Distribution and Inventories of Polychlorinated Biphenyls in the Polar Mixed Layer of Seven Pan-Arctic Shelf Seas and the Interior Basins
Bibliographic record
Abstract
Assessment of the Arctic as a global repository of polychlorinated biphenyls (PCBs) and of uptake processes in the base of its marine food chain hinges on reliable information of PCB distribution in surface seawater, yet there is a scarcity of quality-assured PCB measurements in this key compartment. Here, surface seawater PCB concentrations and congener fingerprints are evaluated for all seven pan-Arctic shelf seas and for the interior basins. Particulate and dissolved PCBs were collected via trace-clean protocols on three basin-wide expeditions (AO-01, Beringia-2005, and ISSS-08). Concentrations of the sum of 13 abundant congeners (∑13PCB) were 0.13-21 pg/L, with higher concentrations in the shelf seas and lower concentrations in the Central Arctic Basin. Trichlorinated PCBs constituted about half of the total loadings in the Eastern Arctic (Beaufort, Chukchi, East Siberian, and Laptev Seas) and in the Central Basin, indicating an atmospheric source. In contrast, hexachlorinated PCBs were more abundant than tri-PCBs in the western sector, suggesting a role also for waterborne transport from regions of heavy PCB consumption in North America and Europe. Finally, the inventory of ∑13PCB in the polar mixed layer of the entire Arctic Ocean was 0.39 ton, which implies that only 0.0008% of historical PCB emissions are now residing in Arctic surface waters.
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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 | 0.002 | 0.002 |
| 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".