Estimation of Bottom Friction in Modeling Tidal Dynamics of Port Phillip Bay
Bibliographic record
Abstract
Abstract Knowledge of bottom friction plays a crucial role in the modeling of coastal ocean hydrodynamics. Existing formulations based on the grain size to estimate the friction coefficients are often imprecise, impacting the performance of numerical models. This study adjusted the estimated friction coefficient based on the specific habitat characteristics of the seabed in Port Phillip Bay. The effectiveness of this method is substantiated through modeling surface elevations within the bay and comparing the results with observational data. Through sensitivity experiments, it was found that the scaling factors should be chosen depending on the seabed characteristics and could vary by one to two orders of magnitude. The impact of the adjusted bottom-friction coefficient on the simulated tides in the bay is also analyzed. Revised estimates of bottom friction significantly improve our capability to predict surface elevations with implications for modeling waves, tides, and sediment transport in Port Phillip Bay.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 teacher head, 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".