A Circulation Model for Inlets Along the Central West Coast of Vancouver Island
Bibliographic record
Abstract
An ocean circulation model has been developed for the central west coast of Vancouver Island, with particular attention to the numerous inlets where salmon farms are located. The ultimate goal is to provide a tool to assist in informing decisions on the siting and management of fish farms and to further understanding of the regional coastal oceanography. The complicated coastline and bathymetry are approximated with an unstructured triangular grid in the horizontal direction and terrain-following coordinates in the vertical. The period of 1 March to 31 July 2016, is simulated using the Finite Volume Community Ocean Model and results are evaluated through comparisons with a combination of acoustic Doppler current profiler, tide gauge, and temperature and salinity observations. The model was found to be accurate in representing (i) tidal elevations and currents everywhere throughout the model domain and (ii) subtidal currents and temperature and salinity along the shelf. However, it fared poorly in inlets where (i) the tidal currents were relatively weak and not the dominant source of mixing and/or (ii) steep bathymetry necessitated smoothing. Sources of these and other inaccuracies, and the changes needed to overcome them, are discussed. Overall, this work highlights the complex and diverse dynamics at play in a glacially-carved coastal ocean, providing an extensive discussion of modelling challenges and potential solutions.
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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 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".