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Article-level metrics are citation metrics which measure the usage and impact of individual scholarly articles. The most common article-level citation metric is the number of citations. [ 1 ] Field-weighted Citation Impact (FWCI) by Scopus divides the total citations by the average number of citations for an article in the scientific field .
The SJR indicator is a free journal metric inspired by, and using an algorithm similar to, PageRank. The SJR indicator computation is carried out using an iterative algorithm that distributes prestige values among the journals until a steady-state solution is reached.
In any given year, the CiteScore of a journal is the number of citations, received in that year and in previous three years, for documents published in the journal during the total period (four years), divided by the total number of published documents (articles, reviews, conference papers, book chapters, and data papers) in the journal during the same four-year period: [3]
Indexing and classification methods to assist with information retrieval have a long history dating back to the earliest libraries and collections however systematic evaluation of their effectiveness began in earnest in the 1950s with the rapid expansion in research production across military, government and education and the introduction of computerised catalogues.
Bibliometrics is the application of statistical methods to the study of bibliographic data, especially in scientific and library and information science contexts, and is closely associated with scientometrics (the analysis of scientific metrics and indicators) to the point that both fields largely overlap.
Journal Citation Reports (JCR) is an annual publication by Clarivate. [1] It has been integrated with the Web of Science and is accessed from the Web of Science Core Collection . It provides information about academic journals in the natural and social sciences , including impact factors .
scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language. [3] It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific ...
The g-index is an author-level metric suggested in 2006 by Leo Egghe. [1] The index is calculated based on the distribution of citations received by a given researcher's publications, such that given a set of articles ranked in decreasing order of the number of citations that they received, the g-index is the unique largest number such that the top g articles received together at least g 2 ...