An Observational Study of Personal Ultraviolet Dosimetry and Acute Diffuse Reflectance Skin Changes at Extreme Altitude
Bibliographic record
Abstract
OBJECTIVE: To determine the level of UV radiation at extreme altitude and to assess the effect it has on the skin. METHODS: Fifteen expeditioners and 10 Sherpas were assessed during a climbing expedition on the north side of Mt Everest (8848 m). UV exposure measurement and diffuse skin reflectance spectrophotometry were performed at the beginning and end of the expedition. RESULTS: Over the course of the expedition, the expeditioners and Sherpas received a median dose of 93.6 (interquartile range [IQR], 61.0-102.8) and 102.5 (IQR, 72.2-117.8) minimal erythemal doses (MEDs) of UV radiation. The maximum dosage exceeded 106 ± 1.4 MEDs. Using reflectance spectrophotometry, expeditioner and Sherpa melanin-hemoglobin increased by 83.6% (IQR, -1.5 to 89.8%) and 24.7% (IQR, -22.4 to 61.5%) for exposed skin, respectively. The amount of subcutaneous lipid-water decreased by a factor of 196.6 (IQR, 52.1-308.4) and 46.7 (IQR, 1.8-1156.5), for expeditioners and Sherpas, respectively. CONCLUSIONS: This expedition's participants received massive doses of UV radiation during their time at high altitude. In many individuals this was similar to the annual exposure of northern European office-workers (100 MEDs). Diffuse skin reflectance spectroscopy revealed considerable subcutaneous lipid loss, skin dehydration, and increased melanin in keeping with these levels of exposure.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".