Use of on-farm emergency slaughter for dairy cows in British Columbia
Bibliographic record
Abstract
On-farm emergency slaughter (OFES), whereby inspection, stunning, and bleeding occur on the farm before the carcass is transported to a slaughterhouse, is permitted in some jurisdictions as a means to avoid inhumane transportation while salvaging meat from injured animals. However, OFES is controversial and its use for dairy cows has been little studied. Inspection documents for 812 dairy cows were examined to identify how OFES was used for dairy cows in British Columbia, Canada, over 16.5 mo. Producers used OFES for dairy cows aged 1 to 13 yr (median of 4 yr). Leg, hip, nerve, spinal, foot, and hind-end injuries or conditions (in that order) were the most common reasons for OFES, and some cases may have been a consequence of calving. Foot conditions were disproportionately common among cows 5 yr and older, and hind-end conditions were disproportionately common among cows 6 yr and older. Producers used OFES promptly after traumatic injury (within 1 d) for some cows, but OFES was delayed for others, sometimes until cows had been nonambulatory for 2 to 6 d. In some cases, OFES was used for nontraumatic chronic conditions, such as lameness and hind-end weakness, rather than traumatic injuries such as fractures and dislocated hips. Use of OFES appears to conform to the purpose of the program when used promptly after traumatic injuries, but clear guidelines are needed to avoid inappropriate use and delays that may prolong animal suffering.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".