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PNAS Article and Journal Metrics

Many metrics, largely citation-based, exist or are being developed to measure the impact of journals and journal articles. Article-level metrics data and article downloads are available for all PNAS articles. Click on the “Metrics” tab of a PNAS article to see its “Online Impact” (Altmetric score) and “Article Usage” (downloads of the abstract, full text, and PDF).

Article-level metrics measure the reach and impact of an article by tracking the mentions it receives online. The Metrics tab provides a summary of mentions of the article across news sites, blogs, social media, and other online sources—which are visualized in a colorful icon, or “badge.” The number in the middle of the badge is the Altmetric score, which is based on the volume, type, and author of the mentions. Article downloads by month and by article format appear below. Users can click on the badge or “See more details” to explore the individual mentions from each source in detail.

Below are some other metrics for PNAS.

Impact Factor, Immediacy Index, Cited Half-Life, and Citation Distribution

2016 rankings, Journal Citation Reports (Thomson Reuters)

Impact factor


5-Year impact factor

Total cites

Immediacy index

Cited half-life


4/64 in “Multidisciplinary”





Impact factor: a measure of the frequency with which the “average article” in a journal has been cited in a particular year or period. The journal impact factor is calculated by dividing the number of current year citations to source items published in that journal during the previous 2 years.

Immediacy index: the average number of times an article is cited in the year it is published.

Cited half-life: the number of years, going back from the current Journal Citation Reports (JCR) year, that account for 50% of citations received by the journal in the current JCR year.

Citation distribution: the distribution of citations to articles over the previous 2 years that contributes to the current JCR year’s impact factor.

See “A simple proposal for the publication of journal citation distributions,” by Vincent Lariviere, Veronique Kiermer, Catriona J MacCallum, Marcia McNutt, Mark Patterson, Bernd Pulverer, Sowmya Swaminathan, Stuart Taylor, and Stephen Curry. BioRxiv. Posted July 5, 2016. http://www.danielhellerman.com/10.1101/062109.

Eigenfactor and Article Influence

2015 rankings



Article Influence



3/63 in “Multidisciplinary Sciences”


5/63 in “Multidisciplinary Sciences”

Eigenfactor: a measure of the journal’s total importance to the scientific community. The Eigenfactor estimates the percentage of time that a reader spends with a particular journal and is calculated using Thomson Reuters data in a model in which readers follow chains of citations as they move from journal to journal. It ignores self-citations. Eigenfactors are scaled so that the Eigenfactor scores of all journals listed in the JCR sum to 100. Thus, if a journal has an Eigenfactor of 1.0, it has 1% of the total influence of all indexed publications.

Article Influence: a measure of the average influence of each of a journal’s articles over the first 5 years after publication. Article Influence scores are normalized so that the mean article in the entire JCR database has an Article Influence of 1.00. For 2015, the PNAS Article Influence score is 4.691, which means that the average article in PNAS has 4.691 times the influence of the mean article in the JCR.

Scopus Metrics: CiteScore, SJR, IPP, and SNIP

2016 rankings


CiteScore Percentile

CiteScore Rank



3 of 77 in “Multidisciplinary”







CiteScore: CiteScore counts the citations received in 2015 to documents published in 2012, 2013, or 2014, and divides this by the number of documents published in 2012, 2013, and 2014. CiteScore’s numerator and denominator both include all document types. This includes articles and reviews, as well as letters, notes, editorials, conference papers, and other types indexed by Scopus. PNAS CiteScore Percentile = 97th, which means that PNAS is in the top 3% of multidisciplinary journals.

SCImago Journal Rank (SJR): is based on the Scopus dataset and is a prestige metric based on the idea that not all citations are the same. With SJR, the subject field, quality, and reputation of the journal have a direct effect on the value of a citation and the impact that the journal makes. In addition the prestige of a citation is weighted over all citations handed out to that journal. SJR is a size-independent indicator and it ranks journals by their “average prestige per article” and can be used for journal comparisons in science evaluation processes. It expresses the average number of weighted citations received in the selected year by the documents published in the selected journal in the 3 previous years (i.e., weighted citations received in year X to documents published in the journal in years X-1, X-2 and X-3).

Impact per Publication (IPP): measures the ratio of citations in year Y to scholarly papers published in the 3 previous years (Y-1, Y-2, Y-3) divided by the number of scholarly papers published in those same years (Y-1, Y-2, Y-3). The IPP uses a citation window of 3 years, which is considered to be the optimal time period to accurately measure citations in most subject fields. Taking into account the same peer-reviewed scholarly papers only in both the numerator and denominator of the equation provides a fair impact measurement of the journal and diminishes the chance of manipulation.

Source Normalized Impact per Paper (SNIP): measures a source’s contextual citation impact. It takes into account characteristics of the source’s subject field, especially the frequency at which authors cite other papers in their reference lists, the speed at which citation impact matures, and the extent to which the database used in the assessment covers the field’s literature. SNIP is the ratio of a source’s average citation count per paper, and the “citation potential” of its subject field. It aims to allow direct comparison of sources in different subject fields. A source’s subject field is the set of documents citing that source. The citation potential of a source’s subject field is the average number of references per document citing that source. It represents the likelihood of being cited for documents in a particular field. A source in a field with a high citation potential will tend to have a high impact per paper.

Google Scholar Metrics: h-5 Index and h-5 Median

h-5 Index

h-5 Median








h-Index: the largest number h such that at least h articles in a publication were cited at least h times each. For example, a sample publication with five articles cited by, respectively, 17, 9, 6, 3, and 2, has the h-index of 3.

h-Core: a set of top-cited h articles from a publication. These are the articles that the h-index is based on. For example, the sample publication above has the h-core with three articles, those cited by 17, 9, and 6.

h-Median: the median of the citation counts in a publication’s h-core. For example, the h-median of the sample publication above is 9. The h-median is a measure of the distribution of citations to the articles in the h-core.

The h5-index, h5-core, and h5-median of a publication are, respectively, the h-index, h-core, and h-median of only those of its articles that were published in the last 5 complete calendar years.

Google Scholar displays the h5-index and the h5-median for PNAS, as well as the entire h5-core of PNAS articles, along with their citation counts, so that you can see which articles contribute to the PNAS h5-index. Click on the citation count for any article in the PNAS h5-core to see who cited it.


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