Relationships between total mercury in sediments and methyl mercury in the freshwater gastropod prosobranch <i>Bithynia tentaculata </i> in the St. Lawrence River, Quebec
Bibliographic record
Abstract
Total Hg concentrations in sediment and methyl mercury (MeHg) levels in the gastropod species Bithynia tentaculata were evaluated at 21 stations in the fluvial corridor of the St. Lawrence River (Quebec, Canada). In the sediments (n = 21), total Hg concentrations ranged from 34 to 2790 ng·g dry weight-1. In the gastropods, MeHg concentrations varied from 15 to 290 ng·g dry weight-1 in undepurated gastropods (n = 20) and from 41 to 420 ng·g dry weight-1 in depurated gastropods (n = 13; without gut contents). The southern sector of Lake St. Louis, located near the Îles-de-la-Paix, had significantly higher Hg concentrations than any other sectors under study, both for total Hg in the sediments and MeHg in the gastropods. We established linear models to describe the relationships between Hg contamination in sediments and molluscs for the fluvial corridor of the St. Lawrence River and for the Lake St. Louis sector. Total Hg in sediments and MeHg in gastropods were highly correlated for all pooled stations (r = 0.83), and the relationship was even stronger for the Lake St. Louis stations (r = 0.92). Our study suggests that the gastropod B. tentaculata is a promising biomonitor species for assessing Hg contamination in the fluvial corridor and lakes of the St. Lawrence River.
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 | 0.001 | 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".