VMSTP Combined Degree Training (VMD/PhD): Key Features of the Program at the University of Pennsylvania
Bibliographic record
Abstract
The Veterinary Medical Scientist Training Program (VMSTP), a combined degree program at the University of Pennsylvania School of Veterinary Medicine (Penn), has been in existence for approximately 35 years and has an excellent track record of producing veterinary physician-scientists. There are a number of key features of the program that I believe have been crucial to its success. Many of these features relate to how the PhD training component of the combined degree program is accomplished. Rather that describing the veterinary training component of the program, I will describe the PhD training component and how this training intersects with the veterinary curriculum. The key features of the VMSTP program at Penn are (1) admitting the right candidates, (2) placing the PhD training component of the program in the hands of individual graduate groups, (3) being committed to PhD training of veterinary students that is not compromised in terms of quality or time, (4) devising mechanisms to interdigitate VMD and PhD training to generate synergy between the programs, (5) providing continual advice to students from numerous perspectives, and (6) providing the monetary and emotional support needed for the long-term commitment students must make in order to complete the program.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.057 | 0.019 |
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".