Simulation of the migration of dissolved contaminants through a subaqueous capping layer: model development and application for As migration
Bibliographic record
Abstract
TRANSCAP-1D is a numerical model that simulates the vertical migration of dissolved contaminants through a subaqueous capping layer. The model was developed for the prediction of the long-term effectiveness of a sediment cap. It considers advection, diffusion, chemical reactions, and the effect of the burrowing activity of the benthic fauna. The sediment is represented as a dual porosity medium composed of sediment pores and biologically formed tubes. The numerical model was calibrated with the concentration profiles of dissolved arsenic measured in the sediments at two sampling stations in the Saguenay Fjord, in Québec, Canada, where a major flood event caused the natural capping of contaminated sediments. Thereafter several numerical simulations with variable bio-irrigation depth and variable thickness of the capping layer were performed to test the effect of the uncertainty and variability of the input values on the model response. These simulations indicate that the depth of bio-irrigation in the sediment and the release from mineral dissolution are major factors controlling the distribution of dissolved contaminants in the sediment column. Key words: Saguenay Fjord, migration, numerical model, capping layer, sediment, bio-irrigation, heavy metals, arsenic.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".