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Analysis of institutional authors

Martínez-Gramage J.Corresponding AuthorPardo Albiach, JuanAuthorAmer-Cuenca J.j.AuthorSegura-Ortí E.Author
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Article

A random forest machine learning framework to reduce running injuries in young triathletes

Publicated to:Sensors. 20 (21): 1-12 - 2020-11-01 20(21), DOI: 10.3390/s20216388

Authors: Martinez-Gramage, Javier; Pardo Albiach, Juan; Nacher Molto, Ivan; Jose Amer-Cuenca, Juan; Huesa Moreno, Vanessa; Segura-Orti, Eva

Affiliations

Federac Triatlon Comunidad Valencian, Triathlon Technificat Program, Manises 46940, Spain - Author
Triathlon Technification Program - Author
Univ Cardenal Herrera CEU, CEU Univ, Dept Physiotherapy, Valencia 46115, Spain - Author
Univ Cardenal Herrera CEU, CEU Univ, Embedded Syst & Artificial Intelligence Grp, Valencia 46115, Spain - Author
Universidad Cardenal Herrera-CEU - Author
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Abstract

Keywords
gait retrainingkinematicsAdolescentAthletesAthletic injuriesBiomechanical phenomenaElectromyographyGaitGait retrainingHumansKinematicsMachine learningRunning

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Sensors due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2020, it was in position 14/64, thus managing to position itself as a Q1 (Primer Cuartil), in the category Instruments & Instrumentation.

From a relative perspective, and based on the normalized impact indicator calculated from the Field Citation Ratio (FCR) of the Dimensions source, it yields a value of: 2.5, which indicates that, compared to works in the same discipline and in the same year of publication, it ranks as a work cited above average. (source consulted: Dimensions May 2025)

Specifically, and according to different indexing agencies, this work has accumulated citations as of 2025-05-02, the following number of citations:

  • WoS: 10
  • Scopus: 10
  • Europe PMC: 7
  • Google Scholar: 14
  • OpenCitations: 9
Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2025-05-02:

  • The use, from an academic perspective evidenced by the Altmetric agency indicator referring to aggregations made by the personal bibliographic manager Mendeley, gives us a total of: 109.
  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 109 (PlumX).

With a more dissemination-oriented intent and targeting more general audiences, we can observe other more global scores such as:

  • The Total Score from Altmetric: 9.6.
  • The number of mentions on the social network X (formerly Twitter): 12 (Altmetric).

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

  • The work has been submitted to a journal whose editorial policy allows open Open Access publication.
Leadership analysis of institutional authors

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (Martínez Gramage, Javier) and Last Author (Segura Orti, Eva).

the author responsible for correspondence tasks has been Martínez Gramage, Javier.