Modeling River Plume Dynamics in a Large Wind-Forced Embayment
Bibliographic record
Abstract
Water quality degradation, in the form of undesirable algae, occurs near the Nottawasaga River mouth and along Wasaga Beach, southeastern Georgian Bay. The ability to manage this water resource is compromised due to lack of monitoring and science. In the present study, a 3D hydrodynamic model was applied to gain an understanding of how advection and dilution of the river plume can trap nutrients along Wasaga Beach. Simulated water temperatures and currents had a root-mean-square error between 1.5°C and 2.5°C and ∼0.06 m s−1, respectively. Maximum nearshore river concentrations occurred near the beach during high river discharge >20 m3 s−1 and westerly winds. Generally, the river plume was advected by winds >∼4 m s−1, traveling along the northern shoreline during southerly winds and along the southwest shoreline during northeasterly winds. This process was analytically modeled when the wind strength indicator or Froude number (ratio of the characteristic wind-velocity scale to the buoyancy–velocity scale) was greater than one.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".