Exposure of Arctic Field Scientists to Ultraviolet Radiation Evaluated Using Personal Dosimeters
Bibliographic record
Abstract
Abstract During July 2000 we used an electronic personal dosimeter (X-2000) and a biological dosimeter (Deutsches Zentrum für Luft- und Raumfahrt: Biofilm) to characterize the UV radiation exposure of arctic field scientists involved in biological and geological fieldwork. These personnel were working at the Haughton impact structure on Devon Island (75°N) in the Canadian High Arctic under a 24 h photoperiod. During a typical day of field activities under a clear sky, the total daily erythemally weighted exposure, as measured by electronic dosimetry, was up to 5.8 standard erythemal dose (SED). Overcast skies (typically 7–8 okta of stratus) reduced exposures by a mean of 54%. We estimate that during a month of field activity in July a typical field scientist at this latitude could potentially receive ∼80 SED to the face. Because of body movements the upper body was exposed to a UV regimen that often changed on second-to-second timescales as assessed by electronic dosimetry. Over a typical 10 min period on vehicle traverse, we found that erythemal exposure could vary to up to 87% of the mean exposure. Time-integrated exposures showed that the type of outdoor field activities in the treeless expanse of the polar desert had little effect on the exposure received. Although absolute exposure changed in accordance with the time of day, the exposure ratio (dose received over horizontal dose) did not vary much over the day. Under clear skies the mean exposure ratio was 0.35 ± 0.12 for individual activities at different times of the day assessed using electronic dosimetry. Biological dosimetry showed that the occupation was important in determining daily exposures. In our study, scientists in the field received an approximately two-fold higher dose than individuals, such as medics and computer scientists, who spent the majority of their time in tents.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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 teacher head, 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".