Levels of Occupational Exposure to Solar Ultraviolet Radiation in Vancouver, Canada
Bibliographic record
Abstract
INTRODUCTION: Outdoor workers are at high risk of exposure to solar ultraviolet radiation (UVR), a known human carcinogen. In Canada, no objective measures of UVR exposure are available for occupational settings. METHODS: The Outdoor Workers Project collected UVR exposure data among outdoor workers in Vancouver, Canada during the summer of 2013. Objective measures of exposure were taken for one week using calibrated electronic UVR dosimeters. Additional data was collected from workers on skin cancer risk factors, family history of skin cancer, and job type; as well as meteorological data for sampling days. Marginal models were constructed to examine the worker, job and meteorological determinants of UVR exposure levels, as measured in standard erythemal dose (SED). RESULTS: Seventy-eight workers were recruited, of which 73 had at least 1 day of measured UVR exposure for this analysis. Participants were mostly male, young and Caucasian. Mean exposure (corrected for repeated measures) was 1.08 SED. Exposure measures were highly variable even in the same workplace, ranging from 0.01 SED to 19.2 SED. Younger age, working in land-based construction, and sunnier weather forecasts led to higher levels of UVR exposure. CONCLUSIONS: Exposure levels capable of causing sunburn were common in this study of outdoor workers, in a location not typically associated with high sun 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 | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".