Dioxin-like contaminants are no longer a risk to the American eel (<i>Anguilla rostrata</i>) in Lake Ontario
Bibliographic record
Abstract
The embryotoxicity of extracts of American eels (Anguilla rostrata) was measured to determine whether maternally derived contaminants contribute to the declining recruitment of eels to Lake Ontario. Sexually maturing, large yellow and silver eels were sampled in 2007 and 2008 from 5 locations in eastern Canada, including Lake Ontario; positive controls included eels from the Hudson River, United States, and Canal Dessel-Schoten, Belgium (European eel, Anguilla anguilla). Japanese medaka eggs were injected immediately after fertilization with 1 or 10 nL of eel extract and, after 12 d, scored for signs of toxicity. Eel extracts did not cause dioxin-like embryotoxicity, reflecting the low concentrations of total dioxin equivalents measured chemically in these same extracts. Embryo mortality and reduced hatching success at high doses of eel extracts may reflect the bioaccumulation of legacy or emerging chemicals of concern. The results were consistent with long-term trends of declining concentrations of persistent organic pollutants (POPs) in tissues of eels and other fish species from Lake Ontario, trends of declining embryotoxicity of eel tissue extracts, and recent increases of recruitment of juvenile eels to Lake Ontario. If dioxin-like compounds contributed in the past to the decline of recruitment and abundance of American eels in Lake Ontario, these data suggest that recruitment should recover, following the same trends as the recovery of lake trout reproduction in Lake Ontario. Environ Toxicol Chem 2018;37:1061-1070. © 2017 SETAC.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".