Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if any of the following hold:
it has ≥500 total citations;
it reaches ≥1.5× the top-1% citation threshold for papers in the same subfield and year (the
threshold is the minimum needed to enter the top 1%, not the average within it);
it reaches the top citation threshold in at least one of its specific research topics.
Countries citing papers authored by Raphael Labaca-Castro
Since Specialization
Citations
This map shows the geographic impact of Raphael Labaca-Castro'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 Raphael Labaca-Castro with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Raphael Labaca-Castro more than expected).
Fields of papers citing papers by Raphael Labaca-Castro
This network shows the impact of papers produced by Raphael Labaca-Castro. 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 Raphael Labaca-Castro. The network helps show where Raphael Labaca-Castro may publish in the future.
Raphael Labaca-Castro is a scholar working on Computer Networks and Communications, Signal Processing, Artificial Intelligence, Management Science and Operations Research and Economics and Econometrics, having authored 2 papers that have together received 4.3k indexed citations. Recurring topics across this work include Sports Analytics and Performance (1 paper), Advanced Malware Detection Techniques (1 paper), Forecasting Techniques and Applications (1 paper), Network Security and Intrusion Detection (1 paper) and Explainable Artificial Intelligence (XAI) (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (2.0k citations), Computer Graphics and Computer-Aided Design (170 citations), Artificial Intelligence (1.5k citations), Media Technology (348 citations) and Health Informatics (51 citations).
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.