An in situ assessment of mercury contamination in the Sudbury River, Massachusetts, using transplanted freshwater mussels (<i>Elliptio complanata</i>)
Bibliographic record
Abstract
Freshwater mussels (Elliptio complanata) were transplanted into the Sudbury River, Massachusetts, to evaluate the bioavailability of total Hg and methyl mercury (MeHg) and the potential impacts to resident species. The principal Hg source is the Nyanza Superfund site, a former textile dye production facility. Mussels (initial tissue concentrations = 640 ng Hg·g dry weight-1 and 120 ng MeHg·g dry weight-1) were transplanted to eight locations in the Sudbury River watershed for 12 weeks. Tissue total Hg concentration increased significantly in mussels at the station closest to the Nyanza site (950 ng Hg·g dry weight-1). Mussel growth, which increased downstream with distance away from the site, was significantly negatively correlated with tissue concentrations of total Hg (r = -0.95) and positively correlated with average temperature (r = 0.85). Due to growth differences, uptake was best assessed by changes in content. Tissue total Hg and MeHg burdens were greatest in mussels at two stations closest to the Nyanza site, with less Hg accumulated in downstream mussels. However, the MeHg content in mussel tissue increased significantly at all Sudbury River stations, indicating that MeHg was bioavailable in all portions of the river evaluated.
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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 | 0.000 | 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".