The SimSpay—Student Perceptions of a Low-Cost Build-It-Yourself Model for Novice Training of Surgical Skills in Canine Ovariohysterectomy
Bibliographic record
Abstract
Practical and ethical considerations have led to an increased use of artificial substitutes for live animals in veterinary surgical skills training. However, commercially produced models are expensive and homemade models often require full-time staff to produce enough models for training large groups of students. In the Department of Veterinary Clinical and Animal Sciences of the University of Copenhagen, a low-cost build-it-yourself model, the SimSpay, was developed for novice training of surgical skills in canine ovariohysterectomy. The model did not require the use of trained technical staff or costly, hard-to-source supplies. The SimSpay was developed and implemented in the clinical veterinary curriculum in 2013. In 2014, 54 students participated in a questionnaire study to investigate their perception of the usefulness of the SimSpay as a learning tool. On a five-point Likert-type scale, students were asked to rate their perceived levels of competence, confidence, and anatomic knowledge before and after SimSpay training. Results demonstrate a strongly significant (p<.0001) increase in all three areas after training on the SimSpay. By increasing students' perceived levels of competence, confidence, and anatomic knowledge, the low-fidelity SimSpay is a useful, low-cost learning tool for teaching ovariohysterectomy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".