Breed, parity, and days in milk affect risk of tongue rolling in dairy cows
Bibliographic record
Abstract
Stereotypic behaviors are repetitive, invariant movements with no obvious biological function. Tongue rolling (TR) is a common stereotypic behavior in cattle, characterized by a repeated circular movement of the tongue inside or outside of the mouth. We assessed TR in adult lactating dairy cows (from 45 to 305 d in milk; DIM) on a large commercial US dairy comprised of Jersey and Jersey-Holstein crosses (n = 8,158 cows). Cows were monitored during each of 3 consecutive milkings using video cameras located at the center of 2 rotary parlors. In total, 29.0% (2,365/8,158) of cows tongue rolled at least once, 7.9% (646/8,158) at least twice, and 1.7% (141/8,158) tongue rolled during all 3 milkings. The effects of breed (Jersey vs. Jersey-Holstein cross), parity (first lactation versus older), DIM, and the interactions between breed and parity and DIM on TR (comparing cows that were never observed rolling versus cows observed doing so at least once) were tested using logistic regression, revealing interactions between breed and parity. Among primiparous cows, Jerseys were more likely than Jersey-Holstein crosses to tongue roll [odds ratio (OR) = 1.61, confidence interval (CI) = 1.35-1.92]; similarly, among second-parity and older cows, Jerseys were again more likely to tongue roll than were Jersey-Holstein crosses (OR = 2.35, CI = 1.95-2.83). The effect of DIM differed by breed and parity; for primiparous Jerseys, the odds of TR increased with DIM (OR = 1.31, CI 1.12-1.52, for every 100-d increase), and for Jersey-Holsteins cows the odds of TR decreased with DIM (OR = 0.61, CI 0.43-0.88, for every 100-d increase). These breed, parity, and stage of lactation differences within a single farm suggest a role of both genetic and developmental effects in the proclivity to tongue roll.
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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 | 0.002 |
| 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) | 0.001 | 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".