Contrasting effects of chloride on growth, reproduction, and toxicant sensitivity in two genetically distinct strains of<i>Hyalella azteca</i>
Bibliographic record
Abstract
The strain of Hyalella azteca (Saussure: Amphipoda) commonly used for aquatic toxicity testing in the United States has been shown to perform poorly in some standardized reconstituted waters frequently used for other test species. In 10-d and 42-d experiments, the growth and reproduction of the US laboratory strain of H. azteca was shown to vary strongly with chloride concentration in the test water, with declining performance observed below 15 mg/L to 20 mg/L. In contrast to the chloride-dependent performance of the US laboratory strain of H. azteca, growth of a genetically distinct strain of H. azteca obtained from an Environment Canada laboratory in Burlington, Ontario, Canada, was not influenced by chloride concentration. In acute toxicity tests with the US laboratory strain of H. azteca, the acute toxicity of sodium nitrate increased with decreasing chloride in a pattern similar not only to that observed for control growth, but also to previous acute toxicity testing with sodium sulfate. Subsequent testing with the Burlington strain showed no significant relationship between chloride concentration and the acute toxicity of sodium nitrate or sodium sulfate. These findings suggest that the chloride-dependent toxicity shown for the US laboratory strain may be an unusual feature of that strain and perhaps not broadly representative of aquatic organisms as a whole.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".