Dissolved Fraction of Standard Laboratory Cladoceran Food Alters Toxicity of Waterborne Silver to Ceriodaphnia dubia
Bibliographic record
Abstract
The biotic ligand model (BLM) for the acute toxicity of cationic metals to aquatic organisms incorporates the toxicity-modifying effects of dissolved organic matter (DOM), but the default parameterization (i.e., assuming 10% of DOM is humic acid) does not differentiate DOM from different sources. We exposed a cladoceran (Ceriodaphnia dubia) to Ag in the presence of DOM from filtered YCT (standard yeast-Cerophyll(R)-trout chow food recommended by the U.S. Environmental Protection Agency [EPA] for cladocerans), from the Suwannee River (GA, USA; relatively little anthropogenic input), and from the Desjardins Canal in Hamilton (ON, Canada; receives treated municipal wastewater effluent). In all three treatments, the dissolved organic carbon (DOC) concentration was 2 mg/L (the concentration following addition of YCT slurry at the U.S. EPA-recommended volume ratio). The average 48-h median effects concentration (EC50) ratios for dissolved Ag in the presence and absence of DOM [i.e., (EC50 with DOM)/(EC50 without DOM)] were as follows: Suwannee River, 1.6; Desjardins Canal, 2.2; and YCT filtrate, 26.8. Therefore, YCT filtrate provided much more protection against Ag toxicity than that provided by DOM from the surface waters. The major spectral characteristic that differentiated YCT filtrate from the other two types of DOM was a strong tryptophan peak in the excitation- emission matrix for YCT. These results have important implications for interpreting Ag toxicity tests in which organisms are fed YCT, and they suggest BLM-calculated toxicity predictions might be improved by incorporating specific chemical constituents or surrogate indices of DOM. Another component of the protective effect against Ag toxicity, however, might be that the dissolved fraction of YCT served as an energy and/or nutrient source for C. dubia.
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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".