Dr Henry Shimizu: The Journey of a Canadian Plastic Surgeon, Advocate, and Artist
Bibliographic record
Abstract
Dr Henry Shimizu was a dedicated Canadian plastic surgeon with Japanese roots who spent his career practicing in Edmonton at the University of Alberta Hospital. He relished the opportunity to share his expertise by training residents and medical students. Dr Shimizu completed his plastic surgery training in the United States and was central to establishing the plastic surgery training program in Edmonton. Beyond clinical practice, Dr Shimizu was a prominent advocate in his community, serving as the Chairman of the Redress committee for Japanese internment. As a talented painter, he had produced magnificent oil paintings based on childhood recollections as an internee in the Slocan Valley. Dr Shimizu has made significant contributions to Canadian plastic surgery serving as president of the Canadian Society of Plastic Surgeons in 1978. His clinic work and dedication to the community at large were recognized with the Order of Canada in 2004 and more recently an honorary degree from the University of Victoria. Dr Shimizu continues to golf, paint, and travel in his retirement. He is happily married to his wife Joan and is the proud father of 4 children and 6 grandchildren.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.020 | 0.004 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.010 |
| Insufficient payload (model declined to judge) | 0.033 | 0.008 |
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".