Chemical-Biological Protective Clothing: Effects of Design and Initial State on Physiological Strain
Bibliographic record
Abstract
PURPOSE: This study examined whether heat strain during low states of chemical and biological protection (CB(low)) impacted tolerance time (TT) after transition to a high state of protection (CB(high)) and whether vents in the uniform reduced heat strain during CB(low) and increased TT. METHODS: There were eight men who walked at 35 degrees C in CB(low), and then transitioned to CB(high). Subjects wore fatigues in CB(low) with an overgarment during CB(high) (F+OG) or a new 1-piece (1PC) or 2PC uniform throughout CB(low) and CB(high). One condition also tested opened vents in the torso, arms, and legs of the 2PC uniform (2PC(vent)) during CB(low); these vents were closed during CB(high). Also worn were fragmentation and tactical vests and helmet. RESULTS: Heart rates were reduced significantly during CB(low) for F+OG and 2PC(vent) (114 +/- 13) vs. 1 PC and 2PC (122 +/- 18). Rectal temperature (T(re)) increased least in CB(low) for F+OG (0.86 +/- 0.23 degree C) and was significantly lower for 2PC(vent) (1.02 +/- 0.25 degree C) vs. 2PC (1.11 +/- 0.27 degree C). T(re) increased rapidly during CB(high) for F+OG, which had the shortest TT (40 +/- 9 min). Increased thermal strain during CB(low) for 1PC negated its advantage in CB(high) and TT (46 +/- 21 min) was similar to F+OG. Differences in T(re) between 2PC and 2PC(vent) remained during CB(high) whereTT was increased during 2PC(vent) (74 +/- 17 min) vs. 2PC (62 +/- 19 min). CONCLUSIONS: It was concluded that heat strain during CB(low) impacted TT during CB(high), and use of vents reduced heat strain during CB(low), thereby increasing TT.
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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 | 0.001 |
| 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".