Experimental assessment of Athabasca River cohesive sediment deposition dynamics
Bibliographic record
Abstract
Polycyclic aromatic hydrocarbons (PAHs) originating from natural sources, and potentially from the Athabasca Oil Sands development, are of concern for the Athabasca River and Lake Athabasca delta ecosystems. In order to model the transport of fine sediments (and associated PAHs), it is important to describe the sediment dynamics within the river system. Flocs possess different settling characteristics compared to individual particles. A key aspect in modelling floc settling behaviour is the mathematical linkage of the floc density to floc size. In this paper, a rotating annular flume is used to determine the settling characteristics of Muskeg River (a tributary of the Athabasca River) sediments under different shear conditions. Simulations of the settling and flocculation behaviour of these sediments were used to calibrate a density vs. floc size model. A relationship of the parameters relating floc size and density with the fractal dimension F shows that as diameter increases flocs become weaker. Recommendations for the practical application of the model are further formulated in this paper. The deposition tests offer a quantitative measure of the relative amount of sediment that is likely to be transported through the river for given flow conditions.
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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 | 0.000 | 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".