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Record W1977983173 · doi:10.3138/jvme.34.5.554

Animal-Handling Teaching at the Royal (Dick) School of Veterinary Studies, University of Edinburgh

2007· article· en· W1977983173 on OpenAlexaffvenue
M.S. Cockram, Kay Aitchison, David Collie, Gidona Goodman, Jo‐Anne Murray

Bibliographic record

VenueJournal of Veterinary Medical Education · 2007
Typearticle
Languageen
FieldHealth Professions
TopicVeterinary Practice and Education Studies
Canadian institutionsUniversity of Prince Edward Island
Fundersnot available
KeywordsAnimal husbandryVeterinary medicineCurriculumCompetence (human resources)Medical educationVeterinary educationMedicinePsychologyPedagogyBiologyAgriculture

Abstract

fetched live from OpenAlex

This article describes the teaching of animal handling at the Royal (Dick) School of Veterinary Studies, University of Edinburgh, as part of an animal husbandry course during the first two years of the veterinary curriculum. Basic methods of handling and restraint appropriate for the wide range of animal species that might be encountered in veterinary practice are demonstrated in practical handling classes. Students are given opportunities to practice the techniques under supervision. Additional handling experience is available during extramural studies in animal husbandry at a variety of establishments. Students are formally examined on their ability to handle and restrain animals, and each is required to reach a threshold degree of competence before progressing to the clinical years.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.090
Threshold uncertainty score0.301

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0030.002
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0900.014

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 head0.345
GPT teacher head0.538
Teacher spread0.193 · 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 designNot applicable
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

Citations11
Published2007
Admission routes2
Has abstractyes

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