Composting as a Means of Disposal of Sheep Mortalities
Bibliographic record
Abstract
Four studies explored the feasibility of year-round composting of lamb and mature sheep mortalities within the arid climate of the Canadian prairies. In all studies, a ratio of 2:1:1 (manure : mortalities : chopped straw) was maintained, although depth of the mortality layer within the bin, number of layers of mortalities per bin, age of animal (lamb or mature sheep) and time of year (summer or winter) were varied. Composting neonatal lambs in the spring/summer was successful whether a single layer (n=15 lambs, weight 99.7 kg) or two, separated layers of mortalities (n=41 lambs, weight 198 kg) were added to a 2.4 m3 open bin. Residual bone, wool and soft tissues were negligible after the lamb compost had completed one heating cycle. In contrast, composting mature sheep in the fall/winter was more difficult due to: (1) over wet manure (31% dry matter) resulting in continuous anaerobic decomposition of carcasses; (2) fat/grease accumulation when composting a layer of carcasses 71 cm in depth (weight of sheep 1020 kg). For mature sheep mortalities, 2 heating cycles were required to eliminate soft tissues and wool. As compost in all studies heated in excess of 60°C in the primary and/or secondary bin, bacterial isolates taken after the compost completed the secondary heating cycle were all innocuous species. Provided that compost is protected from excessive moisture and compost is aerated by turning into a secondary bin, a 2:1:1 (manure:mortalities:straw) ratio allowed for year-round composting of lamb and mature sheep mortalities.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".