Gulf Stream Detection from SAR Doppler Anomaly
Bibliographic record
Abstract
This work presents a Gulf Stream (GS) North Wall (GSNW) detection algorithm applicable to Sentinel-1 Radial surface Velocity (RVL) products derived from Doppler centroid analysis of synthetic aperture radar (SAR) data collected off the east coast of Canada from February 2017 to August 2017. Visual comparison of the extracted location of the GSNW (obtained by evaluating the peak RVL gradient in the azimuth direction), and the estimated location of the GSNW as determined by the U.S. Naval Oceanographic Office and a GSNW search region (GSNWSR), indicates that the algorithm is capable of detecting the GSNW in ∼80% of the cases evaluated. Results are dependent on the geophysical orientation of the GS across the SAR swath, such that the GSNW detector performed most reliably when the GS was oriented across the swath resulting in maximized surface velocities in the range direction. When the GS meandered, or when GS eddies appeared in the RVL data, the GSNW was often partially detected or detected multiple times, reducing confidence in the extracted location. It is anticipated that the results obtained using the Sentinel-1 RVL products will be applicable to SAR data from other platforms.
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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".