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.
Invited review: Sensors to support health management on dairy farms
2013365 citationsC.J. Rutten, A.G.J. Velthuis et al.Journal of Dairy Scienceprofile →
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 C.J. Rutten'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 C.J. Rutten with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites C.J. Rutten more than expected).
This network shows the impact of papers produced by C.J. Rutten. 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 C.J. Rutten. The network helps show where C.J. Rutten may publish in the future.
Co-authorship network of co-authors of C.J. Rutten
This figure shows the co-authorship network connecting the top 25 collaborators of C.J. Rutten.
A scholar is included among the top collaborators of C.J. Rutten 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 C.J. Rutten. C.J. Rutten is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Steeneveld, W., C.J. Rutten, Alfons Oude Lansink, & H. Hogeveen. (2017). Why not investing in sensors is logical for dairy farmers. Socio-Environmental Systems Modeling.3 indexed citations
Rutten, C.J., W. Steeneveld, K. Huijps, & H. Hogeveen. (2015). Development of a predictive model for the onset of calving. Socio-Environmental Systems Modeling. 397–405.1 indexed citations
Rutten, C.J., A.G.J. Velthuis, W. Steeneveld, & H. Hogeveen. (2013). Invited review: Sensors to support health management on dairy farms. Journal of Dairy Science. 96(4). 1928–1952.365 indexed citations breakdown →
9.
Rutten, C.J., A.G.J. Velthuis, W. Steeneveld, & H. Hogeveen. (2013). Can sensor technology benefit mastitis control.. 23–34.1 indexed citations
10.
Rutten, C.J., A.G.J. Velthuis, W. Steeneveld, & H. Hogeveen. (2013). Overview of published sensor systems for detection of oestrus and lameness in dairy cows. Socio-Environmental Systems Modeling. 163–171.
11.
Rutten, C.J., A.G.J. Velthuis, W. Steeneveld, & H. Hogeveen. (2013). Sensor systems for dairy cow health management: A review. Data Archiving and Networked Services (DANS). 89–90.
12.
Oene, G.H. de Weert-van, et al.. (2012). [Clinical treatment of posttraumatic stress disorder in patients with serious dual diagnosis problems].. PubMed. 54(4). 383–8.3 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.