<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>0187-358X</journal-id>
<journal-title><![CDATA[Investigación bibliotecológica]]></journal-title>
<abbrev-journal-title><![CDATA[Investig. bibl]]></abbrev-journal-title>
<issn>0187-358X</issn>
<publisher>
<publisher-name><![CDATA[Universidad Nacional Autónoma de México, Instituto de Investigaciones Bibliotecológicas y de la Información]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0187-358X2024000200089</article-id>
<article-id pub-id-type="doi">10.22201/iibi.24488321xe.2024.99.58857</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Factores asociados a la citación de artículos biomédicos colombianos: análisis con Machine Learning]]></article-title>
<article-title xml:lang="en"><![CDATA[Factors Associated with Citation of Colombian Biomedical Articles: Analysis with Machine Learning]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Sánchez-Bello]]></surname>
<given-names><![CDATA[Nubia Fernanda]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Mejía Quiroga]]></surname>
<given-names><![CDATA[Jorge Enrique]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Pérez-Martelo]]></surname>
<given-names><![CDATA[Constanza Beatriz]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Central Facultad de Ingeniería y Ciencias Básicas ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Colombia</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidad Central Facultad de Ingeniería y Ciencias Básicas ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Colombia</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>06</month>
<year>2024</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>06</month>
<year>2024</year>
</pub-date>
<volume>38</volume>
<numero>99</numero>
<fpage>89</fpage>
<lpage>107</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S0187-358X2024000200089&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S0187-358X2024000200089&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S0187-358X2024000200089&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen Los indicadores de citación pueden medir el impacto o la utilidad de resultados de investigación de un artículo científico, sin embargo, este uso puede ser controversial. Factores intrínsecos y extrínsecos influencian la citación de un artículo, sin mencionar que el comportamiento en las citaciones puede variar entre áreas temáticas, lo cual dificulta las comparaciones entre artículos y disciplinas. Entender que el contexto puede afectar un análisis de citas es esencial para interpretar adecuadamente los indicadores. Por esta razón, buscan reconocerse los factores que inciden en la citación de los artículos de las revistas biomédicas colombianas indexadas en Scopus a través del uso de algoritmos de Machine Learning. Con los algoritmos 'Gradient Boosting Classifier" y 'Light Gradient Boosting Machine' identificamos características de importancia como el índice h del primer y el último autor, acceso abierto, número de autores, palabras clave del artículo, además del número de páginas. Estas características fueron relevantes para el área de interés y pueden brindar un contexto para futuros análisis, considerando que lo relevante de un artículo no debería ser cuántas citaciones atrae, sino si este ayuda a llenar vacíos en el conocimiento.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract Citation indicators can be used to measure the impact or usefulness of research results in a scientific article; however, this usage can be controversial. Intrinsic and extrinsic factors influence the citation of an article, not to mention that citation behavior can differ between thematic areas, which hinders the comparison between articles and disciplines. Understanding that context can affect citation analysis is essential to interpret indicators properly; for this reason, we want to recognize the factors that influence the citation of Colombian biomedical journals indexed in Scopus using Machine Learning algorithms. With 'Gradient Boosting Classifier" and 'Light Gradient Boosting Machine' algorithms, we find characteristics of importance such as the h-index of the first and last author, open access, number of authors and keywords of the article, in addition to identifying the number of pages. These characteristics are relevant to the area of interest and can provide context for future analyses, always considering that what should be relevant about an article is not how many citations it attracts but whether it helps to fill gaps in knowledge.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[Análisis de citas]]></kwd>
<kwd lng="es"><![CDATA[Aprendizaje automático]]></kwd>
<kwd lng="es"><![CDATA[Investigación biomédica]]></kwd>
<kwd lng="es"><![CDATA[Colombia]]></kwd>
<kwd lng="en"><![CDATA[Citation Analysis]]></kwd>
<kwd lng="en"><![CDATA[Machine Learning]]></kwd>
<kwd lng="en"><![CDATA[Biomedical Research]]></kwd>
<kwd lng="en"><![CDATA[Colombia]]></kwd>
</kwd-group>
</article-meta>
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