The impact of municipal wastewater effluent on field-deployed freshwater mussels in the Grand River (Ontario, Canada)
Bibliographic record
Abstract
To examine effects of municipal wastewater effluent (MWWE) on sentinel organisms, the authors deployed caged freshwater mussels (Lasmigona costata) in the Grand River (ON, Canada) upstream and downstream of an MWWE outfall. Passive sampling devices were deployed alongside caged mussels to confirm exposure. Biomarkers of xenobiotic biotransformation, oxidative stress, estrogenicity, and immunomodulation were investigated. Elevated concentrations of selected pharmaceutical and personal care products (PPCPs) and a natural estrogen (estrone) were found at the downstream sites. Mussels caged downstream of the effluent for 2 wk showed minimal evidence of exposure, while those deployed for 4 wk exhibited significantly higher levels of lipid peroxidation (LPO) and glutathione S-transferase (GST) activity, demonstrating that MWWE-exposed mussels exhibit increased activity in xenobiotic conjugation and oxidative stress. With respect to immune responses, a significant increase in plasma lysozyme activity and hemocyte viability was observed in MWWE-exposed mussels. Vitellogenin (vtg)-like protein in male mussels showed a trend toward induction after 4 wk of deployment at the first downstream site, but mean levels were not significantly different. Discriminant function analysis indicated that mussels deployed for 4 wk upstream and downstream of the MWWE discharge could be discriminated on the basis of LPO, GST, plasma lysozyme, and vtg responses. The physiological stress observed in caged mussels indicates that wild mussels chronically exposed to MWWE in this ecosystem would also be negatively impacted.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".