An Accurate Physics-Based Single-Layer Neural Network for Significant Wave Estimation from High Frequency Radar Data
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Bibliographic record
Abstract
Previous work by the second author showed that up to first order, the significant wave height is linearly proportional to the standard deviation of the received voltage from the receivers of an HF radar system, greatly simplifying significant wave height estimation from HF radar data by avoiding the calculation of the Doppler spectrum from the received HF radar data. In this paper, previous work is extended to formulate an artificial neural network model trained using simple matrix inversion. Additionally, the proposed model has shown to perform well on estimating the significant wave height from field data acquired at Argentia, Newfoundland, Canada in July 2018. When compared to wave buoy data, considered to be ground truth for significant wave height measurements, the proposed model gives a root-mean squared error (RMSE) of roughly 22 cm.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 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