Rapid loss of consciousness in cattle following nonstun slaughter: evidence from a systematic review
Bibliographic record
Abstract
Background: Accepting that it is ethical for meat to be consumed as food, then, in any context, religious or secular, it is indefensible for animals to be subjected to undue pain. Animal slaughter must therefore be predicated on the minimization of pain. Nonstun slaughter (NSS) of bovines involves ventral neck incisions, resulting in an abrupt loss of cortical blood flow and causing nearly instantaneous loss of consciousness (LOC). However, some reports have suggested that LOC after NSS is not instantaneous. This paper presents an overview of the neurobiology underlying NSS and a systematic review of the literature on time to LOC in bovines following NSS. Methods: A literature review was conducted across PubMed, Google Scholar, the Cochrane Library, Medline, and the Web of Science, with 3 coauthors independently screening articles to reduce bias. Only original research and review articles specifically addressing time to LOC in bovines after NSS were included; studies not focused on this outcome were excluded. The quality of evidence was ranked based on hierarchy of evidence utilizing predefined criteria. Results: 15 studies were identified: 4 high quality, 3 medium quality, and 8 low quality. High-quality evidence consistently indicates that LOC occurs within 10 seconds of NSS of bovines when done correctly with low-stress, ideal slaughterhouse conditions. Clinical Relevance: Our findings provide important insights to optimize NSS practices, promoting animal welfare while maintaining religious requirements.
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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 | 0.010 | 0.062 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".