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.
Evaluation of the confusion matrix method in the validation of an automated system for measuring feeding behaviour of cattle
2018177 citationsWilhelmiina Hämäläinen, Sari Kajava et al.Behavioural Processesprofile →
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 Sari Kajava'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 Sari Kajava with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sari Kajava more than expected).
This network shows the impact of papers produced by Sari Kajava. 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 Sari Kajava. The network helps show where Sari Kajava may publish in the future.
Co-authorship network of co-authors of Sari Kajava
This figure shows the co-authorship network connecting the top 25 collaborators of Sari Kajava.
A scholar is included among the top collaborators of Sari Kajava 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 Sari Kajava. Sari Kajava is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Uusitalo, Sanna, et al.. (2019). Comparison of milk analysis performance between NIR laboratory analyser and miniaturised NIR MEMS sensors. Lirias (KU Leuven). 111–115.4 indexed citations
8.
Mäntysaari, Päivi, Tuomo Kokkonen, Sari Kajava, et al.. (2018). Developing an indicator for body fat mobilisation using mid-infrared spectrometry of milk samples in dairy cows. Open Repository and Bibliography (University of Liège). 225.3 indexed citations
9.
Hämäläinen, Wilhelmiina, et al.. (2018). Evaluation of the confusion matrix method in the validation of an automated system for measuring feeding behaviour of cattle. Behavioural Processes. 148. 56–62.177 indexed citations breakdown →
10.
Rinne, Marketta, et al.. (2017). Novel rapeseed proteins in Finnish dairy cow’s diets. Jukuri (Natural Resources Institute Finland (Luke)).1 indexed citations
Kajava, Sari, et al.. (2014). Validation of the TrackLab positioning system in a cow barn environment. Jukuri (Natural Resources Institute Finland (Luke)).6 indexed citations
13.
Kajava, Sari, et al.. (2012). Testissä tilatason progesteronimittarit. Jukuri (Natural Resources Institute Finland (Luke)).
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.