Application of<i>Ceriodaphnia dubia</i>for whole effluent toxicity tests in the hawkesbury–nepean watershed, New South Wales, Australia: Method development and validation
Bibliographic record
Abstract
Abstract Use of Ceriodaphnia dubia for whole effluent toxicity testing programs is widespread in North America. However, the methods used for this species in the United States and Canada have not been validated in Australia for use in local waters with the local variant of the species. Consequently, we compared the effects of container size and volume, diet, and dilution water on the survival and reproduction of the local variant of C. dubia (the Sydney clone). We also evaluated the results of control performance and reference toxicant tests with potassium chloride and diazinon obtained over the course of a whole effluent toxicity testing program conducted on effluents discharged from sewage treatment plants into the Hawkesbury–Nepean drainage basin. Our data indicate that the general guidelines published by the U.S. Environmental Protection Agency for conducting acute and chronic toxicity tests with C. dubia can be successfully applied to the Sydney clone with minor modifications and that both acute and chronic tests can be conducted with a high degree of success, provided that appropriate procedures are followed. Moreover, tests with a variety of chemicals indicated that the Sydney clone responded comparably to its North American counterparts, suggesting that existing databases for C. dubia can be applied to the Sydney clone. In addition, the use of test volumes between 20 and 200 ml did not affect the acute toxicity of the organophosphorous pesticide diazinon to this strain.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".