ArticleSensors (Basel, Switzerland)2020
Machine Learning Algorithms to Classify and Quantify Multiple Behaviours in Dairy Calves Using a Sensor: Moving beyond Classification in Precision Livestock.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
26 citing papers in PubMed, 2 syntheses or guidelines pooled it, 56 citations in OpenAlex.
- A systematic review on the application of precision livestock farming technologies to detect lying, rest and sleep behavior in dairy calves.Frontiers in veterinary science · 2024Pooled it
- A Systematic Review of Automatic Health Monitoring in Calves: Glimpsing the Future From Current Practice.Frontiers in veterinary science · 2021Pooled it
- Predicting the onset of left displaced abomasum using behavioral changes measured by small 3D acceleration sensors attached to a cow collar.The Journal of veterinary medical science · 2026Article
- A non-AI preliminary algorithm for the prediction and detection of highly pathogenic African swine fever in pigs using health monitoring collars.Animal welfare (South Mimms, England) · 2026Article
- Wearable Sensors-Based Intelligent Sensing and Application of Animal Behaviors: A Comprehensive Review.Sensors (Basel, Switzerland) · 2025Review
- Wearable Collar Technologies for Dairy Cows: A Systematized Review of the Current Applications and Future Innovations in Precision Livestock Farming.Animals : an open access journal from MDPI · 2025Review
- Do Activity Sensors Identify Physiological, Clinical and Behavioural Changes in Laying Hens Exposed to a Vaccine Challenge?Animals : an open access journal from MDPI · 2025Article
- Monitoring Multiple Behaviors in Beef Calves Raised in Cow-Calf Contact Systems Using a Machine Learning Approach.Animals : an open access journal from MDPI · 2024Article
- Applications of Artificial Intelligence for Heat Stress Management in Ruminant Livestock.Sensors (Basel, Switzerland) · 2024Review
- Intelligent Animal Husbandry: Present and Future.Animals : an open access journal from MDPI · 2024Article
- Quantification of play behaviour in calves using automated ultra-wideband location data and its association with age, weaning and health status.Scientific reports · 2024Article
- A unified Foot and Mouth Disease dataset for Uganda: evaluating machine learning predictive performance degradation under varying distributions.Frontiers in artificial intelligence · 2024Article
- A Literature Review of Modeling Approaches Applied to Data Collected in Automatic Milking Systems.Animals : an open access journal from MDPI · 2023Review
- Evaluation of a Respiration Rate Sensor for Recording Tidal Volume in Calves under Field Conditions.Sensors (Basel, Switzerland) · 2023Article
- Literature Review on Technological Applications to Monitor and Evaluate Calves' Health and Welfare.Animals : an open access journal from MDPI · 2023Review
- Precision Livestock Farming: What Does It Contain and What Are the Perspectives?Animals : an open access journal from MDPI · 2023Review
- The impact of stress and anesthesia on animal models of infectious disease.Frontiers in veterinary science · 2023Review
- Indication of a personality trait in dairy calves and its link to weight gain through automatically collected feeding behaviours.Scientific reports · 2022Article
- Technological Tools for the Early Detection of Bovine Respiratory Disease in Farms.Animals : an open access journal from MDPI · 2022Review
- Industry 4.0 and Precision Livestock Farming (PLF): An up to Date Overview across Animal Productions.Sensors (Basel, Switzerland) · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Previous research has shown that sensors monitoring lying behaviours and feeding can detect early signs of ill health in calves. There is evidence to suggest that monitoring change in a single behaviour might not be enough for disease prediction. In calves, multiple behaviours such as locomotor play, self-grooming, feeding and activity whilst lying are likely to be informative. However, these behaviours can occur rarely in the real world, which means simply counting behaviours based on the prediction of a classifier can lead to overestimation. Here, we equipped thirteen pre-weaned dairy calves with collar-mounted sensors and monitored their behaviour with video cameras. Behavioural observations were recorded and merged with sensor signals. Features were calculated for 1-10-s windows and an AdaBoost ensemble learning algorithm implemented to classify behaviours. Finally, we developed an adjusted count quantification algorithm to predict the prevalence of locomotor play behaviour on a test dataset with low true prevalence (0.27%). Our algorithm identified locomotor play (99.73% accuracy), self-grooming (98.18% accuracy), ruminating (94.47% accuracy), non-nutritive suckling (94.96% accuracy), nutritive suckling (96.44% accuracy), active lying (90.38% accuracy) and non-active lying (90.38% accuracy). Our results detail recommended sampling frequencies, feature selection and window size. The quantification estimates of locomotor play behaviour were highly correlated with the true prevalence (0.97;
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.