Comparison of thermal manikins to human thermoregulatory responses
Bibliographic record
Abstract
Immersion suits are lifesaving appliances (LSA) designed to protect the wearer if they become accidently immersed in cold water by reducing the cold shock response and delaying the onset of hypothermia. Immersion suits are certified to both national and international standards; some of which require the thermal protective properties to be tested using humans or thermal manikins. The ethical nature of testing with humans has been questioned [ 1 ] due to the physically grueling nature of these tests, thus testing with manikins may be preferential. However, previous work has shown that discrepancies exist between thermal manikins and humans that could result in immersion suit selection that would benefit the former more than the latter who would ultimately use it [ 2 ]. This study investigated the thermoregulatory responses of humans and compared them to a thermal manikin while wearing immersion ensembles with insulation distributed in various configurations hypothesized to be beneficial to humans and manikins.
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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) | 0.003 | 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".