Speciation, behavior, and bioavailability of copper downstream of a mine-impacted lake
Bibliographic record
Abstract
A combination of Cu speciation analysis and toxicity testwork was conducted to assess the behavior, speciation, and bioavailability of Cu in a stream system rich in dissolved organic carbon (DOC) downstream of a mine-impacted lake (East Lake, ON, Canada). Elevated levels (approximately 50 microg/L) of Cu exist in the lake due to the release of dissolved Cu to the water column from underlying sediments. Most of the Cu present in East Lake and downstream is present as filterable species that represent 74 to 100% of the total. Measurements of labile Cu as measured by diffusive gradients in thin films (DGT) suggest that most of the Cu is unavailable to aquatic biota. The DGT results indicate that 9 to 24% of Cu within the receiving environment is biologically available. Decreases in the labile Cu fraction with distance downstream of East Lake correlate well with increases in the concentration of DOC (r(2) = 0.79-0.95), presumably due to the progressive importance of Cu-organic complexes. The relationship between filterable Cu and SO(4)(2-) downstream of East Lake was linear (r(2) = 0.99) for all sampling periods, suggesting that decreases in filterable Cu concentration downstream of East Lake could be attributed solely to dilution (i.e., conservative behavior). Variations in the filterable Cu concentration resulting in 50% mortality (LC50 = 96-203 microg/L) and the concentration resulting in an inhibition of reproduction by 25% (IC25 = 75-156 microg/L) with respect to Ceriodaphnia dubia (7-d incubation) in Cu-spiked solutions could be explained by differences in labile-Cu concentrations as determined by DGT. The considerable complexation capacity afforded by lake and stream waters can be attributed to complexation of Cu with abundant DOC (7-17 mg/L). The relevance of the toxicity data to water-effect ratio testwork, and the associated development of site-specific water quality objectives, are discussed.
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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) | 0.000 | 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".