Characterization and Interpolation of Sediment Polychlorinated Biphenyls and Polybrominated Diphenyl Ethers in Resident Killer Whale Habitat along the Coast of British Columbia, Canada
Bibliographic record
Abstract
Abstract The northeastern Pacific northern and southern resident killer whale (Orcinus orca) populations are listed as threatened and endangered in Canada, respectively, with persistent, bioaccumulative contaminants, such as polychlorinated biphenyls (PCBs) and polybrominated diphenyl ethers (PBDEs), posing threats to their recovery. Concentrations of PCBs and PBDEs in subtidal surface sediments collected from 97 sites along the British Columbia (BC) coast were used to identify their distribution and profiles, and to assess killer whale habitat quality. Victoria Harbour (VH3(site ID: 1)) sediments exhibited the highest PCB and PBDE concentrations. For PCBs, PCB-138 was found at the highest concentration, followed by PCB-153, PCB-110, PCB-149, PCB-101, and PCB-118. For PBDEs, individual congeners were ranked as follows: BDE-209 > BDE-207 > BDE-206 > BDE-208 > BDE-47 > BDE-99. Principal component analyses (PCA) illustrated the variations in contaminant profiles, with PC1 for PCBs and PBDEs correlated with the octanol-water partition coefficient (log KOW, p < 0.003). Based on the PCA, sediment particle size, total organic carbon (TOC), and water depth at collection were other factors associated with the distribution of PBDEs, while PCB profiles were associated with TOC. Total PCB and PBDE concentrations at 100% and 34% of the sites, respectively, exceeded the recently adopted British Columbia's Ministry of Environment and Climate Change Strategy Working Sediment Quality Guidelines (PCBs 3.7 pg/g dry wt and PBDEs 1000 pg/g dry wt), considered protective of killer whales. Our findings suggest that the legacy of banned PCBs and PBDEs has the potential to constrain the recovery of killer whales as a result of their mobilization from sediments and consequent uptake by marine food webs. Environ Toxicol Chem 2022;41:2139–2151. © 2022 SETAC
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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 | 0.002 |
| 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".