Habitat-Based PCB Environmental Quality Criteria for the Protection of Endangered Killer Whales (<i>Orcinus orca</i>)
Bibliographic record
Abstract
The development of an area-based polychlorinated biphenyl (PCB) food-web bioaccumulation model enabled a critical evaluation of the efficacy of sediment quality criteria and prey tissue residue guidelines in protecting fish-eating resident killer whales of British Columbia and adjacent waters. Model-predicted and observed PCB concentrations in resident killer whales and Chinook salmon were in good agreement, supporting the model's application for risk assessment and criteria development. Model application shows that PCB concentrations in the sediments from the resident killer whale's Critical Habitats and entire foraging range leads to PCB concentrations in most killer whales that exceed PCB toxicity threshold concentrations reported for marine mammals. Results further indicate that current PCB sediment quality and prey tissue residue criteria for fish-eating wildlife are not protective of killer whales and are not appropriate for assessing risks of PCB-contaminated sediments to high trophic level biota. We present a novel methodology for deriving sediment quality criteria and tissue residue guidelines that protect biota of high trophic levels under various PCB management scenarios. PCB concentrations in sediments and in prey that are deemed protective of resident killer whale health are much lower than current criteria values, underscoring the extreme vulnerability of high trophic level marine mammals to persistent and bioaccumulative contaminants.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".