Wet military uniforms pose low risk of hypothermia while static in mild cold air
Bibliographic record
Abstract
Wet clothing is less insulative than dry clothing and consequently increases heat loss in cold air. Tactical necessity can render removal of wet clothing impossible and/or require Warfighters to remain static to avoid detection, limiting heat production and posing a threat of hypothermia (core temperature <35 °C). This study aimed to characterize body temperatures and evaluate hypothermia risk while statically exposed to 5 °C air wearing three wet military uniforms. Further, low-speed loaded walking was evaluated as a strategy to raise end-static temperatures. Twelve adults (11 M, 1 F) randomly completed three wet-cold trials wearing either the Improved Hot Weather Combat Uniform (IHWCU), Army Combat Uniform (ACU), or ACU with silk-weight base layer (ACU+). Each trial involved 180 min of cold air (5.3 ± 0.3 °C, 0.8 m·s−1) exposure after a clothed 2 min head-out immersion (34.0 ± 0.2 °C). Volunteers were static for 60 min followed by 120 min of walking with a rucksack. Rectal temperature ( Tre) area under the curve did not differ among the three wet uniforms when static ( p = 0.431) with Tre increasing, rather than decreasing, across the 60 min (IHWCU: +0.26 ± 0.19 °C, ACU: +0.37 ± 0.21 °C, ACU+: +0.36 ± 0.20 °C). Hypothermia risk with 60 min static wet-cold exposure therefore appears minimal, regardless of the military uniform worn, in an otherwise low stress cohort. End-static finger temperatures (IHWCU: 9.48 ± 2.30 °C, ACU: 9.99 ± 1.82 °C, ACU+: 9.27 ± 1.66 °C, p > 0.999) were reduced by ∼20–23 °C posing a considerable dexterity concern. Heat production of ∼210 W·m2 appeared sufficient to begin to reverse negative cumulative heat storage and initiate slight elevations of rectal and peripheral temperatures, although finger temperatures increased <2 °C after 120 min. ClinicalTrials.gov ID: NCT05409937.
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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 | 0.000 |
| 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) | 0.003 | 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".