Environmental fractionation of PCBs and PBDEs during particle transport as recorded by sediments in coastal waters
Bibliographic record
Abstract
The Strait of Georgia (British Columbia, Canada) is a hydrologically complex inland sea with a rich abundance and diversity of species of aquatic life. Marine sediments, as both a sink for hydrophobic contaminants and a potential source for aquatic food webs, were collected from 41 sites throughout the 6,900-km(2) Strait of Georgia. The congener-specific concentrations of polychlorinated biphenyls (PCBs) and polybrominated diphenyl ethers (PBDEs), including BDE-209, were measured. Urban harbors represented hotspots for both PCBs and PBDEs, whereas PBDEs were also found at high concentrations near municipal outfalls. Patterns of PCB distribution were consistent with historical point source emissions in urban areas and environmental distillation toward lighter profiles in remote sites over time. The single congener BDE-209 dominated the PBDEs, accounting for 52% of the average total concentration. However, nonurban deep-water sediment PBDE profiles were both heavier and had higher concentration-weighted average log K(OW) (octanol-water partition coefficient) values compared to shallow samples (percent BDE-209 of total PBDE, 66 versus 32%; log K(OW) , 9.5 versus 8.2, respectively). Collectively, our results suggest that although source signals largely explain PCB and PBDE hotspots in the Strait of Georgia, the combination of physicochemical properties and environmental processes drive divergent compositional fates for the PCBs and the heavier PBDEs in the sediments of the Strait of Georgia.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".