Effect of simulated interior lifeboat environments on occupant thermal responses
Bibliographic record
Abstract
The effects of simulated interior lifeboat environments on the thermoregulatory responses of participants wearing immersion suits were investigated. Two different environmental conditions were investigated: the interior air temperature and relative humidity levels found in a conventional lifeboat that relies on passive ventilation (“Condition 1”); and those proposed to be in a next generation lifeboat that will have an active ventilation system (“Condition 2”). Participants performed three hour tests in both Condition 1 and Condition 2. Condition 1 produced a significantly greater increase (P < 0.05) in the rate of sweat accumulation, rate of mean skin temperature and gastro-intestinal temperature increase, heart rate, and physiological strain index values compared to Condition 2. Condition 1 caused an amount of sweat accumulation sufficient to dampen the underclothing to a level that would cause a significant reduction in predicted survival time. Heart rate, gastro-intestinal temperature and physiological strain index values continued to rise during Condition 1 suggesting that the level of thermal stress was uncompensable by the thermoregulatory systems of the participants which is supported by the air temperature and relative humidity levels being at a critical environmental limit in which heat balance cannot be achieved. It is concluded that the interior environmental conditions of conventional lifeboats that rely on a passive ventilation system will result in a level of thermal stress that cannot be compensated for by people wearing immersion suits which will result in increasing levels of physiological strain.
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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) | 0.001 | 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".