Occurrence and Biomagnification of Polychlorinated Naphthalenes and Non- and Mono-<i>ortho</i> PCBs in Lake Ontario Sediment and Biota
Bibliographic record
Abstract
Biota and surface sediments collected from Lake Ontario were analyzed for polychlorinated naphthalenes (PCNs) and non- and mono-ortho-substituted polychlorinated biphenyls (n/ m-o-PCBs) to compare bioaccumulation behavior of these classes of dioxin-like chemicals in a food web from the Great Lakes. Mean sigmaPCN concentrations (tri-octaCN) ranged from 14 +/- 9 pg/g in plankton to 3500 +/- 3200 pg/g (wet weight) in lake trout while sediments contained from 21 to 38 ng/g (dry weight). Principal components analysis of PCN congener patterns indicated that chlorine substitution determined which congeners favored accumulation (e.g., CN-42, -52, -60, -66, -67, and -73), while others may be subject to metabolism. The bioaccumulative congeners exhibited similar trophic magnification factors (TMFs; 1.23-1.42) and biomagnification factors (BMFs; 5.5-8.6) to the n/m-o-PCBs for the trout/weighted diet relation, although BMFs for a benthic feeding relationship (slimy sculpin/Diporeia) indicated that the n/m-o-PCBs were more bioavailablethroughthe benthic pathway. PCNs contribute significantly to the burden of dioxin-like compounds in Lake Ontario biota, contributing between 12 and 22% of total PCN + PCB TEQ in lake trout and up to 69% in benthic organisms.
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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 | 0.000 |
| Scholarly communication | 0.000 | 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".