Data Assimilation for Bathymetry Estimation at a Tidal Inlet
Bibliographic record
Abstract
Abstract This study involved developing and testing a data assimilation framework that accommodates different types of geophysical ocean data (i.e., surface velocity and wave information) and provides an estimation of the bathymetry of a mixed-energy tidal inlet. This framework was successfully applied to a highly variable tidal environment using synthetic data (twin test). The synthetic data consisted of surface velocity components associated with the tidal circulation and wavenumber–frequency pairs of incoming surface gravity waves that mimic data that could be derived from an airborne synthetic aperture radar system and a tower-mounted X-band radar system, respectively. The present ensemble-based assimilation framework has previously been applied in both wave-dominated coastal and current-dominated riverine environments. In contrast, the inlet environment is neither wave nor current dominated. The assimilation of wave and current data together was most useful to obtain a skillful estimate of the spatial map of bathymetry.
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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".