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Record W2109427563 · doi:10.1016/j.wem.2013.05.007

An Observational Study of Personal Ultraviolet Dosimetry and Acute Diffuse Reflectance Skin Changes at Extreme Altitude

2013· article· en· W2109427563 on OpenAlexaff
Ivy Cheng, Alex Kiss, Lothar Lilge

Bibliographic record

VenueWilderness and Environmental Medicine · 2013
Typearticle
Languageen
FieldMedicine
TopicSkin Protection and Aging
Canadian institutionsUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsInterquartile rangeAltitude (triangle)ReflectivityMedicineSurgeryOptics

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.407
Threshold uncertainty score0.655

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.063
GPT teacher head0.299
Teacher spread0.235 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2013
Admission routes1
Has abstractyes

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