Risk-Benefit Assessment of Hog Mandibular Lymph Node Incision at Slaughter in Canada
Bibliographic record
Abstract
In the context of a risk-based meat inspection modernization, the change towards a visual only inspection of all hog mandibular lymph nodes (MLN) has been made in some countries and is considered in Canada. In fact, the current mandatory incision and visual inspection of all MLNs put in force a century ago to detect signs of infection by Mycobacterium bovis may no longer be relevant and may even generate cross-contamination by bacteria potentially pathogenic to humans. To support a science-based decision, a qualitative risk-benefit assessment following the European Food Safety Authority framework was undertaken for each inspection approach (with or without systematic incision). Both risk-benefit assessments led to similar results in concluding that the benefit of any MLN inspection for the detection of M. bovis infection in hogs is no longer existent. For the risk associated with this incision, data is lacking to differentiate the risk between both inspections on the qualitative scale chosen. In conclusion, the scientific opinion is that the replacement of the current systematic incision and visual inspection of all hog MLNs by a systematic visual-only inspection of all MLNs will not affect the food safety risks and in fact may reduce some of them.
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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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 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".