Clothing recommendations for surviving prolonged periods in the Arctic
Bibliographic record
Abstract
In recent years the amount of ice coverage in the Arctic has receded opening up new avenues for marine vessels. Due to the economic advantages offered by these new avenues, Arctic traffic has increased and now includes cruise ships in addition to the normal commercial vessels. Recent marine accidents have called into question the impact of one in the Arctic where resources are limited and cruise ships can carry thousands of passengers who will need to survive in the harsh environment. As a result the passengers and crew of the cruise ship may be reliant on whatever supplies and equipment they carry on board with them. The thermal insulation of various clothing ensembles were measured to determine if they provided sufficient protection from hypothermia in order for people to survive in the Arctic until rescued. The thermal insulation values of the clothing ensembles were measured using thermal manikins in the following conditions: dry/still air; dry/wind; wet/still air; and wet/wind. These values were inputted into a modified version of the Cold Exposure Survival Model to give predicted survival times for 60-70 year old females, which were deemed to be the demographic that would cool the fastest. None of the clothing ensembles tested were able to provide a sufficient level of thermal protection when immersed in 0°C water. The majority of the clothing ensembles were able to provide enough thermal protection in -15°C air but only in ideal conditions. With the exception of two, all the ensembles were very sensitive to wind and wetting and would experience a significant decrease in insulation therefore greatly reducing predicted survival time. Only the ensembles that incorporated sleeping bags did not experience a significant drop in insulation when exposed to wind. It was found that a minimum in-situ clo value of 2.6 was required to ensure that people would not perish from hypothermia in the short term. The majority of the clothing ensembles tested will provide a sufficient level of thermal protection to prevent hypothermia in Arctic conditions but only if they are kept dry and out of the wind. It is recommended that these select clothing ensembles be used in conjunction with a wind break such as a tent or inflatable liferaft. Future work should investigate the possibility of creating a clothing ensemble specifically designed for survival in the Arctic that has an in-situ clo value of 2.6.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".