Severe tail lesions in finisher pigs are associated with reduction in annual profit in farrow‐to‐finish pig farms
Bibliographic record
Abstract
OBJECTIVES: We investigated the financial impact of different prevalence levels of severe tail lesions (STL) during the finisher stage associated with changes in average daily gain (ADG) in farrow-to-finish pig farms. METHODS: Prevalence of STL was estimated for 31 farrow-to-finish pig farms. Regression tree analysis was used to identify a threshold for STL associated with differences in ADG. Then, a financial analysis was carried using the Teagasc Pig Production model. RESULTS: A threshold of ≥0.86% prevalence of STL was associated with a 4.8% decrease in ADG which translated into pigs requiring 7 days more to reach target slaughter weight than in farms below the threshold. Reduced ADG meant that farms with higher prevalence of STL used 3.6% more weaner and 1.4% more finisher feed per year increasing feed costs by 1.5%. This reduced mean annual farm profit by 15.1% in farms with higher prevalence of STL. CONCLUSIONS: Our results provide an indication of the financial effects of STL in intensive pig production systems. The identified threshold for the prevalence of STL could provide a tangible target for farmers to focus on in developing strategies to reduce tail lesions and allow farmers to complete a cost benefit analysis of controlling STL.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".