Energy intake, weight, and body composition of Canadian soldiers participating in an Arctic training
Bibliographic record
Abstract
Military training in extreme environments increases weight loss risk, which could affect soldiers’ performance. This study aimed to assess daily energy intake and requirements of Canadian Armed Forces soldiers consuming combat rations over an 8-week Arctic training and document impact on weight and body composition. Fourteen soldiers participated (males; 31.3±5.5 years). Body weight and composition were measured at different training time-points. Energy intake was measured using food diaries. Energy requirements were estimated using a predictive equation developed for the military. Fourteen soldiers participated. Weight loss was measured (3.9±3.0 kg) for 12 participants from beginning to mid-training after a week consuming combat rations. Energy intake on rations was lower than estimated daily energy requirements and resulted in energy deficits (49.8±19.2%). No body composition changes were measured. More research is needed to explore ways to make rations better adapted to reduce energy deficit and maintain soldiers’ body weight in extremely cold environments.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".