Behavior and productivity of cows milked in automated systems before diagnosis of health disorders in early lactation
Bibliographic record
Abstract
Associations of electronically recorded data were examined before diagnosis of health disorders in early-lactation cows in herds with automated milking systems (AMS). Rumination time, activity, and milk yield data were collected for 8 mo for 605 early-lactation cows in 9 commercial AMS herds. Using multivariable generalized linear regression models controlling for parity and days in milk, data were examined relative to the day of diagnosis for health disorders occurring in absence of, or at least 14 d before, another disorder: mastitis (n = 13), new cases of lameness (n = 45), subclinical ketosis (SCK; n = 113), and purulent vaginal discharge (n = 49). All cases of displaced abomasum (DA; n = 8) occurred in conjunction with other disorders. Deviations from baseline among affected cows were examined, as well as differences compared with a group of healthy cows and an average group of all cows, who were given mock diagnosis days using the mean days in milk at diagnosis for each disorder. On 6 to 14 d of the 2 wk before diagnosis, cows with DA or mastitis had lower milk yield, rumination time, milking frequency, activity, and milk temperature compared with healthy cows as well as deviations from their own baseline rumination time and milk data starting 4 to 12 d before diagnosis. Cows with DA had lower AMS supplement intake than healthy cows and deviations from their baseline activity and milk temperature starting 6 and 4 d before diagnosis, respectively. Cows with mastitis had greater milk conductivity than healthy cows and deviated from their baseline milking frequency and conductivity 8 and 12 d before diagnosis, respectively. Compared with healthy cows, those with SCK or new cases of lameness generally had lower milk yield, rumination time, milk temperature, supplement intake, and milking and refusal frequencies. Only the milk temperature of lame cows deviated from baseline. Thus, acute health disorders (i.e., DA and mastitis) were associated with deviations from those cows' baseline AMS data, whereas more chronic disorders (i.e., SCK and lameness) were associated with significant but subtle longer term changes in milk production and behavior. Because cows with health disorders deviated from a group of healthy cows before they deviated from their own baseline and from the average of all other cows, including a healthy reference group in health alerts could refine the ability of detection models to identify subtle deviations in early lactation.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".