Tactical Combat Casualty Care in the Canadian Forces: lessons learned from the Afghan war
Bibliographic record
Abstract
Tactical Combat Casualty Care (TCCC) is intended to treat potentially preventable causes of death on the battlefield, but acknowledges that application of these treatments may place the provider and even the mission in jeopardy if performed at the wrong time. Therefore, TCCC classifies the tactical situation with respect to health care provision into 3 phases (care under fire, tactical field care and tactical evacuation) and only permits certain interventions to be performed in specific phases based on the danger to the provider and casualty. In the 6 years that the Canadian Forces (CF) have been involved in sustained combat operations in Kandahar, Afghanistan, more than 1000 CF members have been injured and more than 150 have been killed. As a result, the CF gained substantial experience delivering TCCC to wounded soldiers on the battlefield. The purpose of this paper is to review the principles of TCCC and some of the lessons learned about battlefield trauma care during this conflict.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".