Aluminum-dominated acute toxicity to the cladoceran<i>Ceriodaphnia dubia</i>in neutral waters downstream of an acid mine drainage discharge
Bibliographic record
Abstract
Acid mine drainage (AMD) is traditionally considered to impact aquatic ecosystems by acidification, metal precipitation smothering stream substrates, and sediment toxicity in association with trace metals. Using Ceriodaphnia dubia as a test organism, we conducted whole effluent toxicity (WET) tests with both field-collected and laboratory-synthesized AMD samples to investigate possible mechanisms of reduced benthic macroinvertebrate community diversity in neutral (pH > 7.0) waters downstream of an acidified tributary. Our results indicate that Al and Fe in transition from acidic waters to neutralizing receiving streams can cause acute toxicity to standard invertebrate test organisms at neutral pH. Aluminum, with an average LC50(50% lethal concentration) of 2880 µg·L1, was determined to be the cause of acute toxicity in the field for up to a mile downstream of the AMD-influenced tributary and was the likely cause of reduced community diversity at those sites. Although Fe singly may cause acute toxicity in this type of system, it appears to reduce the toxicity of combinations of other metals such as Al, Cu, and Zn.
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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".