Development and Student Evaluation of an Anatomically Correct High-Fidelity Calf Leg Model
Bibliographic record
Abstract
Obstetrical chain placement requires location of specific landmarks and a certain dexterity that must be practiced. Use of low-fidelity models may not always provide students with a realistic experience. In this study we developed an anatomically correct high-fidelity calf leg model that would serve as a better teaching model for pre-clinical veterinary students than a pre-existing low-fidelity polyvinyl chloride (PVC) model. One hundred and twenty pre-clinical veterinary students were instructed how to use obstetrical chains with a low-fidelity PVC model and the anatomically correct high-fidelity calf leg model. After a 45-minute lab, students were surveyed on their experience with both models. Overall students felt the anatomically correct high-fidelity calf leg model increased accuracy in chain placement and provided more accurate landmarks, a more realistic model, and more real-life scenario training.
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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 | 0.007 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".