Energy expenditure and intake during Special Operations Forces field training in a jungle and glacial environment
Bibliographic record
Abstract
The purpose of this study was to identify and compare energy requirements specific to Special Operations Forces in field training, in both cool and hot environments. Three separate training sessions were evaluated, 2 in a hot environment (n = 21) and 1 in a cool environment (n = 8). Total energy expenditure was calculated using doubly labeled water. Dietary intake was assessed via self-report at the end of each training mission day, and macronutrient intakes were calculated. Across the 3 missions, mean energy expenditure (4618 ± 1350 kcal/day) exceeded mean energy intake (2429 ± 838 kcal/day) by an average of 2200 kcal/day. Macronutrient intakes (carbohydrates (g/(kg·day body weight (bw)) −1 ) = 3.2 ± 1.2; protein (g/(kg·day bw) −1 ) = 1.3 ± 0.7; fat (g/(kg·day bw) −1 ) = 1.2 ± 0.7) showed inadequate carbohydrate and possibly protein intake across the study period, compared with common recommendations. Total energy expenditures were found to be similar between hot (4664 ± 1399 kcal/day) and cool (4549 ± 1221 kcal/day) environments. However, energy intake was found to be higher in the cool (3001 ± 900 kcal/day) compared with hot (2200 ± 711 kcal/day) environments. Based on the identified energy deficit, high variation in energy expenditures, and poor macronutrient intake, a greater attention to feeding practices during similar training scenarios for Special Operations Forces is needed to help maintain performance and health. The differences in environmental heat stress between the 2 climates/environments had no observed effect on energy expenditures, but may have influenced intakes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 teacher head, 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".