Comparison of spectral estimation methods for current estimation by an HF surface wave radar
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Bibliographic record
Abstract
This paper presents a comparative study of conventional spectrum estimation methods, such as the periodogram method, and modern techniques, such as the autoregressive and multiple signal classification methods, for current mapping by a high frequency surface wave radar. To calculate the radial current velocity, it is important to estimate its associated Doppler shift from the frequency spectrum. In addition to the conventional centroid method, a more robust Bragg frequency identification method, termed the symmetric-peak-sum, is proposed and examined in conjunction with each of the spectral estimation techniques. It has been found that a weighted sum of the radar-derived current estimates using these two methods generally provides a lower rms difference from the buoy measurements. The weighting ratio is optimized using a genetic algorithm. Field data indicate that a combination of these spectral estimation methods is capable of providing improvements in retrieved current velocities for various current conditions.
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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 it