Technical note: Evaluation of a system for monitoring rumination in heifers and calves
Bibliographic record
Abstract
The Hi-Tag electronic rumination-monitoring system (SCR Engineers Ltd., Netanya, Israel), based on capturing audio recordings, provides a reasonable measure of rumination time in dairy cows, but has not been validated for milk-fed or weaned heifers. The objective of this study was to validate the Hi-Tag rumination-monitoring system in heifers and calves and to assess whether suckling from a teat interfered with recording from this system. Assessments of 2 independent observers were highly correlated (r=0.99, n=20), indicating that direct visual observations provide a useful standard. Measures from the Hi-Tag system were validated by comparing values with those from a single human observer, using observations from three 2-h intervals from 35 Holstein calves and heifers aged 4, 6, and 9 wk and 3, 6, and 9 mo, respectively. In 9-mo-old heifers, rumination times obtained from the electronic system were highly correlated with visual observations (r=0.88, R2=0.77, n=15), and the mean difference was minor (-4±8 min/2-h interval). The accuracy of data from the automated system decreased when used on heifers less than 9 mo old. Suckling did not interfere with the electronic system (r=-0.1, n=18). These results indicate that the Hi-Tag system is an accurate tool for monitoring rumination behavior in Holstein Friesian heifers from the age of 9 mo.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".