MétaCan
Menu
Back to cohort
Record W3093199998 · doi:10.3138/jvme-2019-0112

Simulated Clinical Skills for Veterinary Students Supplement Limited Animal and Clinical Resources in Developing Countries

2020· article· en· W3093199998 on OpenAlexvenueno aff
Jennifer M. Seddon, An T.T. Vo, Samantha R. Kempster, Hannah J. Lee, Toan Tat Nguyen, Katherine Munce, Alexander Del Bianco, Vithaya Chakitdee, Thong Quang, Frances M Shapter

Bibliographic record

VenueJournal of Veterinary Medical Education · 2020
Typearticle
Languageen
FieldHealth Professions
TopicVeterinary Practice and Education Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedical educationCompetence (human resources)Veterinary educationVeterinary medicineSkills managementMedicinePsychologyCurriculumPedagogy

Abstract

fetched live from OpenAlex

As part of an OIE Veterinary Education Twinning Project linking The University of Queensland, Australia and Nong Lam University, Vietnam, the limited access to animal and clinical resources was identified as an impediment to high quality veterinary education at Nong Lam University. However, student focused, simulated learning spaces, which have been widely adopted in veterinary training, are a cost-effective opportunity to provide initial clinical skills to students in countries where resourcing is constrained. In clinical skills training facilities, students use models and simulators to practice their clinical skills to develop the confidence, competence and muscle memory to enter the clinical phase of their training. While high-fidelity veterinary simulators and models are expensive, effective models for foundational clinical skills development can be built in-house for students to practice their skills authentically. This article outlines the cost effective establishment of a veterinary clinical skills training facility at Nong Lam University.

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)0.005
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.502
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.501
GPT teacher head0.634
Teacher spread0.132 · 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.

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

Citations7
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Veterinary Medical EducationSame topicVeterinary Practice and Education StudiesFrench-language works237,207