Long‐term changes in legacy trace organic contaminants and mercury in Lake Ontario salmon in relation to source controls, trophodynamics, and climatic variability
Bibliographic record
Abstract
We used long‐term (20+ yr) datasets to determine how the sum of 209 polychlorinated biphenyl congeners ([ΣPCB]), dodecachloropentacyclodecane ([mirex]), para‐para dichlorodiphenyltrichloroethane ([ p,p'‐DDT]), and total mercury ([Tot‐Hg]) concentrations have changed in Lake Ontario chinook salmon (Oncorhynchus tshawytscha, 1983‐2003) and coho salmon (Oncorhynchus kisutch, 1976‐2003). Exponential decay models best describe temporal reductions of persistent organic pollutant concentrations [POPs], including [ΣPCB], [mirex], and [p,p'‐DDT], in chinook (r2 = 0.68‐0.77, p < 0.001) and coho (r2 = 0.68‐0.87, p < 0.001) salmon over the record. In comparison, declines in [Tot‐Hg] were slight, with linear models best describing trends (r2 = 0.49‐0.50, p = <0.001‐0.001). Rapid declines of [POPs] from the mid‐1970s through the early 1980s were attributed mostly to Canada‐United States bans on usage and sedimentation; subsequent concentration oscillations were linked to salmonine stocking and nutrient abatement programs, climatic cycles, and alewife (Alosa pseudoharengus) population dynamics.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".