Bioreduction of Sheep Carcasses Effectively Contains and Reduces Pathogen Levels under Operational and Simulated Breakdown Conditions
Bibliographic record
Abstract
Options for the storage and disposal of animal carcasses are extremely limited in the EU after the introduction of the EU Animal By-products Regulations (ABPR; EC/1774/2002), leading to animosity within the livestock sector and the call for alternative methods to be validated. Novel storage technologies such as bioreduction may be approved under the ABPR provided that they can be shown to prevent pathogen proliferation. We studied the survival of Enterococcus faecalis, Salmonella spp., E. coli O157 and porcine parvovirus in bioreduction vessels containing sheep carcasses for approximately 4 months. The vessels were operated under two different scenarios: (A) where the water within was aerated and heated to 40 °C, and (B) with no aeration or heating, to simulate vessel failure. Microbial analysis verified that pathogens were contained within the bioreduction vessel and indeed reduced in numbers with time under both scenarios. This study shows that bioreduction can provide an effective and safe on-farm storage system for livestock carcasses prior to ultimate disposal. The findings support a review of the current regulatory framework so that bioreduction is considered for approval for industry use within the EU.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".