Doppler HF Radar Application for the Study of Spatial Structure of Currents in the Black Sea
Bibliographic record
Abstract
The results of the surface current spatial structure observations performed by SeaSonde Doppler HF radar (operating frequency is 25 MHz) in the Black Sea region adjacent to the city of Gelendzhik are represented.The observations imply a special technique consisting in successive measurements at two selected points of the coastline.Initially, the measurements are carried out in the first of two selected coastal points during two hours.Then the radar system is transferred to the second point on the coast where the procedure is repeated.At that the velocity field is assumed to remain unchanged during the total measurement period (including the time of the radar displacement) from both points.The measurement results are shown in a form of a spatial map of the current velocity vectors in the research region (with 20 × 20 km dimensions).Some features of the current spatial and temporal variability in the coastal waters are revealed.Particularly, the eddy-like formations (the diameter is a few kilometers) which rapidly move and collapse.Since similar eddies are detected using the contact measurement methods, complex and variable structure of the surface currents measured by a radar does not seem to be an artifact.Nevertheless, reliability of the data resulted from the radar measurements of the surface current velocity field should be verified in future by comparing it with the results of the quasi-synchronous velocity field measurements performed by stationary, drifting and towed velocity meters.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.003 | 0.001 |
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".