Oxybenzone contamination from sunscreen pollution and its ecological threat to Hanauma Bay, Oahu, Hawaii, U.S.A.
Bibliographic record
Abstract
Hanauma Bay is a 101-acre bay created by the partial collapse of a volcanic cone and once supported a vibrant coral reef system. It is the most popular swimming area in the Hawaiian Islands and has been reported to have averaged between 2.8 and 3.5 million visitors a year between the 1980s and the 2010s, with visitors averaging between 3000-4000 a day and peaking around 10,000-13,000 per day. Concentrations of oxybenzone and other common UV filters were measured in subsurface water samples and in sands from the beach-shower areas in Hanauma Bay. Results demonstrate that beach showers also can be a source of sunscreen environmental contamination. Hydrodynamic modeling indicates that oxybenzone contamination within Hanauma Bay's waters could be retained between 14 and 50 h from a single release event period. Focusing on only oxybenzone, two different Hazard and Risk Assessment analyses were conducted to determine the danger of oxybenzone to Hanauma Bay's coral reef system. Results indicate that oxybenzone contamination poses a significant threat to the wildlife of Hanauma Bay. To recover Hanauma Bay's natural resources to a healthy condition and to satisfactorily conserve its coral reef and sea grass habitats, effective tourism management policies need to be implemented that mitigate the threat of sunscreen pollution.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".