Health indicators in surplus calves at the time of arrival at auction markets: Associations with distance from farms of origin in Québec, Canada
Bibliographic record
Abstract
This study evaluated the associations between estimated distance from farms' locations to auction markets, and health indicators of surplus dairy calves sold during summer 2019 and winter 2020 in Québec, Canada. A total of 3,610 animals from 1,331 different farms were used in this cross-sectional cohort study. Geographic coordinates (latitude and longitude) were obtained for each farm and the 2 participating livestock auction markets. Calves' abnormal physical signs (APS) were noted upon arrival at the auction market as they were examined by trained research staff. The haversine distance between the farm and the auction market was evaluated using geographic coordinates and categorized. Generalized linear mixed models were used for statistical analyses. The main APS observed were ocular discharge (34.9%), abnormal hide cleanliness (21.2%), swollen navel (17.2%), dehydration score 1 (at least one of the 2 following clinical signs: persistent skin tent or sunken eye, 12.9%), and dehydration score 2 (both clinical signs mentioned above, 6.5%). Calves from farms located at greater distances from the auction markets (≥110 km) had a higher risk ratio [RR = 1.08; 95% confidence internal (CI) = 1.03, 1.13] for dehydration than those from lesser distances (0-25 km). During the summertime, a RR of 1.18 (95% CI = 1.15, 1.22) was observed for dehydration compared with wintertime. A 2-way interaction between estimated distance and season showed a higher prevalence of ocular discharge for calves from farms at distances greater than or equal to 110 km during the summer (RR = 1.11; 95% CI: 1.04, 1.20) than for calves from farms located at lesser distances (0-25 km). These results demonstrate that calves from farms located at greater distances from the auction markets had more APS, mainly during the summer. A better understanding of the transport conditions and interaction with management at the farm of origin is determinant to mitigate the impact of the journey on surplus calf health.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".