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Record W2010463936 · doi:10.3390/su6118237

Management Practices and Their Potential Influence on Johne’s Disease Transmission on Canadian Organic Dairy Farms—A Conceptual Analysis

2014· article· en· W2010463936 on OpenAlexafffundabout
Laura Pieper, U.S. Sorge, A. Godkin, T.J. DeVries, K. Lissemore, D.F. Kelton

Bibliographic record

VenueSustainability · 2014
Typearticle
Languageen
FieldMedicine
TopicMycobacterium research and diagnosis
Canadian institutionsMinistry of Agriculture, Food and Rural AffairsUniversity of Guelph
FundersOntario Ministry of Food and AgricultureUniversity of Guelph
KeywordsOrganic farmingBusinessAgricultureAgricultural scienceLimitingTransmission (telecommunications)Production (economics)Dairy farmingDairy cattleDisease managementBiotechnologyDiseaseEngineeringEnvironmental scienceMedicineEconomicsGeographyBiology

Abstract

fetched live from OpenAlex

Johne’s disease (JD) is a chronic, production-limiting disease of ruminants. Control programs aiming to minimize the effects of the disease on the dairy industry have been launched in many countries, including Canada. Those programs commonly focus on strict hygiene and management improvement, often combined with various testing methods. Concurrently, organic dairy farming has been increasing in popularity. Because organic farming promotes traditional management practices, it has been proposed that organic dairy production regulations might interfere with implementation of JD control strategies. However, it is currently unclear how organic farming would change the risk for JD control. This review presents a brief introduction to organic dairy farming in Canada, JD, and the Canadian JD control programs. Subsequently, organic practices are described and hypotheses of their effects on JD transmission are developed. Empirical research is needed, not only to provide scientific evidence for organic producers, but also for smaller conventional farms employing organic-like management practices.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.352

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.005
Science and technology studies0.0030.002
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.008
GPT teacher head0.280
Teacher spread0.272 · 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 designTheoretical or conceptual
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

Citations4
Published2014
Admission routes3
Has abstractyes

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