Ambient solar UV radiation and seasonal trends in potential sunburn risk among schoolchildren in South Africa
Bibliographic record
Abstract
Background. The detrimental effects of excess personal solar ultraviolet (UV) radiation exposure include sunburn, immunosuppression and skin cancer. In South Africa, individuals with minimum natural protection from melanin, including fair-skinned individuals and African albinos, and people spending extended unprotected periods outdoors are at risk of sunburn, a risk factor for skin cancer. Sunburn becomes increasingly likely during the high solar UV radiation hours around midday, and previous studies have shown that children are exposed to potentially high, sunburn-causing solar UV radiation levels while at school. Method. To estimate national potential child sunburn risk patterns, monitored ambient solar UV radiation levels at six sites in South Africa were converted into possible schoolchild solar UV radiation exposures by calculating the theoretical child exposure to 5% of the total daily ambient solar UV radiation as derived from personal child exposure studies. Results. Schoolgoing children with skin types I, II and III were identified as being at greatest risk of sunburn. There were 44 and 99 days in a year when schoolchildren with skin type III (moderately sensitive) living in Durban and De Aar, respectively, would be likely to experience sunburn. Schoolchildren with skin type I (extremely sensitive) were at risk of experiencing sunburn on 166 days in De Aar, and those with skin types I and II were at risk on at least 1 day per year at all six locations. Conclusion. Seasonal patterns show that schoolchildren with sensitive skin types may experience sunburn in spring, summer and autumn months. Differences in child sunburn risk were evident, mainly due to latitude and atmospheric aerosols. Additional factors affecting sunburn risk include schoolchildren’s use of sun protection, sun-exposed activity, and timing and duration of exposure. Understanding risk patterns and obtaining locally relevant information will assist South African skin cancer prevention and sun protection awareness
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".