Application of Finite-Volume Coastal Ocean Model in Studying Strong Tidal Currents in Discovery Passage, British Columbia, Canada
Bibliographic record
Abstract
The unstructured-grid, Finite-Volume Coastal Ocean Model (FVCOM) was used to simulate the flows in Discovery Passage, British Columbia, Canada. Challenges in this numerical study include the strong tidal currents in Seymour Narrows of up to 7.8 m s-1, small-scale topographic features, and freshwater discharge and stratification. Tidal forcing, freshwater input, the Coriolis effect, and wet and dry regions were considered. The model was integrated for 16 days and model results of the last 14 days were examined. The model was validated using available historical measurements at different sites in Discovery Passage, including water surface elevation and ocean current data, as well as CTD-bottle profile data. Model results are also compared with the recent numerical studies by Jiang and Fissel (2007) and by Foreman et al. (2012). Model results demonstrated that the unstructured-grid model generated reasonable maps of the very strong currents in tidal channels, with the advantage of high adaptability in resolving the complex geometry of the narrow channels as seen in Discovery Passage. Effects of stratification and freshwater discharge from Campbell River during the study period were investigated.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| 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".