Duration limits for exposure for the whole body and extremities with a military extreme cold protection clothing ensemble at an ambient temperature of -40°C
Bibliographic record
Abstract
Manual performance and body temperature responses were assessed in a 1-h trial at an ambient temperature (TAMB) of −40°C for 7 male participants (32 ± 14 (mean ± SD) years) wearing a typical military extreme cold protection clothing ensemble. The purpose was to establish duration limited exposure (DLIM) for these conditions, and it was hypothesized that (i) core temperature (TCORE) would remain normothermic, whereas extremity skin temperature (TSK) would decrease; (ii) decrements of manual performance would be in proportion to decreases of hand TSK; and (iii) DLIM would be determined by the hand or foot TSK responses. Linear regression was employed to assess associations of manual performance scores and body temperatures with DLIM assessed using the Required Clothing Insulation (IREQ) model and extremity temperatures in ISO 11079–2007. Results showed TCORE remained at ~37.3°C, whereas there were significant (0.0001 < p < 0.05) decreases in extremity TSK. Associations between manual performance and hand TSK showed coefficients of determination (R2) ranging from 0.48 < R2 < 0.98; 0.00005 ≤ p ≤ 0.08. The DLIM for the whole-body ensemble ranged from 2.2 h to > 8 h, whereas the DLIM for the extremities was 0.56 ± 0.20 h for TSK decreasing 15°C. In conclusion, the hypotheses of a stable core temperature and decreases of extremity skin temperature giving decrements in manual performance were accepted as was the hypothesis that duration limits for exposure would be determined by extremity skin temperatures of the hand and foot.
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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 | 0.001 | 0.001 |
| 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) | 0.002 | 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".