MétaCan
Menu
Back to cohort

Composting as a Means of Disposal of Sheep Mortalities

2000· article· en· W2068095977 on OpenAlexaffabout
Kim Stanford, Francis J. Larney, Å. Olson, L. J. Yanke, Ross H. McKenzie

Bibliographic record

VenueCompost Science & Utilization · 2000
Typearticle
Languageen
FieldVeterinary
TopicAnimal Behavior and Welfare Studies
Canadian institutionsAgriculture and Agri-Food CanadaAgriculture Food and Rural Development
Fundersnot available
KeywordsCompostStrawManureAnimal scienceAerationWoolBinAgronomyBiologyLitterEnvironmental scienceMaterials scienceEcologyMathematics

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.116
GPT teacher head0.395
Teacher spread0.279 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations42
Published2000
Admission routes2
Has abstractyes

Explore more

Same venueCompost Science & UtilizationSame topicAnimal Behavior and Welfare StudiesFrench-language works237,207