Bioavailability of sediment-associated mercury to<i>Hexagenia</i>mayflies in a contaminated floodplain river
Bibliographic record
Abstract
We examined the bioavailability of mercury in sediments from the contaminated Sudbury River (Massachusetts, U.S.A.). Mayfly nymphs (Hexagenia) were exposed in four 21-day bioaccumulation tests to contaminated and reference sediments (treatments) from reservoirs, flowing reaches, palustrine wetlands, and a riverine lake. Mean total mercury (ΣHg) ranged from 880 to 22 059 ng·g dry weight-1in contaminated sediments and from 90 to 272 ng·g-1in reference sediments. Mean final concentrations of methyl mercury (MeHg) in test water were greatest (8-47 ng Hg·L-1) in treatments with contaminated wetland sediments, which had mean ΣHg ranging from 1200 to 2562 ng·g-1. In mayflies, final mean concentrations of MeHg were highest in treatments with contaminated wetland sediments (122-183 ng Hg·g-1), intermediate in treatments with contaminated sediments from reservoirs, flowing reaches, and a riverine lake (75-127 ng Hg·g-1), and lowest in treatments with reference sediments (32-41 ng Hg·g-1). We conclude that the potential entry of MeHg into the benthic food chain was greater in contaminated palustrine wetlands than in the contaminated reservoirs, which had the most contaminated sediments.
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 | 0.000 | 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) | 0.001 | 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".