A Physiologically Based Biotic Ligand Model for Predicting the Acute Toxicity of Waterborne Silver to Rainbow Trout in Freshwaters
Bibliographic record
Abstract
An early silver−gill binding model using conditional equilibrium binding constants ( K ) was fitted to actual toxicity data for rainbow trout ( Oncorhynchus mykiss ) and subsequently modified to produce a mechanistically based acute toxicity model for predicting silver toxicity. The model used an “off the shelf” aquatic geochemistry software program (MINEQL + ) and physiologically based log K values to predict the acute effects of waterborne silver in rainbow trout. The final version of the model does not predict total gill−silver loading, as the early model did, but rather predicts the binding of Ag + to key toxic sites on the gill and incorporates the effects of cation competition at these sites. The acute toxicity model for Ag + provided the best fit to toxicity data when a log K value for the affinity of these sites was 7.6 with cationic competition log K values for Na + and Ca 2+ of 2.9 and 2.3, respectively. A log K for Ag−DOM of 9.0 was used representing strong Ag + binding to dissolved organic matter. The model we present is easy to use and provides a good match with previously published acute AgNO 3 toxicity data for rainbow trout from 31 data sets in 10 studies. The modified model is now ready for full verification with a greater range of laboratory and natural waters.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.005 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 teacher head, 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".