Heightened Biological Uptake of Polybrominated Diphenyl Ethers Relative to Polychlorinated Biphenyls Near-Source Revealed by Sediment and Plankton Profiles along a Coastal Transect in British Columbia
Bibliographic record
Abstract
Polychlorinated biphenyl (PCB) and polybrominated diphenyl ether (PBDE) concentrations and profiles in paired sediment-plankton samples were determined along a 500 km transect in coastal British Columbia, Canada. PCB and PBDE levels in sediment were both greater in the industrialized Strait of Georgia than in remote northern sites and exhibited parallel spatial trends. In plankton, recent-use PBDE levels were higher near-source, while levels of legacy PCBs were uniform across sites. Principal component analysis of 95 PCB congeners illustrated the influence of proximity to source (i.e., latitude) on congener patterns for both matrices (sediment, r(2) = 0.52, p = 0.012; plankton, r(2) = 0.59, p = 0.016). The PCB pattern in plankton grew lighter with latitude, but the opposite pattern in sediments suggested that temperature-related fractionation, sediment processes, and basin-wide oceanography had divergent effects on each matrix. Biota-sediment accumulation factors (BSAFs) were greater for PBDEs than PCBs, but spatial profiles were similar; PCBs and PBDEs were near equilibrium in remote atmospherically driven sites (BSAF = 1.7 and 1.3) but accumulated preferentially in sediments at source-driven sites (BSAF = 0.2 and 0.4). The influences of particle-binding and hydrophobicity on the aquatic fate of PCBs and PBDEs was evident by the strong influence of log KOW on congener-specific BSAFs (PCBs, r(2) = 0.18 p < 0.001; PBDEs, r(2) = 0.61 p < 0.001). While biotic uptake of PCBs has become spatially uniform in coastal BC because of dilution over time, biomagnification of PBDEs remains higher in industrialized 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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".