Surgery under siege: A case study of leg amputation in 18th century Louisbourg, Nova Scotia, Canada
Bibliographic record
Abstract
OBJECTIVE: Paleopathological analysis of a below-knee amputation was conducted to explore the sociocultural reasons why the amputation took place. MATERIALS: Older adolescent male (18-21 years) from the New Englander mass burial at the 18th century Fortress of Louisbourg. METHODS: Macroscopic assessment and archival data. RESULTS: A surgical amputation of the right tibia and fibula, distal to the knee was identified. The cross-sectional diaphysis of the leg has kerf marks and a splinter (breakaway point) at the posterior-lateral border of the tibia suggesting the leg gave way from its own weight or was manually removed once most of the sawing was complete. CONCLUSIONS: Archival records suggest frostbite from prolonged exposure to freezing temperatures and trauma from unsafe working conditions at the Fortress were the main causes that led to amputation. SIGNIFICANCE: This case study highlights the importance of contextualizing cases of amputation to understand factors leading to the amputation procedure and techniques used in the past, and the social and living conditions of the individual. LIMITATIONS: Observations were restricted to skeletal material as soft tissue decomposed and there was no material evidence suggestive of amputation associated with this individual in their grave. SUGGESTIONS FOR FUTURE RESEARCH: Full trauma assessment of the Fortress of Louisbourg skeletal collection to provide additional insight into injury sustained at Louisbourg and 18th century surgical practices.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".