Fu-Chan Wei—Surgeon, Innovator, and Leader of the Legendary Chang Gung Microsurgery Center
Bibliographic record
Abstract
Fu-Chan Wei is a world-renowned plastic and reconstructive surgeon. He is clearly one of the most influential and innovative surgeons in the history of plastic surgery. The Taiwanese legend is the innovator of the osteoseptocutaneous fibula flap, which revolutionized the reconstruction of composite bone and soft tissue defects in the jaw and extremities. He has pioneered several perforator flaps, including the free style variety. He has taken toe-to-hand microsurgical transplantation to a whole new level. He is not only recognized for his surgical skills and clinical innovations, but also for his vision, leadership, and teaching. The establishment and development of the famous Microsurgery Center at Chang Gung Memorial Hospital is unparalleled anywhere. The international fellowship program in microsurgery there remains the envy of all microsurgical trainees. Dr. Wei and his colleagues have trained and influenced more than 1,500 surgeons from all over the world. The aim of this video article is to share what we learned by interviewing Fu-Chan Wei at Chang Gung. The story of Fu Chan Wei, his colleagues, and the development of the Microsurgery Center in Taiwan is worth knowing.
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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 | 0.001 | 0.003 |
| 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 | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 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".