Toxicity of fluoride to aquatic species and evaluation of toxicity modifying factors
Bibliographic record
Abstract
The present study was performed to investigate the toxicity of fluoride to a variety of freshwater aquatic organisms and to establish whether water quality variables contribute substantively to modifying its toxicity. Water hardness, chloride, and alkalinity were tested as possible toxicity modifying factors for fluoride using acute toxicity tests with Hyalella azteca and Oncorhynchus mykiss. Chloride appeared to be the major toxicity modifying factor for fluoride in these acute toxicity tests. The chronic toxicity of fluoride was evaluated with a variety of species, including 3 fish (Pimephales promelas, O. mykiss, and Salvelinus namaycush), 3 invertebrates (Ceriodaphnia dubia, H. azteca, and Chironomus dilutus), 1 plant (Lemna minor), and 1 alga (Pseudokirchneriella subcapitata). Hyalella azteca was the most sensitive species overall, and O. mykiss was the most sensitive species of fish. The role of chloride as a toxicity modifying factor was inconsistent between species in the chronic toxicity tests.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".