Bioaccumulation and toxicity of uranium, arsenic, and nickel to juvenile and adult <i>Hyalella azteca</i> in spiked sediment bioassays
Bibliographic record
Abstract
Uranium (U) mining and milling release arsenic (As), nickel (Ni) and U to receiving waters, which accumulate in sediments. The objective of the present study was to investigate if As, Ni, and U concentrations in tissue residue of Hyalella azteca, overlying water, sediment porewater, and solids could predict juvenile and adult survival and growth in conditions similar to lake sediments downstream of U mines and mills. We conducted 14-d static sediment toxicity tests spiked with U, As, and Ni salts. For U, we spiked uranyl nitrate with sodium bicarbonate to limit U precipitation once in contact with circumneutral sediment. The median lethal concentrations for As, Ni, and U of juveniles and adults based on measured concentrations in sediments were 134 and 165 μg/g, 370 and 787 μg/g, and 48 and 214 μg/g, respectively. Adult survival and growth linearly decreased with increasing bioaccumulation. For juveniles, metal accumulation linearly predicted survival. We calculated median lethal body concentrations for juveniles and adults of 5 and 36 μg As/g, 14 and 49 μg Ni/g, and 0.4 and 1.0 μg U/g. The concentrations of As, Ni, and U in tissue residue leading to a 20% decrease in adult growth were 32 μg As/g, 44 μg Ni/g, and 1 μg U/g. Overall, the present study showed that U was the most toxic element, followed by As and Ni; that juveniles were more sensitive to the 3 metals tested than adults; and that threshold body concentrations can support assessment of benthic invertebrate community impairment. Environ Toxicol Chem 2018;37:2340-2349. © 2018 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.
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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".