A comparison of the transport and fate of polychlorinated biphenyl congeners in three great lakes food webs
Bibliographic record
Abstract
A food web bioaccumulation model was used to compare transport and fate of polychorinated biphenyls (PCB) congeners in three food webs in the Laurentian Great Lakes of North America. The model was used to quantify the contribution of sediment-derived and freely dissolved PCBs to the body burden of aquatic biota. In eastern Lake Erie (OH, USA), almost 100% of the chemical body burden of biota originates from sediment. In western Lake Erie, benthic invertebrates accumulated slightly more than half of their PCB body burden from sediment while fish accumulated less than half of their chemical body burden from sediment. Fish from Lake Ontario, Canada, accumulated less than 30% of their body burden of PCB congeners with log Kow < 6.4 from sediment and approximately half of their body burden of PCB congeners with log Kow > or = 6.4 from sediment. Field data and the model were also used to determine the effects of declining concentrations of PCBs in water and sediment on concentrations of PCBs in aquatic biota. Results indicate that, as concentrations of PCB congeners in the ecosystem decline, the role of sediment as the source of contaminant to aquatic biota increases. Furthermore, as sediment becomes the predominant source of contaminant to aquatic biota. the concentration of PCB congeners in biota tends to equilibrium with bottom sediment.
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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 | 0.001 |
| 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) | 0.000 | 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".