David Navega

996 total citations
32 papers, 672 citations indexed

About

David Navega is a scholar working on Archeology, Genetics and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, David Navega has authored 32 papers receiving a total of 672 indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Archeology, 14 papers in Genetics and 10 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in David Navega's work include Forensic Anthropology and Bioarchaeology Studies (29 papers), Forensic and Genetic Research (13 papers) and Paleopathology and ancient diseases (12 papers). David Navega is often cited by papers focused on Forensic Anthropology and Bioarchaeology Studies (29 papers), Forensic and Genetic Research (13 papers) and Paleopathology and ancient diseases (12 papers). David Navega collaborates with scholars based in Portugal, United Kingdom and United States. David Navega's co-authors include Eugénia Cunha, María Teresa Ferreira, Ricardo Vicente, Francisco Curate, João d’Oliveira Coelho, Catarina Coelho, David Gonçalves, Ann H. Ross, Sofia N. Wasterlain and Duarte Nuno Vieira and has published in prestigious journals such as SHILAP Revista de lepidopterología, American Journal of Physical Anthropology and Forensic Science International.

In The Last Decade

David Navega

29 papers receiving 665 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
David Navega Portugal 12 600 271 197 61 54 32 672
Constantine Eliopoulos United Kingdom 11 492 0.8× 236 0.9× 83 0.4× 80 1.3× 68 1.3× 31 600
María Teresa Ferreira Portugal 15 621 1.0× 225 0.8× 118 0.6× 91 1.5× 170 3.1× 85 813
John Albanese Canada 11 526 0.9× 303 1.1× 140 0.7× 54 0.9× 22 0.4× 25 655
Francisco Curate Portugal 16 684 1.1× 262 1.0× 204 1.0× 98 1.6× 59 1.1× 74 845
Carme Rissech Spain 18 788 1.3× 223 0.8× 320 1.6× 63 1.0× 27 0.5× 46 946
Christian M. Crowder United States 13 451 0.8× 194 0.7× 118 0.6× 74 1.2× 50 0.9× 33 703
Anja Petaros Croatia 13 282 0.5× 150 0.6× 87 0.4× 51 0.8× 45 0.8× 46 461
Nicholas P. Herrmann United States 9 396 0.7× 162 0.6× 143 0.7× 48 0.8× 28 0.5× 25 480
Joseph T. Hefner United States 13 534 0.9× 407 1.5× 111 0.6× 49 0.8× 15 0.3× 38 644
Lucina Hackman United Kingdom 11 265 0.4× 102 0.4× 127 0.6× 30 0.5× 15 0.3× 36 375

Countries citing papers authored by David Navega

Since Specialization
Citations

This map shows the geographic impact of David Navega'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 David Navega with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Navega more than expected).

Fields of papers citing papers by David Navega

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David Navega. 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 David Navega. The network helps show where David Navega may publish in the future.

Co-authorship network of co-authors of David Navega

This figure shows the co-authorship network connecting the top 25 collaborators of David Navega. A scholar is included among the top collaborators of David Navega 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 David Navega. David Navega is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Cunha, Eugénia, et al.. (2024). Metric analysis of the patella for sex estimation in a Portuguese sample. Forensic Sciences Research. 9(2). owae015–owae015. 1 indexed citations
2.
Scott, G. Richard, et al.. (2024). rASUDAS2. Liverpool John Moores University.
3.
Navega, David, María Teresa Ferreira, & Francisco Curate. (2023). Eigenfemora—Age-at-Death Estimation in the Proximal Femur through an Image Processing Approach. SHILAP Revista de lepidopterología. 4(1). 1–11.
4.
Scott, G. Richard, et al.. (2023). Peopling of the Americas: A new approach to assessing dental morphological variation in Asian and Native American populations. American Journal of Biological Anthropology. 186(1). e24878–e24878. 2 indexed citations
5.
Navega, David, Ernesto Costa, & Eugénia Cunha. (2022). Adult Skeletal Age-at-Death Estimation through Deep Random Neural Networks: A New Method and Its Computational Analysis. Biology. 11(4). 532–532. 21 indexed citations
6.
Curate, Francisco, David Navega, Eugénia Cunha, & João d’Oliveira Coelho. (2022). DXAGE 2.0 — adult age at death estimation using bone loss in the proximal femur and the second metacarpal. International Journal of Legal Medicine. 136(5). 1483–1494. 6 indexed citations
7.
Wasterlain, Sofia N., et al.. (2019). SPINNE: An app for human vertebral height estimation based on artificial neural networks. Forensic Science International. 298. 121–130. 4 indexed citations
8.
9.
Freire, Alexandre Rodrigues, David Navega, Eugénia Cunha, et al.. (2018). Application and validation of Diagnose Sexuelle Probabiliste V2 tool in a miscegenated population. Forensic Science International. 290. 351.e1–351.e5. 19 indexed citations
10.
Navega, David, et al.. (2018). Age estimation of adult human remains from hip bones using advanced methods. Forensic Science International. 287. 163–175. 37 indexed citations
11.
Navega, David, M. Godinho, Eugénia Cunha, & María Teresa Ferreira. (2018). A test and analysis of Calce (2012) method for skeletal age-at-death estimation using the acetabulum in a modern skeletal sample. International Journal of Legal Medicine. 132(5). 1447–1455. 9 indexed citations
12.
Navega, David, et al.. (2017). Luminol chemiluminescence: contribution to postmortem interval determination of skeletonized remains in Portuguese forensic context. International Journal of Legal Medicine. 131(4). 1149–1153. 13 indexed citations
13.
Gonçalves, David, et al.. (2017). Dead weight: Validation of mass regression equations on experimentally burned skeletal remains to assess skeleton completeness. Science & Justice. 58(1). 2–6. 3 indexed citations
14.
Ibáñez, Óscar, Ricardo Vicente, David Navega, et al.. (2016). MEPROCS framework for Craniofacial Superimposition: Validation study. Legal Medicine. 23. 99–108. 8 indexed citations
15.
Curate, Francisco, João d’Oliveira Coelho, David Gonçalves, et al.. (2016). A method for sex estimation using the proximal femur. Forensic Science International. 266. 579.e1–579.e7. 63 indexed citations
16.
Dias, Paulo, Catarina Coelho, João d’Oliveira Coelho, et al.. (2016). Towards automatic non-metric traits analysis on 3D models of skulls. 1–7.
17.
Curate, Francisco, et al.. (2015). Cortical Bone Loss and Osteoporotic Fractures in the Coimbra Identified Skeletal Collection. 2 indexed citations
18.
Ferreira, María Teresa, Ricardo Vicente, David Navega, et al.. (2014). A new forensic collection housed at the University of Coimbra, Portugal: The 21st century identified skeletal collection. Forensic Science International. 245. 202.e1–202.e5. 87 indexed citations
19.
Navega, David, Catarina Coelho, Ricardo Vicente, et al.. (2014). AncesTrees: ancestry estimation with randomized decision trees. International Journal of Legal Medicine. 129(5). 1145–1153. 81 indexed citations
20.
Navega, David, Ricardo Vicente, Duarte Nuno Vieira, Ann H. Ross, & Eugénia Cunha. (2014). Sex estimation from the tarsal bones in a Portuguese sample: a machine learning approach. International Journal of Legal Medicine. 129(3). 651–659. 83 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.

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