Retention of Heavy Metals in the Post '96 Flood Sediment Layer Deposited in the Saguenay River, Quebec, Canada
Bibliographic record
Abstract
In July 1996 during a 50 year event flood, a new layer of sediments composed of debris, gravel and fine materials was transported and deposited over an ancient, one meter contaminated layer of sediments in the Saguenay River Fjord and Ha! Ha! Bay floors. During the Industrial Revolution years, various metallurgic, plastic, aluminum and pulp and paper production industries discharged their wastes on these waters, resulting in the high contamination of both water and sediments. This contamination limited the exploitation of fish and seafood. Given that the new layer is composed essentially of cleaner material, the zone is presenting important changes in the direction of a healthier environment. The Canadian Government and some of the surrounding industries aim to assess the new potential of the zone and its environmental safety. At present, it represents over a million-dollar study. This part of the Saguenay project aimed to recognize and evaluate the capacity of the new layer to contain and retain the contaminants left at the bottom layer. Particular interest is given to mercury and to heavy metals such as Pb, Zn, Cd, and Ni and to their geochemical distribution among natural adsorbing materials such as clays, oxides, carbonates and organic matter. The paper presents the recognition and sampling mission on the Alcide Horth Ship, the contamination profiles given in two dimensions (length and depth), the geochemical distribution of heavy metals on the contaminated layer, transition layer and new layer as well as the evolution of their retention and transfer. Discussion and relations with common sediment characteristics such as grain size, cation exchange capacity and surface area are also given. Sequential selective extraction has been used jointly with scanning electron microscopy (SEM) to study heavy metal species.
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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 | 0.002 |
| Science and technology studies | 0.003 | 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) | 0.002 | 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".