The Effect of an Ovariohysterectomy Model Practice on Surgical Times for Final-Year Veterinary Students’ First Live-Animal Ovariohysterectomies
Why this work is in the frame
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Bibliographic record
Abstract
This study evaluated whether one supervised simulated ovariohysterectomy (OVH) using a locally developed canine OVH model, decreased surgical time for final-year veterinary students’ first live-animal OVH. We also investigated student perceptions of the model as a teaching aid. Final-year veterinary students were exposed to an OVH model (Group M, n = 48) and compared to students without the exposure (Group C, n = 58). Both groups were instructed similarly on performing an OVH using a lecture, student notes, a video, and a demonstration OVH performed by a veterinary surgeon. Students in Group M then performed an OVH on the model before performing a live-animal OVH. Students in Group C had no exposure to the OVH model before performing a live-animal OVH. Surgical time data were analyzed using linear regression. Students in Group M completed a questionnaire on the OVH model after performing their first live-animal OVH. The OVH model exposure reduced students’ first canine live-animal OVH surgery time ( p = .009) for students without prior OVH experience. All students ( n = 48) enjoyed performing the procedure on the mode; students practicing an OVH on the model felt more confident (92%) and less stressed (73%) when performing their first live-animal OVH. Results suggest that the canine OVH model may be helpful as a clinical training tool and we concluded that the OVH model was effective at decreasing students’ first OVH surgical time.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it