Seabed disturbance and sediment mobility due to tidal current and waves on the continental shelves of Canada
Bibliographic record
Abstract
Waves and tidal currents can interact to produce strong seabed shear stress and mobilization of sediments on continental shelves. Modelled wave and tidal current data for a 3-year period were used in a combined-flow sediment transport model to simulate the seabed shear stresses and the mobilization of uniform medium sand on the continental shelves of Canada. The modelling results are presented to establish the first national framework of seabed disturbance and sediment mobility on the continental shelves of Canada. Strong waves and tidal currents on the Canadian continental shelves produce mean bed shear velocity >5 cm·s−1. Medium sand can be mobilized >50% of the time over many areas on the shelves. The mobilization by tidal currents occurs over 36% and by waves over 50% of the shelf area, demonstrating that mobilization of sediments is dominated by waves on the Canadian continental shelves. Combined shear stresses due to wave and tidal current interaction further increase sediment mobilization to over 68% of the shelf area. The spatial variation of the relative importance of wave and tidal disturbances allows classification of the continental shelves into six disturbance types. Innovative Seabed Disturbance (SDI) and Sediment Mobility (SMI) indices are proposed to quantify the seabed exposure to oceanographic processes and sediment mobilization, incorporating both the magnitude and frequency of these processes. The proposed SDI and SMI, together with the disturbance type classification, can be used as standard parameters to best quantify seabed disturbance and sediment mobility on other shelves of the world.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".