Impacts of Ship-Induced Waves along Shorelines during Flooding Events
Bibliographic record
Abstract
Ship-generated waves are often amplified onshore in confined seaways and are associated with several incidents worldwide. Few tools enable modeling the ship waves’ evolution through complex bathymetry. Here, we assess the skill of XBeach’s ship module for simulating the primary wave generated by a moving pressure head. The model was validated for five ships against field observations at three stations across Lake Saint Pierre, the widest section of the St. Lawrence seaway between Quebec City and Montreal. The study was motivated by reported damages caused by a container ship transiting at 17.6 knots, that is, 20% faster than other ships during extreme flooding. Our model predicted that the ship involved in the incident created drawdown (<20 cm) and runup (<15 cm) that was twice as high as slower ships. However, simulating a wide range of water levels and ship speeds shows that the waves would have been larger at lower water levels due to shoaling. Nonetheless, XBeach could model the evolution of the waves’ drawdown as they propagated over several kilometers from the channel.
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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 | 0.000 |
| 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 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".