Toxicity of α-, β-, (α+β)-endosulfan and their formulated and degradation products to <i>Daphnia magna, Hyalella azteca, Oncophynchus mykiss, Oncophynchus kisutch</i>, and biological implications in streams
Bibliographic record
Abstract
The static acute toxicities of alpha-endosulfan, beta-endosulfan, (alpha + beta)-endosulfan, endosulfan sulfate (their transformation product), and formulated materials were determined for a representative freshwater amphipod (Hyalella azteca), cladoceran (Daphnia magna), and salmonid fish (Oncorhynchus mykiss). Acute lethality tests also were conducted on these organisms and coho salmon (Oncorhynchus kisutch) by exposing them to simulated field water endosulfan concentrations, using either a single compound and/or in combinations. As well, growth/survival bioassays of H. azteca were carried out in simulated sediment endosulfan concentrations that were detected in farm ditches contiguous to fish streams in the Lower Fraser Valley (BC, Canada). All materials tested were very highly toxic to these nontarget aquatic indicator organisms. As the most potent compound, alpha-endosulfan is about 1.3, 6.6, and 58 times more toxic than the beta-isomer to Daphnia, rainbow trout, and Hyalella, respectively. Some possible biological and toxicological implications of our findings are discussed in the context of endosulfan concentrations found in farm ditches flowing to fish streams in the Lower Fraser Valley.
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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 | 0.000 | 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 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".