SMHS to present Doctor of Medicine degrees
Bibliographic record
Abstract
GRAND FORKS, N.D.—The University of North Dakota School of Medicine and Health Sciences will confer the Doctor of Medicine (MD) degree during commencement at 2:30 p.m. on Sunday, May 15, at the Chester Fritz Auditorium on the UND campus in Grand Forks. Seventy-two degree candidates will participate in the ceremony. The graduates have completed four years of medical education to earn their Doctor of Medicine, beginning with two years of instruction at the UND campus in Grand Forks, followed by two years learning and working with practicing physicians who volunteer to serve as their teachers in hospitals and clinics throughout North Dakota. Upon graduating, the doctors will complete their residencies, a period of advanced intensive training in their chosen medical specialty before independent practice as a physician. Depending on the medical specialty, medical school graduates complete anywhere from three to seven years of residency training after medical school. Patrick Carr, PhD, associate professor in the Department of Biomedical Sciences at the School of Medicine and Health Sciences, will deliver the keynote address titled “Everything You Need to Know You Learned in Anatomy.” Carr was raised in western Manitoba and completed his undergraduate education at Brandon University and a doctoral degree in physiology at the University of Manitoba. He then completed further training at the University of Manitoba, the National Institutes of Health in Bethesda, Md., and at Wright State University in Dayton, Ohio. He joined the University of North Dakota in 1998, where he is currently the director of Education Resources and assistant dean for Faculty Development for the School of Medicine and Health Sciences. Medical students have honored Carr with over 30 teaching awards. His teaching responsibilities currently include gross anatomy and neuroscience. When not at work, he can often be found encouraging medical students to join him at hockey, mountain biking or playing guitar.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.611 | 0.413 |
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".