Development and Validation of a Feline Medial Saphenous Venipuncture Model and Rubric
Bibliographic record
Abstract
Cats are extremely popular pets with the reputation of being uncooperative for even common procedures, such as venipuncture. In this study, we sought to create and validate a cat medial saphenous venipuncture model and rubric for use in veterinary training. The validation framework consisted of content evidence, internal structure evidence, and relationship with other variables. Eleven veterinarians and veterinary technicians who were experienced with the procedure evaluated the model by means of a survey. These experienced participants, along with 25 veterinary students who were novices at the skill, performed venipuncture on the model while being digitally recorded. One hundred percent of the experienced participants and 88% of the novices reported that the model was helpful for teaching feline medial saphenous venipuncture. They identified a few areas for continued improvement, including increasing the blood flow rate and decreasing the vessel wall rigidity. Experienced users’ rubric scores were significantly higher than novice students’ (experienced, M = 13.4; novice M = 16.5; p = .05), suggesting that the model’s features were adequate to differentiate the performances of various users. Internal consistency of the eight-item rubric was acceptable at .74. These results supported validation of the cat medial saphenous model and rubric for use in veterinary education.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".