Bibliographic record
Abstract
Most historians agree that modern plastic surgery was born out of the efforts of reconstructive surgeons in World War I (WW I). In a single British hospital, over 8000 wounded soldiers were treated for disfiguring facial wounds. These gruesome injuries provided surgeons with enough cases to make unprecedented advances in tissue reconstruction. After the war, however, surgeons returned to civilian society where they found relatively few cases to support their new niche. In England, plastic surgery failed to establish itself while, in the United States, plastic surgeons had much greater success in founding their new specialty. Emphasizing this trend is the staggering statistic that, at the outbreak of World War II (WW II), the US boasted 60 trained plastic surgeons compared with only 4 in Britain. This article analyzes a variety of primary sources (speeches, journal articles, letters, and live interviews) obtained from several libraries and special collections to argue that the relative success of US plastic surgery in the interwar period (1920-1940) can be attributed to (1) the efforts of pioneering American plastic surgeons (Varaztad Kazanjian, Vilray Blair, and John Davis), (2) the post-Flexner report restructuring of US medical training, and (3) a much warmer reception both by the US public and general surgical community to plastic surgery.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 0.001 |
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".