A prospective longitudinal study of risk factors associated with cattle lameness in southern Alberta feedlots
Bibliographic record
Abstract
The objectives of this study were to determine the incidence proportion of lameness in feedlot cattle and the associated risk factors. Lameness was studied in two southern Alberta feedlots over a 2 yr period. The incidence proportion of lameness was 36.3% for all calves pulled for treatment. Risk factors associated (P < 0.0001) with increased lameness included body weight (BW), type of cattle, source, stocking density, percentage of forage in the diet, season, precipitation 1 d before diagnosis, and average temperature range 3 d prior to diagnosis. As BW (P < 0.001) increased, the odds of becoming lame also increased. Yearlings and Holsteins had greater (P < 0.001) incidence of lameness than respiratory disease. The odds of becoming lame decreased (P < 0.001) with increased pen density and percentage of forage in the diet. Lameness was greatest in spring (P < 0.001) with the odds of becoming lame being more likely (P < 0.001) with increased precipitation and temperature range (P < 0.001). Use of a multifactorial approach including animal, managerial, and environmental factors in a single analysis will improve our understanding of the risk of increased lameness and aid in development of strategies to reduce its incidence in feedlots.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".