Examining Model Predictions of Zinc and Copper Aqueous Speciation and Freshwater Ecotoxicity: Case Study of Ross Lake, Flin Flon, Manitoba, Canada
Bibliographic record
Abstract
Models of aqueous metal speciation and ecotoxicity have become commonplace due to their ability to estimate metal behaviour. This study evaluated commonly used aqueous geochemical speciation and ecotoxicity models with application to a mine impacted lake in northern Manitoba. \nThe geochemical speciation model Winderemere Humic Aqueous Model (WHAM) was compared with Diffusive Gradients in Thinfilm (DGT) measurements of zinc and copper. DGT measurements in the water column corresponded well with WHAM-estimated Zn2+, Cu2+ was off by up to 100x. Additional metal, either from small organic bound species or dissolution of metal sulphides from resuspended sediment, served to improve model estimates. \nThe single metal Biotic Ligand Model (BLM) predicted acute toxicity to Daphnia magna attributable to copper but not zinc, at low pH (3.55 – 5.5). Comparison of results did not show a significant difference between the single and mixture BLMs, suggesting a non-interactive effect on metal toxicity for measured water chemistry.
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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 | 0.000 | 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) | 0.002 | 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".