The association between foot lesions and culling risk in Ontario Holstein cows
Bibliographic record
Abstract
The objective was to determine the association between specific foot lesions and culling in dairy cows. Using 5 trained professional hoof trimmers, data from 6,513 cows in 157 herds were recorded for analysis. During the study period, 1,293 cows (19.9%) were culled. Infectious lesions were most frequent in nonculled cows, whereas hoof horn lesions were most common in the culled cows. Median time to culling was 188 d [95% confidence interval (CI): 175-198 d] for cows without a lesion and 157 d (CI: 149-168 d) for cows with a lesion. Time from hoof trimming to culling was used to model the association between foot lesions and culling hazard. The final multivariate Cox proportional hazards model included heifers, infectious lesions, white line lesions, hemorrhages, sole ulcers, other lesions, and free-stall housing as covariates. Results of the final model showed that infectious hoof lesions had no significant association with culling. Yet, the hazard ratios for white line lesions, ulcers, and hemorrhage were 1.72 (CI: 1.39-2.11), 1.26 (CI: 1.05-1.52), and 1.36 (CI: 1.16-1.59), respectively. The association with culling for the grouped variable "other lesions" was time dependent and decreased with time. These results illustrate that there were significant associations with cow productivity for hoof horn lesions found at routine hoof trimming and that emphasis should be placed on proper treatment and earlier detection of these foot lesions.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".