A reduced-order model for the regeneration of surface currents in Gorgan Bay, Iran
Bibliographic record
Abstract
Abstract This study developed a hydrodynamic reduced-order model (ROM) to regenerate surface currents in Gorgan Bay, Iran. The developed ROM was based on linking a three-dimensional hydrodynamic model, MIKE3-FM, with a data reduction technique, proper orthogonal decomposition (POD). The MIKE3-FM model was first run to simulate surface currents in the bay under a real wind scenario for two years starting July 1, 2010. Thereafter, time and space steps of 6 hours and 500 m, respectively, were chosen to capture 2,920 snapshots of the simulated surface currents using the MIKE3-FM model on 1,937 grids in the bay. The snapshots were then used as input for the POD model to develop the ROM. By applying the POD on the snapshots, necessary spatial and temporal components of surface currents used to develop the ROM were calculated. Having spatial and temporal terms, two ROMs for regeneration of surface currents U and V in two directions x and y, respectively, were developed. Analysis of ROM results revealed they accurately regenerated surface currents using only the first ten modes (among 2,920 modes). Comparison of MIKE3-FM and ROMs developed by the first ten modes revealed there were only negligible differences between their results when they simulated and regenerated, respectively, U and V, in the bay.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".