Daily behavioral measures recorded by precision technology devices may indicate bovine respiratory disease status in preweaned dairy calves
Bibliographic record
Abstract
Precision technology devices can measure and detect relative changes in an animal's behavior to possibly create alerts to intervene and to administer treatments. However, the association of relative changes in daily feeding and activity behaviors in calves with bovine respiratory disease (BRD) status is still largely unexplored. The objective of this case-control study was to determine if daily behavioral patterns of preweaning dairy calves (measured by precision technologies) change before BRD diagnosis. This case-control study enrolled 33 pairs of calves (33 BRD calves matched by age, sex, and birthdate to 33 controls) health scored daily for BRD for the preweaning period (until 50 d on the automated feeder). A pedometer (IceQube, Ice Robotics) was attached to the left rear leg to track activity (lying time, lying bouts, total steps, and acceleration activity index). At 3.0 ± 2.0 d of age, calves were trained to use the automated feeder, which recorded milk and calf starter intake, drinking speed, and feeder visits. Calves were allotted a maximum 10 L/d of milk replacer (Cow's Match, Land O'Lakes Animal Milk Products Co.; 140 g/L) and starter (Special Calf Starter and Grower, Baghdad Feeds), ad libitum. Calves were scored daily for signs of BRD using the Wisconsin scoring system, and their lungs were scored with ultrasonography twice weekly. Outward signs of BRD as defined by the Wisconsin scoring system and an area of consolidated lung ≥3.0 cm2 was identified as BRD (d 0). Relative changes in daily behaviors were calculated using d −5 before BRD diagnosis as the baseline for each calf for each behavior. Linear mixed models were used to investigate the association of BRD status with feeding behaviors, activity, and relative changes in calf behavior over a 5-d period before diagnosis, as well as the BRD status × day interaction. Calves with a BRD bout were diagnosed at an average age of 33.0 ± 9.0 d (mean ± standard deviation) and weighed 56.1 ± 9.7 kg. Over the period, BRD calves had reduced milk and starter intake, greater lying times, and fewer lying bouts, step counts, and activity indices when compared with healthy calves. Furthermore, there was a BRD status × day interaction for relative changes in unrewarded visits, and relative changes in calf starter intake. Specifically, BRD calves had a decline in relative changes in their unrewarded visits on d −4, −2, −1, and 0 compared with healthy calves. This study suggests that there is the potential to use feeding and activity behaviors to identify BRD development in preweaning calves. However, utilization of an animals' daily behavioral patterns in real time is fundamental for developing disease detection algorithms, thus we suggest relative changes in unrewarded visits may be useful for algorithm development when d −5 is used as a baseline. Future research should investigate the potential of feeding behavior and activity levels collectively to indicate BRD status in calves using machine learning techniques.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".