PSV-13 Incidence of infectious and non-infectious feet lesions and their association with carcass quality in sheep at a slaughter plant in Alberta
Bibliographic record
Abstract
Abstract Infectious and non-infectious feet lesions (FL) in livestock have been associated with reduced welfare, production, carcass and meat quality. Currently, the incidence of FL in sheep and its relationship with carcass quality has not been documented in Canada. The objectives of this study were to determine 1) the incidence and type of lesions in Alberta sheep at slaughter and 2) the relationship between FL and carcass quality. A total of 4,487 sheep carcasses were assessed for FL at a slaughter plant in Alberta, Canada between October 2017 and March 2019. Approximately 300 sheep were evaluated monthly by two experienced observers who recorded common infectious (IN) and non-infectious (NIN) lesions. In addition, carcass information including hot carcass weight (HCW), and back fat thickness (BFT) were obtained from the slaughter plant records. Data were analyzed by multivariable regression models using SAS PROC GLIMMIX. Overall, FL incidence was 9.4% (7.0% having one lesion and 2.4% having more than one lesion). Infectious lesions accounted for 45.7% of all lesions [footrot (37.1%), interdigital dermatitis (7.3%), and contagious ecthyma (1.3%)], while NIN lesions accounted for 54.3% [overgrown horn (21.9%), injury (13.6%), laminitis (10.2%), and other lesions (8.6%)]. Sheep with IN had lower BFT (13.5 ± 1.32 cm, P = 0.0002) and HCW (51.5 ± 1.89 kg, P = 0.0189) than NIN (15.8 ± 1.51 cm and 54.7 ± 1.97 kg, respectively). For every 1 cm decrease in BFT and 1 kg decrease in HCW the odds of IN increased by 0.89 (P < 0.0001) and 0.98 (P = 0.0229), respectively. Based on our findings, foot lesions are a significant issue for the Canadian sheep industry and infectious lesions may have greater detrimental effect on carcass quality than non-infectious lesions. Further studies are necessary to understand the relationship of carcass quality and feet lesion.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".