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.
New PARSEC evolutionary tracks of massive stars at low metallicity: testing canonical stellar evolution in nearby star-forming dwarf galaxies
2014296 citationsL. Bianchi et al.Monthly Notices of the Royal Astronomical Societyprofile →
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 L. Bianchi'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 L. Bianchi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites L. Bianchi more than expected).
This network shows the impact of papers produced by L. Bianchi. 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 L. Bianchi. The network helps show where L. Bianchi may publish in the future.
Co-authorship network of co-authors of L. Bianchi
This figure shows the co-authorship network connecting the top 25 collaborators of L. Bianchi.
A scholar is included among the top collaborators of L. Bianchi 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 L. Bianchi. L. Bianchi is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Rampazzo, R., S. Ciroi, P. Mazzei, et al.. (2020). Dorado and its member galaxies. Hα imaging of the group backbone. arXiv (Cornell University). 643.1 indexed citations
Bianchi, L., et al.. (2009). Young Stellar Populations in M31. 213.1 indexed citations
11.
Bianchi, L. & L. H. Rodríguez‐Merino. (2007). Statistical properties of the GALEX-SDSS matched source catalogs, and classification of the UV sources. LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas).42 indexed citations
12.
Gordon, Karl D., G. H. Rieke, O. Krause, et al.. (2004). The multiwavelength view of M31 including New Spitzer/MIPS infrared images. Swinburne Research Bank (Swinburne University of Technology). 205.1 indexed citations
Bianchi, L., et al.. (2000). GALEX (The Galaxy Evolution Explorer). MmSAI. 71. 1117.1 indexed citations
15.
Bianchi, L., et al.. (2000). The Ultraviolet Digital Sky (the GALEX Science Data Archive). MmSAI. 71. 1123.1 indexed citations
16.
Bianchi, L., et al.. (1999). The Galaxy Evolution Explorer (GALEX): an All Sky Ultraviolet Survey. MmSAI. 70. 365.3 indexed citations
17.
Moos, W., Kenneth R. Sembach, & L. Bianchi. (1998). Far Ultraviolet Astronomy and Origins: The FUSE Mission. ASPC. 148. 304.1 indexed citations
18.
Martin, Christopher, B. Madore, L. Bianchi, et al.. (1997). The Galaxy Evolution Explorer. CaltechAUTHORS (California Institute of Technology). 164. 182.3 indexed citations
19.
Cassatella, A., P. Patriarchi, P. L. Selvelli, et al.. (1982). The UV variability of T CrB.. ESASP. 176. 229–231.1 indexed citations
20.
Rohr, H.P., J. Lüthy, F Gudat, et al.. (1976). Stereology: a new supplement to the study of human liver biopsy specimens.. Munich Personal RePEc Archive (Ludwig Maximilian University of Munich). 5. 24–34.12 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.