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Record W4321510073 · doi:10.21423/aabppro20123866

Beef practice models

2012· article· en· W4321510073 on OpenAlexaffabout
Murray Jelinski

Bibliographic record

VenueAmerican Association of Bovine Practitioners Conference Proceedings · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Farm Safety
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsConsolidation (business)BusinessService (business)Best practiceMarketingAgricultureService delivery frameworkProduction (economics)Food serviceOperations managementEngineeringEconomicsManagementFinanceGeography

Abstract

fetched live from OpenAlex

Veterinary service delivery models for beef practice are best viewed as a continuum, ranging from the traditional task-oriented, service-on-demand ("fire engine practice") to a more contemporary evolving model, wherein veterinary practitioners provide consultative services. The bulk of practices, however, lie within these two extremes, with practitioners providing a blend of services customized to their clients' needs. Generally, larger beef operations have been more receptive to paying retainer fees for consultative services, while smaller operators prefer the conventional fee-for-service (unbundled services) model. North America is aging, and nearly half of Canadian producers are over 55 years of age. As a result, consolidation in all agricultural sectors will continue, and may even accelerate, leading to fewer but much larger operations. Therefore, the stage is being set for the beef practice delivery model to shift towards consultative services. While this model requires fewer veterinarians to look after a larger number of animals, it also requires practitioners to become more knowledgeable in the areas of beef production.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.472
Threshold uncertainty score0.285

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.017
GPT teacher head0.241
Teacher spread0.224 · 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 teacher head, 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

Citations0
Published2012
Admission routes2
Has abstractyes

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