Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
This map shows the geographic impact of Pablo Moscato'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 Pablo Moscato with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pablo Moscato more than expected).
This network shows the impact of papers produced by Pablo Moscato. 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 Pablo Moscato. The network helps show where Pablo Moscato may publish in the future.
Co-authorship network of co-authors of Pablo Moscato
This figure shows the co-authorship network connecting the top 25 collaborators of Pablo Moscato.
A scholar is included among the top collaborators of Pablo Moscato 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 Pablo Moscato. Pablo Moscato is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Berretta, Regina, et al.. (2015). FSMEC: a feature selection method based on the minimum spanning tree and evolutionary computation. 129–139.2 indexed citations
Mathieson, Luke, Alexandre Mendes, J. Marsden, James Pond, & Pablo Moscato. (2004). Computer-aided Breast Cancer Diagnosis with Optimal Feature Sets: Application of Safe Reduction Rules and Optimization Techniques.1 indexed citations
13.
Moscato, Pablo & Carlos Cotta. (2003). Una Introducción a los Algoritmos Memeticos. Redalyc (Universidad Autónoma del Estado de México). 7(19). 131–148.10 indexed citations
Mendes, Alexandre, et al.. (2001). NP-Opt: an optimization framework for NP problems. American Journal of Obstetrics and Gynecology. 137(6). 746–7.4 indexed citations
16.
Moscato, Pablo, et al.. (1999). Memetic algorithms using guided local search: a case study. 235–244.16 indexed citations
17.
Moscato, Pablo. (1999). Memetic algorithms: a short introduction. 219–234.277 indexed citations
18.
Durán, Guillermo, et al.. (1999). On worst-case and comparative analysis as design principles for efficient recombination operators: a graph colouring case study. 279–294.2 indexed citations
Moscato, Pablo, et al.. (1995). Arbitrarily Large Planar Etsp Instances With Known Optimal Tours.2 indexed 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.