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.
GPR monitoring for road transport infrastructure: A systematic review and machine learning insights
2022112 citationsMezgeen Rasol, Jorge C. Pais et al.Construction and Building Materialsprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Jorge C. Pais'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 Jorge C. Pais with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jorge C. Pais more than expected).
This network shows the impact of papers produced by Jorge C. Pais. 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 Jorge C. Pais. The network helps show where Jorge C. Pais may publish in the future.
Co-authorship network of co-authors of Jorge C. Pais
This figure shows the co-authorship network connecting the top 25 collaborators of Jorge C. Pais.
A scholar is included among the top collaborators of Jorge C. Pais 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 Jorge C. Pais. Jorge C. Pais is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Rasol, Mezgeen, Jorge C. Pais, Vega Pérez‐Gracia, et al.. (2022). GPR monitoring for road transport infrastructure: A systematic review and machine learning insights. Construction and Building Materials. 324. 126686–126686.112 indexed citations breakdown →
Trichês, Glicério, et al.. (2008). Comparison between asphalt rubber and conventional mixtures in overlay design. RepositóriUM (Universidade do Minho).2 indexed citations
12.
Pereirâ, Paulo A. A., Jorge C. Pais, Elisabete F. Freitas, Hugo Manuel Ribeiro Dias da Silva, & Joel Oliveira. (2007). The road network rehabilitation for the 21st century: a global vision on innovation in road rehabilitation. RepositóriUM (Universidade do Minho). 3(1).1 indexed citations
13.
Trichês, Glicério, et al.. (2007). Desempenho de misturas betuminosas com betume modificado com borracha através do processo húmido. RepositóriUM (Universidade do Minho). 67(5). 182–5.1 indexed citations
Pais, Jorge C., et al.. (2002). VARIABILITY OF LABORATORY FATIGUE LIFE OF BITUMINOUS MIXTURES USING FOUR POINT BENDING TEST RESULTS. 1(2).1 indexed citations
16.
Sousa, Jorge B., et al.. (2002). Development of a mechanistic-empirical based overlay design method for reflective cracking. Transportation Research Record Journal of the Transportation Research Board. 209–217.15 indexed citations
Pereirâ, Paulo A. A., Jorge C. Pais, & Jorge B. Sousa. (2000). MODELLING THE EFFECT OF TRUCK SPEED ON PERMANENT DEFORMATION OF ASPHALT MIXES. Road Materials and Pavement Design. 1(2).1 indexed citations
19.
Pereirâ, Paulo A. A., Jorge C. Pais, & Jorge B. Sousa. (1999). Modeling the effect of truck speed on permanent deformation of asphalt concrete mixes. Road Materials and Pavement Design. 1(2). 197–207.3 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.