Copper and nickel effects on survival and growth of northern leopard frog (<i>Lithobates pipiens</i>) tadpoles in field-collected smelting effluent water
Bibliographic record
Abstract
Trace metals can have subtle yet chronic impacts on organisms by inducing physiological stress that reduces their survival or impedes their ability to tolerate additional environmental stressors. The toxicity literature indicates, however, that aquatic organisms react differently to trace metals depending on the environments in which they reside. The objective of the present study was to understand the response of northern leopard frog (Lithobates pipiens) larvae to ionic copper (Cu), nickel (Ni), and their combination within an effluent water collected downstream of a tailings wetland area. Tadpoles were assigned randomly to 1 of 8 Cu concentrations (8-200 μg/L), 7 Ni concentrations (160-1200 μg/L), or 8 Cu and Ni combined concentrations (8:160-200:1200 μg/L) and showed significant differences in survival and life history traits among treatments. In the Cu and Cu and Ni combined treatments, tadpole survival decreased with increased Cu exposure starting at Cu = 160 μg/L and in the Ni treatment, tadpole survival decreased with increased Ni exposure starting at Ni = 650 μg/L. All Cu-exposed treatments induced a growth increase as the concentration increased, whereas the tadpoles showed a significant decrease in growth rate in Ni treatments. These contrasting outcomes suggest a plastic response to trace metals whereby tadpoles allocate energy reserves toward either escaping or coping with stress. Finally, the authors' argue that future studies will benefit from examining the impacts of multiple stressors in aquatic ecosystems to provide better environmental mitigation.
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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) | 0.001 | 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".