Verocytoxigenic<i>Escherichia coli</i>in animal faeces, manures and slurries
Bibliographic record
Abstract
Animal wastes and effluents from farming operations, including manures and slurries, are frequently applied as fertilizer to land used for crop or silage production and cattle grazing. It is well documented that potentially harmful pathogens including verocytoxigenic Escherichia coli (VTEC) are shed in animal faeces and there is growing concern in many countries about the number of sporadic and outbreak cases of VTEC attributable to direct contact with faecal material either as a result of handling contaminated mud in fields or ingestion of produce grown in contaminated manures or slurries. VTEC has been detected in the faeces of ruminant and non-ruminant farmed animals, wild animals, domestic pets and birds and the pathogen appears to be well adapted to survive in animal faeces and can persist for extended periods ranging from several weeks to many months. Because of this persistence these materials are important as potential vehicles for transmission within herds, farms, the fresh food chain and the wider environment. Appropriate handling of bovine faeces is necessary to control spread of this pathogen and to limit the significant risks of human infection. It may be necessary to hold manure/slurry for extended periods prior to spreading on farmland, or for use in the production of food crops, particularly foods that are to be consumed in the raw or minimally processed state. Alternatively, it may be necessary to apply processes such as composting, heat drying or digestion which can expedite the decline of pathogens including VTEC in manures. However, there is a need for research work to develop economical and practical systems for treatment of manures and slurries. The risk from direct contact with faecal material at farms and petting zoos is also recognized and many public health authorities have put forward measures for strict practices to limit the risk of infection, particularly for young children visiting these environments.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".