Bibliographic record
Abstract
Environmental context. Mercury is a neurotoxin that bioaccumulates and is associated with global contamination and often with regional atmospheric sources. However, in Connecticut, USA, in watersheds characterised by a gradient of forested to urban land uses we found that the predominant source of elevated Hg is local. This study uses a novel nested sampling method to pinpoint hot spots of mercury and presents inorganic mercury concentrations in water, sediment, soil, and aquatic organisms. The results indicate that mercury contamination is an environmental legacy associated with the silver plating industry and that local sources are critical to the biogeochemical mercury cycle here. Abstract. Mercury levels were measured in various environmental compartments of the Quinnipiac River system (CT, USA). In streams, dissolved mercury reached a maximum of 6.3 ng L–1 during baseflow and 30 ng L–1 during stormflow, whereas surficial impoundment sediments had a maximum mercury concentration of 420 µg kg–1. A sediment core collected from the Quinnipiac River indicates that peak loading of mercury occurred before 1940. Wharton Brook tributary of the Quinnipiac River represents 30% of the mercury loading to the river and the likely source of mercury to the sediment is a past silver manufacturing plant. Analysis of soil samples from the riparian zone of Wharton Brook, a tributary of concern because it empties into a popular fishing location, revealed mercury concentrations as high as 20 000 µg kg–1. It appears that the soil surrounding the former factory is acting as the current source of mercury to the water column and aquatic communities. Removal of contaminated soil will probably be necessary to reduce mercury levels and the threat to humans in downstream environments.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.004 | 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 teacher head, 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".