PSV-1 A prospective longitudinal study of the incidence and risk factors associated with footrot in feedlot lambs in Southern Alberta
Bibliographic record
Abstract
Abstract Lameness in sheep caused by footrot (FR) is a significant health, welfare, and economic concern worldwide. To date, no studies have documented the incidence of FR or associated risk factors in feedlot lambs in Alberta. The objectives of this study were to determine 1) FR incidence and 2) animal, managerial and environmental risk factors associated with FR in one Southern Alberta, lamb feedlot. Assessments were conducted biweekly (average of 10 pens per visit) by 2 experienced observers. A total of 73,150 lambs were assessed between October 2017 and March 2019. All lame lambs were scored according to a 3-point mobility scale (1 = mild, 2 = moderate, and 3 = severe lameness) and physically examined to diagnose the cause of lameness. Risk factors associated with FR were documented and included gender, days on feed (DOF), diet composition, and season. Multivariable regression models (SAS PROC GLIMMIX) were used to determine significant risk factors. A total of 473 lambs were identified as lame, 107 of which were diagnosed with FR (incidence of 22.6%). Footrot affected lambs had greater mobility scores (≥ 2; P < 0.0001) than all other lame diagnoses. Footrot was 4.40 and 0.10 times more likely (P < 0.0001) in female and wether than ram lambs, and 0.60 and 0.23 times more likely (P < 0.0001) in fall and summer than winter and spring seasons. The odds of being diagnosed with FR increased for each additional DOF and each unit increase of barley in the diet (P = 0.0268), while the odds decreased (P = 0.0016) for each additional unit of supplement in the diet. Based on our findings, footrot is an issue to lambs in Alberta, and further studies are still necessary to understand the risk factors associated with potential strategy for mitigating FR in feedlot lambs.
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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 | 0.001 | 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 | 0.000 |
| 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".