A meaningful legacy: urologists as Nobel Prize laureates.
Bibliographic record
Abstract
OBJECTIVE: To review the careers of two urologists among Nobel Prize-winners in medicine, W. Forssmann and C. H. Huggins, and the significance of their contributions. MATERIAL AND METHODS: Investigation was performed based on analysis of collected findings from the biographies of laureates, their scientific publications and the Nobel archive database. RESULTS: Review revealed that of the 175 scientists and physicians who received the Nobel Prize, just over one half (94) held an MD degree while the remainder were PhD's or other degrees. Of the 94 MD-degreed physicians nine (9.4%) were surgeons. Two of these laureates were urologists- Drs. Werner Forssmann and Charles B. Huggins, who were awarded the Nobel Prize in 1956 and 1966, respectively. Although Werner Forssmann worked as a urologist for most of his career, early in his surgical training he invented procedures for cardiac catheterization and performed the first procedures on himself in 1929. Charles Huggins identified the role of androgens in prostate cancer progression in 1940, and thus established the principles of hormonal suppressive therapy for advanced disease. CONCLUSIONS: The distinguished accomplishments of these two great urologists exemplify the highest level of excellence in science for the entire surgical and urological community. Furthermore, today's breakthroughs in molecular medicine represent an extremely appealing challenge for the new generation of scientists and clinicians.
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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 | 0.006 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".