Wind parameter measurement using X-band marine radar images
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Chapter Contents: 17.1 Wind streaks/wind gusts based methods 17.1.1 Local gradient based method 17.1.2 Optical flow based method for wind vector retrieval 17.2 Intensity information and curve fitting based methods 17.2.1 Single curve fitting based algorithm 17.2.2 Two-model curve fitting for rain mitigation 17.2.3 Dual curve fitting for low sea state cases 17.2.4 Significant wave height incorporated curve fitting 17.2.5 Intensity level selection algorithms 17.2.6 Modified ILS 17.2.7 Texture analysis incorporated ILS 17.3 Transform domain and curve fitting based methods 17.3.1 Spectral noise based algorithm 17.3.2 Spectral integration based algorithm 17.3.3 Ensemble empirical mode decomposition based methods 17.4 Nonparametric regression based methods 17.4.1 Neural network based method 17.4.2 Support vector regression based method 17.4.3 Gaussian process regression based method 17.5 Error mitigation 17.6 Conclusions and outlook References
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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