Influence of salinity and organic carbon on the chronic toxicity of silver to mysids (<i>Americamysis bahia</i>) and silversides (<i>Menidia beryllina</i>)
Bibliographic record
Abstract
Tests were conducted with mysids (Americamysis bahia) and silversides (Menidia beryllina) to evaluate the influence of salinity and organic carbon on the chronic toxicity of silver. During 7- and 28-d tests conducted at 10, 20, and 30% per hundred salinity, higher concentrations of dissolved silver generally were required to cause a chronic effect as the salinity of the seawater was increased. The 28-d mysid and silverside 20%-effective concentration values (expressed as dissolved silver) ranged from 3.9 to 60 and from 38 to 170 microg/L, respectively, over the salinity range. This pattern was not observed when the same test results were evaluated against the concentrations of free ionic silver (measured directly during toxicity tests), as predicted by the free-ion activity model. Increasing the concentration of dissolved organic carbon from 1 mg/L to the apparent maximum achievable concentration of 6 mg/L in seawater caused a slight decrease in chronic toxicity to silversides but had no effect on the chronic toxicity to mysids. The possible additive toxicity of silver in both food and water also was investigated. Even at the maximum achievable foodborne concentration, the chronic toxicity of silver added to the water was not affected when silver was also added to the food, based on the most sensitive endpoint (growth). However, although fecundity was unaffected at all five tested concentrations during the test with silver in water only, it was significantly reduced at the two highest waterborne silver concentrations (12 and 24 microg/L) during the test with silver dosed into food and water.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".