Future Directions in Training Zoological Medicine Veterinarians
Bibliographic record
Abstract
The American College of Zoological Medicine (ACZM) is dedicated to excellence in furthering the health and well-being of both captive and free-ranging wild animals. Currently there are 14 ACZM-approved residency programs in zoological medicine. In addition, eight non-approved residencies and 15 internships in North America provide training opportunities in this field. This article outlines some of the training opportunities for both veterinary students and graduate veterinarians that would best position them for entry into a zoological medicine training program. Although there is a growing number of opportunities for individuals to serve in captive and free-ranging wildlife health positions, existing training programs are inadequate to meet these needs. It is also acknowledged that there is an increasing number of veterinary students entering veterinary schools with an interest in zoological medicine and that the job market is still limited. However, positions and opportunities in zoological medicine are available for those individuals with the drive, dedication, and passion to succeed.
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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 | 0.018 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.015 | 0.006 |
| Insufficient payload (model declined to judge) | 0.046 | 0.008 |
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".