Influence of Salinity and Dissolved Organic Carbon on Acute Cu Toxicity to the Rotifer <i>Brachionus plicatilis</i>
Bibliographic record
Abstract
Acute copper (Cu) toxicity tests (48-h LC50) using the euryhaline rotifer Brachionus plicatilis were performed to assess the effects of salinity (3, 16, 30 ppt) and dissolved organic carbon (DOC, ∼ 1.1, ∼ 3.1, ∼ 4.9, ∼ 13.6 mg C L(-1)) on Cu bioavailability. Total Cu was measured using anodic stripping voltammetry, and free Cu(2+) was measured using ion-selective electrodes. There was a protective effect of salinity observed in all but the highest DOC concentrations; at all other DOC concentrations the LC50 value was significantly higher at 30 ppt than at 3 ppt. At all salinities, DOC complexation significantly reduced Cu toxicity. At higher concentrations of DOC the protective effect increased, but the increase was less than expected from a linear extrapolation of the trend observed at lower concentrations, and the deviation from linearity was greatest at the highest salinity. Light-scattering data indicated that salt induced colloid formation of DOC could be occurring under these conditions, thereby decreasing the number of available reactive sites to complex Cu. When measurements of free Cu across DOC concentrations at each individual salinity were compared, values were very similar, even though the total Cu LC50 values and DOC concentrations varied considerably. Furthermore, measured free Cu values and predicted model values were comparable, highlighting the important link between the concentration of bioavailable free Cu and Cu toxicity.
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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".