On the Rate of Decline of Persistent Organic Contaminants in Lake Trout (<i>Salvelinus namaycush</i>) from the Great Lakes, 1970−2003
Bibliographic record
Abstract
Thirty-four years of data from the Great Lakes Fish Monitoring Program (GLFMP) show significant changes in the behavior of most contaminants in lake trout over time consistent with changes in contaminant inputs following regulation and remediation. Polybrominated diphenyl ethers (PBDEs) show positive apparent first-order rate constants falling to near zero. Dieldrin shows relatively unchanging half-lives of around 10 years except in Lake Superior (∼25 years). Mirex, consistently detected only in Lake Ontario fish, shows a slow decrease until the 1990s, when remediation of a source site occurred, after which half-lives are 2−3 years. Half-lives of oxychlordane, polychlorinated biphenyls (PCBs), and dichloro-diphenyl-trichlorethane (DDT) and its metabolites were typically 3−6 years until the mid 1980s; since then, the newest data confirm half-lives are usually around 15−30 years. For PCBs, an increasing half-life is found in other media as well. Changes in food web structure, fishery dynamics, and climate undoubtedly affect concentrations but cannot explain observed long-term trends across several media. Concentrations of legacy contaminants in the Great Lakes are likely to continue to decline only slowly and pose a health concern for decades without identifying and containing remaining sources.
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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.221 | 0.001 |
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; both teacher heads agree on what is shown here.
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".