Associations between feeding behaviors collected from an automated milk feeder and disease in group-housed dairy calves in Ontario: A cross-sectional study
Bibliographic record
Abstract
The adoption of automated milk feeders and group housing of preweaning dairy calves has become more common in Canada; however, disease detection in group-housed calves remains a challenge. The aim of this cross-sectional study was to assess whether feeding behavior data collected from a single point in time could be used to aid in the detection of neonatal calf diarrhea (NCD), bovine respiratory disease (BRD), and general disease, in preweaning group-housed calves being fed via an automated milk feeder. The data used was collected in an earlier study. A total of 8 dairy farms recruited from an online survey of calf-management practices were enrolled into the study. There was a total of 523 observations with 130 events of NCD, 115 events of BRD, and 210 events of general disease. Each farm was visited once in each of the fall, winter, spring, and summer, when the calves' health was scored, and the data were collected from the automated milk feeders. Mixed linear regression models were used to identify associations between feeding behavior data (milk consumption, time spent at the feeder, drinking speed, and the number of rewarded and unrewarded visits) and the presence of NCD, BRD, or general disease (having one or more of NCD, BRD, or umbilical infection), on the day of health scoring. Generalized linear mixed models were used to analyze the percentage of milk the calf consumed from their daily milk allotment. Calves with BRD consumed 63% less of their daily allotment of milk, had 2 fewer unrewarded visits to the automated milk feeder, and drank milk 152 mL/min slower compared with calves without BRD. Calves with NCD consumed 57% less of their daily milk allotment, consumed 758 mL less per day, and drank 92 mL/min slower than calves compared with calves without NCD. Calves with general disease drank 50% less of their daily milk allowance, consumed 496 mL less per day, drank 80 mL/min slower, and had 2 fewer unrewarded visits to the automated milk feeder, when compared with calves without disease. No significant associations were found between the presence of NCD, BRD, or general disease and time spent at the feeder or number of rewarded visits. Sensitivity and specificity values for disease identification were low when evaluating the feeding behaviors individually, so parallel testing was completed. To do so, if any significant feeding behavior was below the optimal cut point for disease detection as determined using a ROC curve, the calf was considered positive for disease and the sensitivity and specificity were recalculated. Parallel testing resulted in a sensitivity of 0.82, 0.78, and 0.84, and a specificity of 0.26, 0.23, and 0.21, for BRD, NCD, and general disease, respectively. This suggests that automated milk feeders may serve as a useful preliminary tool in the detection of diseased calves. For example, producers could use feeding behavior data to identify calves requiring further inspection; however, they should not use feeding behavior data as a sole disease detection method.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 source (direct Gemma or distilled Codex), 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".