Digitally measuring solar ultraviolet radiation in outdoor workers: A study protocol for establishing the use of electronic personal dosimeters in Portugal
Bibliographic record
Abstract
Introduction: The rising incidence of skin cancer over the years has made it a significant public and occupational health issue. However, skin cancer is highly preventable, mainly through reduced exposure to solar ultraviolet radiation (UVR), which can be achieved by a variety of individual and collective protective measures and interventions. The relative risk associated with different patterns of exposure to solar UVR differs for the subtypes of keratinocyte cancers (KC). Specifically, whether the exposure is intermittent or continuous, and occurs in an occupational or leisure/recreational setting. The main aim of the study using this protocol is to contribute to raising public and policy awareness on solar UVR-inflicted occupational skin cancers in Lisbon. This will be achieved by performing direct measurements of the solar UVR dose received by outdoor workers using a digital platform. Results will likely contribute to further understanding the risk estimates for keratinocyte cancer estimations in this population. Methods: A prospective observational study will be conducted in Lisbon, Portugal. Personal electronic dosimeters (GENESIS-UV system) integrated with a digital platform will be used to assess occupational solar UVR doses of gardeners, masons, and gravediggers of the municipality of Lisbon. Two hundred and ten outdoor workers will be selected to wear the dosimeter for 1 month each, between April and October during their daily working hours. A digital web-based platform that offers private access to information through dashboard visualization will provide information for the outdoor workers and facilitate communication with the participants. Discussion: The expected results of the overall proposal comprise the occupational solar UVR doses, expressed in standard erythemal dose (SEDs) per day of outdoor work for 7 months. Study data will provide outdoor workers with information on their personal solar UVR exposure during their working hours and an estimate of their risk of developing skin cancer. It is expected that the occupational solar UVR doses of the outdoor workers in Portugal will be above the threshold of 1 to 1.33 SED/day, due to the latitude of Lisbon and the nature of the occupations. The results prospectively should flow into the design of adequate prevention campaigns for skin cancer in outdoor workers.
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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 | 0.022 | 0.011 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.005 |
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".