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 (r 2 = 0.68‐0.77, p < 0.001) and coho (r 2 = 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 (r 2 = 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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 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 teacher head, 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".