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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Comparison of methods for predicting cow composite somatic cell counts
Dorota Anglart, C. Hallén-Sandgren, Ulf Emanuelson, et al.
Journal of Dairy Science (2020) Vol. 103, Iss. 9, pp. 8433-8442
Open Access | Times Cited: 27

Showing 1-25 of 27 citing articles:

Performance comparison of machine learning models used for predicting subclinical mastitis in dairy cows: Bagging, boosting, stacking, and super-learner ensembles versus single machine learning models
Alicja Satoła, Krzysztof Satoła
Journal of Dairy Science (2024) Vol. 107, Iss. 6, pp. 3959-3972
Open Access | Times Cited: 11
Comparison of machine learning methods to predict udder health status based on somatic cell counts in dairy cows
Tania Bobbo, Stefano Biffani, Cristian Taccioli, et al.
Scientific Reports (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 43
Early detection of subclinical mastitis in lactating dairy cows using cow-level features
Arjun Pakrashi, Chris Ryan, Christophe Guéret, et al.
Journal of Dairy Science (2023) Vol. 106, Iss. 7, pp. 4978-4990
Open Access | Times Cited: 17
Over 20 Years of Machine Learning Applications on Dairy Farms: A Comprehensive Mapping Study
Philip Shine, Michael D. Murphy
Sensors (2021) Vol. 22, Iss. 1, pp. 52-52
Open Access | Times Cited: 34
Precision livestock farming technologies: Novel direction of information flow
Koray Tekin, Begüm Yurdakök-Di̇kmen, Halit Kanca, et al.
Ankara Üniversitesi Veteriner Fakültesi Dergisi (2021) Vol. 68, Iss. 2, pp. 193-212
Open Access | Times Cited: 29
Modeling the relationships among technological properties of sheep individual animal factors, milk composition, and minerals using generalized additive mixed models
Giorgia Stocco, Claudio Cipolat‐Gotet, Andrea Summer, et al.
Journal of Dairy Science (2025)
Open Access
Research on the prediction model of mastitis in dairy cows based on time series characteristics
Rui Guo, Yongqiang Dai, Junjie Hu
Frontiers in Veterinary Science (2025) Vol. 12
Open Access
Forecasting chronic mastitis using automatic milking system sensor data and gradient-boosting classifiers
John Bonestroo, Mariska van der Voort, H. Hogeveen, et al.
Computers and Electronics in Agriculture (2022) Vol. 198, pp. 107002-107002
Open Access | Times Cited: 16
Exploiting machine learning methods with monthly routine milk recording data and climatic information to predict subclinical mastitis in Italian Mediterranean buffaloes
Tania Bobbo, Roberta Matera, G. Pedota, et al.
Journal of Dairy Science (2022) Vol. 106, Iss. 3, pp. 1942-1952
Open Access | Times Cited: 16
Estimating the nonlinear association of online somatic cell count, lactate dehydrogenase, and electrical conductivity with milk yield
John Bonestroo, Mariska van der Voort, Nils Fall, et al.
Journal of Dairy Science (2022) Vol. 105, Iss. 4, pp. 3518-3529
Open Access | Times Cited: 14
Temperature, productivity, and heat tolerance: Evidence from Swedish dairy production
Haseeb Ahmed, Lena‐Mari Tamminen, Ulf Emanuelson
Climatic Change (2022) Vol. 175, Iss. 1-2
Open Access | Times Cited: 11
A Literature Review of Modeling Approaches Applied to Data Collected in Automatic Milking Systems
Laura Ozella, Karina Brotto Rebuli, Claudio Forte, et al.
Animals (2023) Vol. 13, Iss. 12, pp. 1916-1916
Open Access | Times Cited: 6
Cumulative Effect of Subclinical Mastitis on Immunological and Biochemical Parameters in Cow Milk.
H Dawood Saleem, M A Razooqi, Hasanain A. J. Gharban
DOAJ (DOAJ: Directory of Open Access Journals) (2021) Vol. 76, Iss. 6, pp. 1629-1638
Closed Access | Times Cited: 13
An economic analysis of high milk somatic cell counts in dairy cattle in Chiang Mai, Thailand
Tosapol Dejyong, Karoon Chanachai, Nathawit Immak, et al.
Frontiers in Veterinary Science (2022) Vol. 9
Open Access | Times Cited: 9
Rule Discovery in Milk Content towards Mastitis Diagnosis: Dealing with Farm Heterogeneity over Multiple Years through Classification Based on Associations
Esmaeil Ebrahimie, Manijeh Mohammadi‐Dehcheshmeh, Richard Laven, et al.
Animals (2021) Vol. 11, Iss. 6, pp. 1638-1638
Open Access | Times Cited: 12
Progression of different udder inflammation indicators and their episode length after onset of inflammation using automatic milking system sensor data
John Bonestroo, Mariska van der Voort, Nils Fall, et al.
Journal of Dairy Science (2020) Vol. 104, Iss. 3, pp. 3458-3473
Open Access | Times Cited: 7
Detecting and predicting changes in milk homogeneity using data from automatic milking systems
Dorota Anglart, Ulf Emanuelson, Lars Rönnegård, et al.
Journal of Dairy Science (2021) Vol. 104, Iss. 10, pp. 11009-11017
Open Access | Times Cited: 6
CowMesh: a data-mesh architecture to unify dairy industry data for prediction and monitoring
Arjun Pakrashi, Duncan Wallace, Brian Mac Namee, et al.
Frontiers in Artificial Intelligence (2023) Vol. 6
Open Access | Times Cited: 2
Somatisko šūnu skaita dinamikas kompleksā izvērtēšana mastīta diagnostikā govju robotizētā slaukšanā un transferencei derīgu embriju ieguvē = Complex assessment of the somatic cell count dynamics in mastitis diagnosis in cows` robotic milking and in the production of transferable embryos
Ivars Lūsis
(2024)
Open Access
Synergizing Enhanced Neuro-Fuzzy System for Predictive Livestock Healthcare in Cloud IoT Environment
T. Vigneswari, Farjana Farvin Sahapudeen, S. Geetha, et al.
2022 9th International Conference on Computing for Sustainable Global Development (INDIACom) (2024), pp. 171-177
Closed Access
Using Milk Flow Profiles for Subclinical Mastitis Detection
Changhong Jin, John Upton, Mehran Hossein Zadeh Bazargani, et al.
Smart Agricultural Technology (2024) Vol. 9, pp. 100537-100537
Open Access
Assessing traditional and machine learning methods to smooth and impute device-based body condition score throughout the lactation in dairy cows
José O. Chelotti, H. Atashi, M. Ferrero, et al.
Computers and Electronics in Agriculture (2024) Vol. 227, pp. 109599-109599
Open Access
A Literature Review on the Use of Modeling Approaches Applied to Automatic Milking Systems
Laura Ozella, Karina Brotto Rebuli, Claudio Forte, et al.
(2023)
Open Access | Times Cited: 1
Do Cows Have Fingerprints? Using Time Series Techniques and Milk Flow Profiles to Characterise Cow Milking Performance and Detect Health Issues
Changhong Jin, John Upton, Brian Mac Namee
Lecture notes in computer science (2023), pp. 230-242
Closed Access | Times Cited: 1
137. Machine learning to predict somatic cell count at the subsequent test-day record in the Italian Mediterranean Buffaloes
Tania Bobbo, Roberta Matera, G. Pedota, et al.
(2022), pp. 598-601
Closed Access | Times Cited: 1
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