Analyzing the Effects of Wind and Stratification on Surface Currents in a Large Lake
Bibliographic record
Abstract
Surface currents in large lakes are important for water quality and ecosystem processes since they drive nutrient transport. In this study, the individual effects of wind and stratification on surface currents are analyzed in a large lake, Lake Ontario. A state-of-the-art numerical model is applied to explore effects of a common wind scenario (6 m/s eastward) and stratification on surface currents, and their interactions with tributary plumes. For a non-stratified lake, eastward wind accelerates the surface velocities by maximum 23.5 cm/s in nearshore areas, while its effects on current direction are not obvious in the nearshore areas. In mid-lake regions, wind could change the current directions by about 100 degrees counter-clockwise. This eastward wind accelerates the propagation of the Niagara River plume, but decreases its width and bulge area at the river mouth. Lake stratification increases surface velocities in offshore regions and decreases velocities in nearshore regions. The changes of surface current direction by stratification are within 68 degrees in most areas. Tributary plumes are strongly affected by surface currents and the unusual westward Niagara River plume observations could be explained by currents caused by unusual westward wind conditions. Predicting changes in surface currents caused by wind and stratification is important for understanding nutrient dynamics and shedding light on ecological problems such as algal bloom occurrences.
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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) | 0.000 | 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".