus, the coauthor appearing at the third position is supposed to have contributed more than the coauthor appearing at the fourth position. The other less commonly used norms are \"equal-contribution (EC)\", \"first-last-author-emphasis\", and \"percent-contribution-indicated\" norms. The percent-contribution-indicated norm, also known as \"author contribution details\", should be prioritized over the SDC approach in order to get a truer picture [14]. Unfortunately, not many journals publish author contribution details, which renders this approach unworkable. [PERSON] et al. have presented a review of different credit assignment schemes proposed by various researchers for quantifying a researcher's output in multiple author publications [15]. Based on the review, the authors have classified the schemes into the following three categories: linear, curve, and other. [PERSON] has proposed the application of harmonic counting for an equity-based distribution of the publication credit among the coauthors [16]. The author has claimed superiority of this method over similar approaches, such as fractional counting, geometric counting, and arithmetic counting. For example, it is claimed, in respect of arithmetic counting, that the credit of the former last coauthor is initially increased by adding more coauthors, thus undermining the effectiveness of the approach. However, the claim will be refuted in this work. A network-based method is also presented for distribution of the publication credit among the coauthors [17]. The method visualizes coauthorship as a directed, weighted network, where coauthors transfer credit shares among one another. The authors have claimed to have empirically validated the approach by fitting it to the data regarding credit shares from various research fields. A source-level scientometric index, impact factor (IF), is defined as the average number of citations received per year by articles published in an academic journal in the last two years [18; 19]. For instance, the IF of a journal reported in the year 2020 is equal to the total number of citations received by it in 2020 divided by the total number of articles published in years 2018 and 2019. Used as a yardstick by institutes and funding bodies for measuring the quality of researchers' scholarly outputs and deciding on research proposals and associated grants, the metric has been criticized for distorting ethical research practices [20; 21]. The author-level metric, h-index, and the journal-level metric, IF, are, for obvious reasons, positively correlated. A higher number of citations received by an article would not only increase the h-index of the author/coauthors but also contribute positively toward enhancing the IF of the journal. As far as the association between the journal-level h-index and IF is concerned, however, it has been shown that the level of correlation varies from journal to journal [22]. The brief review of the literature provided above uncovers a significant research gap available. A robust method is required to justly quantify the scholarly impacts of researchers by considering the number of coauthors, the sequence number of the researcher in the authors list, and the time elapsed after the date of publication of their articles. The work presented here employs the concept of arithmetic series to work out a mathematical model for impartial and reasonable calculations of the researchers' scholarly impacts.