Matías Gámez

56 total papers · 1.0k total citations
35 papers, 736 citations indexed

About

Matías Gámez is a scholar working on Economics and Econometrics, Artificial Intelligence and Management Science and Operations Research. According to data from OpenAlex, Matías Gámez has authored 35 papers receiving a total of 736 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Economics and Econometrics, 9 papers in Artificial Intelligence and 5 papers in Management Science and Operations Research. Recurrent topics in Matías Gámez's work include Market Dynamics and Volatility (6 papers), Housing Market and Economics (6 papers) and Imbalanced Data Classification Techniques (5 papers). Matías Gámez is often cited by papers focused on Market Dynamics and Volatility (6 papers), Housing Market and Economics (6 papers) and Imbalanced Data Classification Techniques (5 papers). Matías Gámez collaborates with scholars based in Spain, India and United Kingdom. Matías Gámez's co-authors include Noelia García, Esteban Alfaro, David Elizondo, Indranil Ghosh, José Luis Alfaro Navarro, José‐María Montero, Beatriz Larraz, Tamal Datta Chaudhuri, Emilio L. Cano and Silvia Casado and has published in prestigious journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and Technological Forecasting and Social Change.

In The Last Decade

Matías Gámez

34 papers receiving 689 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Matías Gámez 266 210 175 127 103 35 736
Noelia García 267 1.0× 210 1.0× 179 1.0× 127 1.0× 103 1.0× 42 908
Esteban Alfaro 274 1.0× 236 1.1× 199 1.1× 136 1.1× 112 1.1× 39 806
María Óskarsdóttir 268 1.0× 209 1.0× 78 0.4× 58 0.5× 97 0.9× 49 849
Baofeng Shi 143 0.5× 237 1.1× 299 1.7× 80 0.6× 132 1.3× 45 909
Cuicui Luo 146 0.5× 149 0.7× 151 0.9× 137 1.1× 68 0.7× 42 661
Javier Arroyo 263 1.0× 100 0.5× 173 1.0× 248 2.0× 102 1.0× 40 906
Marijana Zekić–Sušac 190 0.7× 135 0.6× 80 0.5× 102 0.8× 57 0.6× 34 691
Barbro Back 326 1.2× 327 1.6× 94 0.5× 208 1.6× 124 1.2× 39 759
Flávio Barboza 269 1.0× 485 2.3× 147 0.8× 130 1.0× 240 2.3× 26 790
Pedro Carmona 149 0.6× 420 2.0× 159 0.9× 87 0.7× 148 1.4× 52 858

Countries citing papers authored by Matías Gámez

Since Specialization
Citations

This map shows the geographic impact of Matías Gámez's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Matías Gámez with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matías Gámez more than expected).

Fields of papers citing papers by Matías Gámez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matías Gámez. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Matías Gámez. The network helps show where Matías Gámez may publish in the future.

Co-authorship network of co-authors of Matías Gámez

This figure shows the co-authorship network connecting the top 25 collaborators of Matías Gámez. A scholar is included among the top collaborators of Matías Gámez based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Matías Gámez. Matías Gámez is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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