An evaluation of hock, knee, and neck injuries on dairy cattle in Canada
Bibliographic record
Abstract
This thesis is an investigation of the prevalence of, and factors associated with, hock, knee, and neck injuries on dairy cattle in Canada. Tie-stall (n = 100) and free-stall farms (n = 90) were visited in Quebec, Ontario, and Alberta, Canada. Cows were scored for hock (tarsus), knee (carpus), and neck injuries on a 3 or 4-point scale combining the attributes of hair loss, broken skin, and swelling. Animal-based and environmental measures were taken which were hypothesized to be risk factors for injury. On tie-stall farms the mean herd-level prevalence of hock, knee, and neck injuries was 56, 43, and 30%, respectively. On free-stall farms the mean herd-level prevalence of hock, knee, and neck injuries was 47, 24, and 9%, respectively. Having sand stall bases, feed rail heights above 140 cm and managing cows to reduce slips and falls were associated with reduced injury prevalence.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".