The cardiovascular effects of shechita in cattle: a systematic review shows the fallacies that vertebral artery will preserve cerebral blood flow and false aneurysms occur in severed carotid arteries
Bibliographic record
Abstract
Objective: To examine the hypotheses that (1) the Jewish practice of animal slaughter called shechita leaves meaningful cerebral blood flow through the vertebral arteries in cattle and (2) false aneurysms occur in carotid arteries that impair blood loss from hemorrhaging. Methods: A systematic literature review and calculations from existing data. Results: The shechita ventral-neck incision produces an immediate cessation of blood flow through the carotid arterial system, a dramatic fall in systemic arterial blood pressure (BP), and a more rapid fall in vertebral BP. Calculated cerebral blood flow is < 5% of normal within 10 seconds, a level that likely cannot sustain brain function or viability, a finding consistent with evidence that ligation of the vertebral arteries prior to ventral-neck incision does not alter brain function. None of the published histologic data are consistent with the definition of a false aneurysm. Data suggest the presence of fibrin or parts of blood clots inside or a hematoma around the severed carotid artery. None show significant intravascular thrombosis. There are no experimental data linking a false aneurysm with blood loss. Conclusions: Shechita produces a rapid fall in BP that reduces cerebral blood flow to < 5% within a few seconds, demonstrating the inadequacy of vertebral circulation to maintain cerebral blood flow. The label of false aneurysm is a misnomer, and the data do not convincingly link it to blood loss. Clinical Relevance: Clinicians should not be concerned that shechita in cattle will leave meaningful cerebral blood flow through vertebral arteries.
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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 | 0.004 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".