Bibliographic record
Abstract
Advances have been made in expanding veterinary curricula to deliver basic key knowledge and skills necessary for provision of health care to captive and companion non-domestic or non-traditional species in the veterinary colleges of the United States and Canada. These advances were in large part facilitated by the deliberations and recommendations of the White Oak Accords. Though a five-year review of curricular opportunities at US and Canadian veterinary colleges shows that progress has been made in implementing the recommendations of the White Oak Accords, there remains room for improvement. The broadly comparative and health-maintenance basis of zoological medicine contributes critically to the potential for veterinary medicine to make important contributions to the concept of the integrated health of the planet. Emergence of key zoonotic and production-animal diseases derived from and within wildlife populations since 2000 has increased awareness worldwide of the importance of zoological medicine in protecting both production livestock and public health. These areas are addressed in elective curricula at colleges emerging as centers of excellence in zoological medicine, but it is critical that core curricula in zoological medicine at all schools be strengthened to include these important areas to prepare our DVM/VMD graduates to protect companion-animal, production-animal, and public health.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.019 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.041 | 0.004 |
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".