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.
Countries citing papers authored by Andres L. Carrano
Since
Specialization
Citations
This map shows the geographic impact of Andres L. Carrano'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 Andres L. Carrano with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andres L. Carrano more than expected).
Fields of papers citing papers by Andres L. Carrano
This network shows the impact of papers produced by Andres L. Carrano. 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 Andres L. Carrano. The network helps show where Andres L. Carrano may publish in the future.
Co-authorship network of co-authors of Andres L. Carrano
This figure shows the co-authorship network connecting the top 25 collaborators of Andres L. Carrano.
A scholar is included among the top collaborators of Andres L. Carrano 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 Andres L. Carrano. Andres L. Carrano is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Tornese, Fabiana, Andres L. Carrano, Brian K. Thorn, Jennifer A. Pazour, & Debjit Roy. (2016). Carbon footprint analysis of pallet remanufacturing. Journal of Cleaner Production. 126. 630–642.45 indexed citations
Carrano, Andres L., Michael E. Kuhl, & Matthew Marshall. (2008). Integration of an Experiential Assembly System Engineering Laboratory Module. International journal of engineering education. 24(5). 1012–1017.1 indexed citations
12.
Carrano, Andres L., et al.. (2007). Monitoring of abrasive loading for optimal belt cleaning or replacement. Forest Products Journal. 57(5). 78–83.4 indexed citations
Carrano, Andres L., James B. Taylor, & Richard L. Lemaster. (2004). Machining Induced Subsurface Damage of Wood. Forest Products Journal. 54(1). 85–91.6 indexed citations
15.
Carrano, Andres L., James B. Taylor, Robert E. Young, Richard L. Lemaster, & Daniel Saloni. (2004). Fuzzy knowledge-based modeling and statistical regression in abrasive wood machining. Forest Products Journal. 54(5). 66–72.5 indexed citations
16.
Carrano, Andres L., James B. Taylor, & Richard L. Lemaster. (2002). Parametric Characterization of Peripheral Sanding. Forest Products Journal. 52(9). 44–50.13 indexed citations
17.
Taylor, James B., Andres L. Carrano, & Richard L. Lemaster. (1999). Quantification of Process Parameters in a Wood Sanding Process. Forest Products Journal. 49(5). 41–46.1 indexed citations
18.
Taylor, James B., Andres L. Carrano, & Richard L. Lemaster. (1999). Quantification of process parameters in a wood sanding operation.. Forest Products Journal. 49(5). 41–46.61 indexed citations
19.
Carrano, Andres L. & J. Benjamin Taylor. (1999). Cooperative Learning Factories and Their Impact on Learning Styles. 3. 17–25.1 indexed citations
20.
Taylor, James B., Richard L. Lemaster, & Andres L. Carrano. (1999). Experimental Modeling of the Sanding Process - The Relationship Between Input and Output Parameters.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.