Description of patterns of ear and tail lesions during the grower-finisher period in a commercial pig farm
Bibliographic record
Abstract
BACKGROUND: Ear and tail lesions are prevalent indicators of impaired welfare observed in pig production with different multifactorial causes. Understanding the progression of ear and tail lesions over time is important to implement preventative strategies on commercial pig farms. Therefore, this case study aimed to provide a detailed account of patterns of ear and tail lesions in pigs on a single commercial farm during the grower-finisher period. CASE PRESENTATION: A total of 1,676 12-week old pigs (n = 773 females and n = 903 males, all tail docked) were followed from arrival to the grower facilities until transferred to the finisher stage on a commercial pig farm in Ireland. Pigs were individually weighed and inspected for the severity of fresh ear and tail lesions (score 0-4) on transfer to the first grower (24.9 ± 5.33 kg, 12 weeks of age, n = 1,676 pigs), second grower (33.3 ± 7.04 kg, 14 weeks of age, n = 1,641 pigs), and finisher stage (60.2 ± 7.74 kg, 18 weeks of age, n = 1,626 pigs). Due to the low number of pigs with high scores, ear lesions were classified as no (score 0), mild (score 1), moderate (score 2) and severe (score ≥ 3) and tail lesions were classified as no (score 0), mild (score 1), and moderate-to-severe (score ≥ 2). Ear lesions were more prevalent than tail lesions at each inspection. There were approx. 19% of pigs with ear lesions at all three inspections but no pigs presented with tail lesions at all three inspections. When considering the specific severity categories, we observed 32 different ear lesion score combinations and 15 different tail lesion score combinations across the three inspections. CONCLUSION: The high number of observed patterns of ear and tail lesions suggest large individual variability in lesion progression. Ear lesions were more of an issue than tail lesions and little is known about this health and welfare problem indicating that further research into causes and management strategies is needed.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".