32. Relearning in military surgery: The contributions of Princess Vera Gedroits
Bibliographic record
Abstract
It is a well known truth that knowledge is often forgotten and has to be relearned. In medicine, this unfortunate trend is especially prevalent in the history of military surgery. The story of a Russian Princess, military surgeon, and poet, Dr. Vera Gedroits is one such forgotten story. Dr. Gedroits’ largely unrecognized contribution to military surgery was the adoption of laparotomy for penetrating abdominal wounds (PAWs). In the latter half of the 19th Century, the treatment of PAWs was controversial. However, the results of the Spanish-American (1898) and Boer (1899-1902) Wars and the outspoken opinions of prominent experts unified medical opinion; conservative treatment was clearly established as the treatment paradigm for PAWs at the birth of the 20th Century. Indeed, conservative treatment was officially adopted by the Russians at the outset of the Russo-Japanese War (1904-1905). During this war, the bold surgical practices of Dr. Gedroits would seriously challenge this standard of care. Dr. Gedroits performed operations in a converted railway car in a Red Cross hospital train. Despite these suboptimal conditions, she performed laparotomies on victims of PAWs with unprecedented success. These results, which were largely due to strict surgical indications and technical skill, effectively demonstrated the importance of laparotomy in the treatment of such wounds. As a result, the Russians adopted operative treatment as the new standard of care. Interestingly however, no other countries seemed to take any notice. Dr. Gedroits’ results were barely remarked upon and quickly forgotten. Indeed, contemporary Western observers of the Russian medical outfit, and historians since, have interpreted the surgical results of the war to support conservative management. It was not until WWI, ten years later, that surgeons relearned the utility of laparotomy. The story of Dr. Gedroits, both before and after her innovative treatment in the Russo-Japanese war, deserves remembering. Bennett J. Princess Vera Gedroits: military surgeon, poet, and author. British Medical Journal 1992; 305(6868):1532-1534. Harvard V, Hoff J. Reports of Military Observers Attached to the Armies in Manchuria during the Russo-Japanese War. London: HMSO, 1908. Wallace C. War surgery of the abdomen. Lancet 1917; 189(4885):561-5568.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.013 |
| Insufficient payload (model declined to judge) | 0.004 | 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".