Distribution, hydrologic transport, and cycling of total mercury and methyl mercury in a contaminated river-reservoir-wetland system (Sudbury River, eastern Massachusetts)
Bibliographic record
Abstract
Riparian wetlands contaminated with Hg from an industrial point source were found to be important sites of production and release of methyl mercury (MeHg) in a 40-km reach of the Sudbury River in eastern Massachusetts. Stream discharge and concentration measurements were used to calculate annual mean loads for total Hg (ΣHg) and MeHg in contaminated river reaches, a reservoir, and a riparian wetland downstream from the industrial source. Budgets based on these loads indicate that the annual mean ΣHg load increased sixfold in a reach receiving flow from the point source, but the annual mean MeHg load did not increase. About 23% of the ΣHg load was removed by sedimentation during flow through the reservoir. Net production of MeHg in the reservoir was similar to that reported elsewhere for lakes receiving Hg from atmospheric deposition only. ΣHg concentrations and loads increased significantly as the river passed through the riparian wetland reach. On the basis of flooded wetland area, net production of MeHg was 15 times greater in the wetland reach than in wetland-associated drainages described in other studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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".