Dr. Mladen Vranic—A Legend in Diabetes Research: 1930–2019
Bibliographic record
Abstract
Mladen Vranic, MD, DSc, FRSC, FRCP(C), FCAHS, was an early pioneer in the field of diabetes, greatly advancing our understanding of diabetes physiology. Over the course of his scientific career, Dr. Vranic changed the landscape of diabetes research in North America and internationally through his groundbreaking work in glucose metabolism, exercise, stress, and hypoglycemia. It is noteworthy that he trained as the last postdoctoral fellow of Dr. Charles Best, a codiscoverer of insulin, at the University of Toronto. Dr. Vranic’s interest in diabetes research started during his early life, as did his determination to thrive despite deep struggles. He was born 30 April 1930 to Vladamir and Ana Vranic in Zagreb, Croatia. His father was a professor at the Faculty of Economics, Engineering, and Sciences and dean at the School of Economics and Engineering at the University of Zagreb. His teaching specialty was mathematics. Mladen was an only child, of Jewish heritage, and a Holocaust survivor. He and his family narrowly escaped capture by the Nazis multiple times during World War II. As a young boy he, his parents, and his grandmother sought refuge in Italy, managing to flee just ahead of their would-be captors. Despite their efforts, they were eventually caught and sent to a concentration camp when Mladen was 11. He attributed his survival there to his and his family’s undeterred tenacity to endure and escape. Mladen Vranic Upon completing medical school at the University of Zagreb, Mladen pursued graduate studies in physiology, with a focus on diabetes, the only specialty available in the department at the time. Concomitantly, his father developed type 2 diabetes. Mladen said about the field that was to become his life’s work and passion, “I have never regretted for one instant my commitment to a life in medical research and education” and “diabetes …
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.024 | 0.021 |
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".