Advice regarding an alternative bleeding method for harvesting young grey seals
Bibliographic record
Abstract
The Marine Mammal Regulations (MMR) mandate a three-step process when killing seals for personal or commercial purposes to comply with high standards of animal welfare. The aim of the final “bleeding step” (described in the MMR as bleeding the animal by severing the axillary arteries) is undertaken to ensure that the animal is dead before the carcass is further processed by the harvester. The time required to bleed young grey seals by severing either the axillary arteries and surrounding blood vessels or the common carotid arteries and surrounding blood vessels were compared. Results indicate that severance of the common carotid arteries and surrounding blood vessels located in the ventral part of the neck is as rapid and efficient as severing the axillary arteries and surrounding blood vessels for bleeding young grey seals and would thus be adequate to ensure death from an animal welfare perspective. Bleeding time with both methods was unaffected by the body weight of the young grey seals and was similar for males and females. Comparing bleeding time from severance of axillary arteries between young harp seals and grey seals, bleeding time was overall 60% longer in grey seals than harp seals. This is likely a result of a larger body mass and blood volume in grey seals, and differences in hunting techniques between these two species.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.028 | 0.018 |
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".