OBSERVATIONS OF BEACH-DUNE MORPHOGOLICAL RESPONSE TO STORM WAVES USING LIDAR BATHYMETRIC MAPPING IN A WAVE BASIN
Bibliographic record
Abstract
Waves during major storms can cause significant changes to coastal morphology (Lee et al., 1998). The beach-dune system is known to be highly vulnerable to erosion when the wave run-up exceeds the threshold of the base of the dune in the collision regime, according to the Storm Impact scale defined by Sallenger (2000). Detailed bathymetric measurements are very difficult to obtain during storms due to the hazardous wave conditions. However, bathymetric surveys can be easily and intermittently performed during smaller scale physical model experiments (e.g., Hamilton et al., 2001) and high resolution can be achieved using laser scanning with Light Detection and Ranging (LIDAR) sensors (Smith et al., 2017). In the present study, a laboratory experiment of beach-dune morphology change is conducted in a rectangular wave basin that has recently been used to simulate erosion of a 2-dimensional sand dune (Berard et al., 2017). The objective of the present study is to investigate the 3-dimensional morphologic response of a sand beach-dune system to storm waves approaching at an oblique angle.
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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 | 0.000 |
| 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) | 0.001 | 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".