12 The Canadian Pork Industry’s Perspective on Swine Welfare Research.
Bibliographic record
Abstract
The Canadian pork industry places a high priority on swine welfare and strives to continuously improve it. Canada has a long history of producing high-quality swine welfare research from its universities and centres of excellence, much of which is highly and immediately applicable to the industry. The most recent edition of the Code of Practice for the Care and Handling of Pigs, which outlines standards of care expected at all Canadian pig farms, was developed by the industry and published in 2014. The development and implementation of the Code identified a number of priorities related to swine welfare that require further research. Other research priorities to address current welfare challenges in the Canadian pork industry have also been identified recently. These priorities include social, environmental, nutritional, and management factors that impact swine welfare.
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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 | 0.017 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.010 | 0.012 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.011 | 0.007 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".