Impact of environmentally based chemical hardness on uranium speciation and toxicity in six aquatic species
Bibliographic record
Abstract
Treated effluent discharge from uranium (U) mines and mills elevates the concentrations of U, calcium (Ca), magnesium (Mg), and sulfate (SO4 (2-) ) above natural levels in receiving waters. Many investigations on the effect of hardness on U toxicity have been experiments on the combined effects of changes in hardness, pH, and alkalinity, which do not represent water chemistry downstream of U mines and mills. Therefore, more toxicity studies with water chemistry encountered downstream of U mines and mills are necessary to support predictive assessments of impacts of U discharge to the environment. Acute and chronic U toxicity laboratory bioassays were realized with 6 freshwater species in waters of low alkalinity, circumneutral pH, and a range of chemical hardness as found in field samples collected downstream of U mines and mills. In laboratory-tested waters, speciation calculations suggested that free uranyl ion concentrations remained constant despite increasing chemical hardness. When hardness increased while pH remained circumneutral and alkalinity low, U toxicity decreased only to Hyalella azteca and Pseudokirchneriella subcapitata. Also, Ca and Mg did not compete with U for the same uptake sites. The present study confirms that the majority of studies concluding that hardness affected U toxicity were in fact studies in which alkalinity and pH were the stronger influence. The results thus confirm that studies predicting impacts of U downstream of mines and mills should not consider chemical hardness. Environ Toxicol Chem 2015;34:562-574. © 2014 The Authors. Published by Wiley Periodicals, Inc. on behalf of SETAC.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.002 | 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 teacher head, 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".