Evidencing the Impact of Coastal Contaminated Sediments on Mussels Through Pb Stable Isotopes Composition
Bibliographic record
Abstract
Heavily contaminated sediments are a serious concern for ecosystem quality, especially in coastal areas, where vulnerability is high due to intense anthropogenic pressure. Surface sediments (54 stations), 50 cm interface cores (five specific stations), river particles, coal and bulk Pb plate from past French Navy activities, seawater and mussels were collected in Toulon Bay (NW Mediterranean Sea). Lead content and Pb stable isotope composition have evidenced the direct impact of sediment pollution stock on both the water column quality and the living organisms, through the specific Pb isotopic signature in these considered compartments. The history of pollution events including past and present contaminant dispersion in Toulon Bay were also demonstrated by historical records of Pb content and Pb isotope ratios in sediment profiles. The sediment resuspension events, as simulated by batch experiments, could be a major factor contributing to the high Pb mobility in the considered ecosystem. A survey of Pb concentrations in surface seawater at 40 stations has revealed poor seawater quality, affecting both the dissolved fraction and suspended particles and points to marina/harbors as additional diffuse sources of dissolved Pb.
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 | 0.000 |
| 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".