Estimating sediment quality thresholds to prevent restrictions on fish consumption: Application to polychlorinated biphenyls and dioxins–furans in the Canadian Great Lakes
Bibliographic record
Abstract
Sediment quality thresholds (SQTs) are used by a variety of agencies to assess the potential for adverse impact of sediment-associated contaminants on aquatic biota, typically benthic invertebrates. However, sedimentary contaminants can also result in elevated fish contaminant levels, triggering consumption advisories that are protective of humans. As such, SQTs that would result in fish concentrations below consumption advisory levels should also be considered. To illustrate how this can be addressed, we first calculate biota sediment accumulation factors (BSAFs) for polychlorinated biphenyls (total PCB) and polychlorinated dioxins-furans (PCDD/Fs) in the Canadian Great Lakes using measured lake sediment and fish tissue concentrations in 4 fish species, namely, lake trout, whitefish, rainbow trout, and channel catfish. Using these BSAFs and tissue residue values for fish consumption advisories employed by the Ontario Ministry of the Environment (OMOE, Canada), we derive fish consumption advisory-based SQTs (fca-SQTs) that are likely to result in fish tissue residues that are safe to eat without restriction. The PCDD/Fs fca-SQTs ranged from 6 to 128 pg toxic equivalents (TEQ)/g dry weight (dw) and were above the Canadian Council of the Ministers of the Environment (CCME) threshold effect level (TEL) of 0.85 pg TEQ/g dw. In contrast, the total PCB fca-SQTs ranged from 1 to 60 ng/g dw and were generally below the CCME's TEL of 34.1 ng/g and OMOE's lowest effect level (LEL) of 70 ng/g; however, they were consistent with the OMOE's no effect level (NEL) of 10 ng/g. The fca-SQTs derived using the BSAF as well as food chain multiplier (FCM) approach for a smaller scale system (Hamilton Harbour in Lake Ontario) corresponded well with average lakewide Lake Ontario fca-SQTs. This analysis provides approximate sediment concentrations necessary for reducing fish consumption advisories for each of the Canadian Great Lakes and emphasizes the impacts of historical lake sediment contamination on fish advisories. We believe that this approach merits consideration in sediment guideline development.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".