Evaluation of the protective effects of reactive sulfide on the acute toxicity of silver to rainbow trout (<i>Oncorhynchus mykiss</i>)
Bibliographic record
Abstract
Acute 96-h toxicity tests were performed with juvenile rainbow trout (Oncorhynchus mykiss) exposed to AgNO3 in either the absence or the presence of 100 nM reactive sulfide to evaluate the protective effect of aqueous sulfides against ionic Ag toxicity. The sulfide was presented in the form of zinc sulfide (ZnS) clusters under oxic conditions. Silver was lost from the water column during the course of the experiment, so mean measured Ag concentrations were used to generate all median lethal concentration (LC50) data. The system was complicated in that Ag2S precipitated because of the need for large amounts of Ag to obtain lethal effects in the presence of ZnS. Some of the losses of Ag could be explained by complexation with ZnS and formation of solid Ag2S. Other losses were probably the result of partial adsorption to exposure-chamber walls or to complexation with ligands or functional groups within organic material produced by the fish. The LC50 (95% confidence interval) values generated using measured concentrations for total Ag were 139 (122-162) nM in the absence of sulfide and 377 (340-455) nM in the presence of 100 nM sulfide. The LC50 values generated using measured concentrations from filtered (pore size, 0.45 microm) water samples were 122 (105-145) nM in the absence of sulfide and 225 (192-239) nM in the presence of 100 nM sulfide. These results suggest a stoichiometric protection of sulfides up to a 2:1 ratio of Ag:sulfide. Greater accumulation of Ag at the gills was measured in fish exposed to AgNO3 in the presence of sulfide.
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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".