Simulated Clinical Skills for Veterinary Students Supplement Limited Animal and Clinical Resources in Developing Countries
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".