Nutrition Education in European Veterinary Schools: Are European Veterinary Graduates Competent in Nutrition?
Bibliographic record
Abstract
Knowledge of nutrition is vital for veterinarians to inform owners about care of healthy pets and management of disease. Owners wish to have information from the veterinary health care team (VHT), and graduate veterinarians should be sufficiently educated to provide evidence-based information. Many veterinary practitioners feel that their veterinary school education in small-animal nutrition was insufficient. This survey presents the information on nutrition education in 63 European veterinary schools, including attitudes about teaching of nutrition, importance of nutrition, satisfaction of graduate performance and skills in nutrition, existing and required curriculum hours in nutrition, existing and required teaching staff, and barriers to achieving adequate teaching. The questionnaire was provided online to university deans and faculty members. The majority of schools felt that nutrition was important, but lacked staff numbers or knowledge to teach adequately. Many were also restricted by a crowded curriculum. Potential solutions include hiring a nutritionist, outsourcing nutrition education, and/or using online materials.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".