Bibliographic record
Abstract
Dr. Keith Prasse is a very distinguished leader in veterinary education. He started his career achieving his BS and DVM degrees from Iowa State University (ISU). He returned to ISU after a brief period in private practice in Illinois. His well-recognized career in veterinary pathology began with his MS and PhD degrees, followed by a five-year period of teaching at ISU. Dr. Prasse joined the faculty of the University of Georgia in 1972, and thus began a long-term partnership with Dr. Bob Duncan that is arguably the foundation of veterinary clinical pathology. The textbook they authored, Veterinary Laboratory Medicine: Clinical Pathology, or "Duncan and Prasse" as it is known, remains the standard today, with later participation from Dr. Ed Mahaffey and most recently Dr. Ken Latimer. Dr. Prasse has mentored numerous graduate students and received many awards over his 23-year career in teaching, including the Norden Distinguished Teaching award twice, once at ISU and once at Georgia. His leadership as President of the American College of Veterinary Pathologists was greatly acknowledged and appreciated. Dr. Prasse's administrative service at the University of Georgia spanned 14 years, first as Associate Dean for Public Service and Outreach and later as Dean for eight years, during which time he served as President of the Association of American Veterinary Medical Colleges (AAVMC). The growth of the College of Veterinary Medicine under Dean Prasse's visionary leadership was extraordinary. He led through difficult economic and political times, yet the college and its community continued to prosper. His legacy at the University of Georgia is indelible and perpetual. His outstanding leadership of the college was recognized by the Georgia Veterinary Medical Association in 2004, when he was given the Georgia Veterinarian of the Year award. Since his retirement from Georgia, Dr. Prasse has contributed greatly to the profession and to the AAVMC by leading the Foresight project. Dr. Prasse honored those attending the 2009 AAVMC Symposium by giving the Recognition Lecture. As always, his address was inspirational, and the substance of it is included here. -Sheila W. Allen, Dean, University of Georgia College of Veterinary Medicine.
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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 | 0.016 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.012 | 0.014 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.016 | 0.029 |
| Insufficient payload (model declined to judge) | 0.029 | 0.006 |
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".