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      Preprints and preprint servers as academic communication tools Translated title: Preprints y servidores de preprints como herramientas para la comunicación académica

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          ABSTRACT Preprints and preprint servers comprise the articulation of the ultimate and most proximal node to publishing the scientific results in academic journals. Therefore, in this review, the concept, development, advantages and limitations of preprints and preprint servers are analyzed, attending to their main function as publicly available repositories of manuscripts on the way to getting published. Moreover, an analysis of the motor forces contributing to their establishment to communicate research results among scientific communities is given, with their classification (journal, non-journal and mixed servers; subject repositories), as well as debate on the most successful (arXiv) and debated (Biology, Chemistry) servers, preprint formats, and their relationship with information phenomena such as open access, open archiving, digital information certification, information retrieval, and the added value through immediacy in availability and citation in comparison with published articles. Examples of their integration with ongoing communicational processes are discussed, such as migration of editors from journals to preprint servers to channel up manuscripts, open peer review strategies and scientific community engagement. A list of the most relevant preprint servers until 2018, their characteristics, general stats of their preprints and citation counts in Scopus is included.

          Translated abstract

          RESUMEN Los manuscritos pre-publicación (o preprints) articulan el último eslabón previo y más próximo a la publicación de los resultados investigativos en las revistas académicas. En este artículo de revisión se analiza el concepto, el desarrollo, las ventajas y las limitaciones de los preprints y los servidores de preprints. Esto atendiendo a su función principal como repositorios públicos disponibles de manuscritos en vías de publicación. Además, se abunda sobre los motivos de su surgimiento y de su establecimiento para la comunicación de los resultados de investigación entre comunidades científicas, su clasificación (servidores de revistas científicas, no asociados a revistas científicas y servidores mixtos; repositorios temáticos). Se incluyen los debates sobre el servidor más famoso, arXiv, y los más debatidos en Biología (biorXiv) y en Química; sobre los formatos de los preprints y su interrelación con los fenómenos informacionales del acceso abierto, el archivo abierto, la certificación de información digital, la recuperación de información y el valor agregado de la inmediatez de disponibilidad y citación en comparación con los artículos publicados. También se incluyen elementos sobre su integración con los procesos comunicacionales en ejecución, entre ellos la migración de editores de las revistas a los servidores de preprints para canalizarlos hacia la publicación final, las estrategias de evaluación por pares abierta y la vinculación con las comunidades científicas. Se incluye además una lista de los servidores de preprints posicionados hasta el año 2018, con la citación de sus preprints en la base de datos Scopus, así como algunas de sus características.

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          Most cited references 63

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          Does it take too long to publish research?

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            Efficient discovery of overlapping communities in massive networks.

            Detecting overlapping communities is essential to analyzing and exploring natural networks such as social networks, biological networks, and citation networks. However, most existing approaches do not scale to the size of networks that we regularly observe in the real world. In this paper, we develop a scalable approach to community detection that discovers overlapping communities in massive real-world networks. Our approach is based on a Bayesian model of networks that allows nodes to participate in multiple communities, and a corresponding algorithm that naturally interleaves subsampling from the network and updating an estimate of its communities. We demonstrate how we can discover the hidden community structure of several real-world networks, including 3.7 million US patents, 575,000 physics articles from the arXiv preprint server, and 875,000 connected Web pages from the Internet. Furthermore, we demonstrate on large simulated networks that our algorithm accurately discovers the true community structure. This paper opens the door to using sophisticated statistical models to analyze massive networks.
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              Rising Publication Delays Inflate Journal Impact Factors

              Journal impact factors have become an important criterion to judge the quality of scientific publications over the years, influencing the evaluation of institutions and individual researchers worldwide. However, they are also subject to a number of criticisms. Here we point out that the calculation of a journal’s impact factor is mainly based on the date of publication of its articles in print form, despite the fact that most journals now make their articles available online before that date. We analyze 61 neuroscience journals and show that delays between online and print publication of articles increased steadily over the last decade. Importantly, such a practice varies widely among journals, as some of them have no delays, while for others this period is longer than a year. Using a modified impact factor based on online rather than print publication dates, we demonstrate that online-to-print delays can artificially raise a journal’s impact factor, and that this inflation is greater for longer publication lags. We also show that correcting the effect of publication delay on impact factors changes journal rankings based on this metric. We thus suggest that indexing of articles in citation databases and calculation of citation metrics should be based on the date of an article’s online appearance, rather than on that of its publication in print.

                Author and article information

                Revista Cubana de Información en Ciencias de la Salud
                Rev. cuba. inf. cienc. salud
                Editorial Ciencias Médicas (La Habana, , Cuba )
                March 2019
                : 30
                : 1
                La Habana orgnameCenter for Genetic Engineering and Biotechnology orgdiv1Elfos Scientiae Publisher Cuba
                S2307-21132019000100008 S2307-2113(19)03000100008

                This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

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