UV filters bioaccumulation in fish from Iberian river basins
Bibliographic record
Abstract
The occurrence of eight organic UV filters (UV-Fs) was assessed in fish from four Iberian river basins. This group of compounds is extensively used in cosmetic products and other industrial goods to avoid the damaging effects of UV radiation, and has been found to be ubiquitous contaminants in the aquatic ecosystem. In particular, fish are considered by the scientific community to be the most feasible organism for contamination monitoring in aquatic ecosystems. Despite that, studies on the bioaccumulation of UV-F are scarce. In this study fish samples from four Iberian river basins under high anthropogenic pressure were analysed by liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). Benzophenone-3 (BP3), ethylhexyl methoxycinnamate (EHMC), 4-methylbenzylidene camphor (4MBC) and octocrylene (OC) were the predominant pollutants in the fish samples, with concentrations in the range of ng/g dry weight (d.w.). The results indicated that most polluted area corresponded to Guadalquivir River basin, where maximum concentrations were found for EHMC (241.7 ng/gd.w.). Sediments from this river basin were also analysed. Lower values were observed in relation to fish for OC and EHMC, ranging from below the limits of detection to 23 ng/gd.w. Accumulation levels of UV-F in the fish were used to calculate biota-sediment accumulation factors (BSAFs). These values were always below 1, in the range of 0.04-0.3, indicating that the target UV-Fs are excreted by fish only to some extent. The fact that the highest concentrations were determined in predators suggests that biomagnification of UV-F may take place along the freshwater food web.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".