Investigation of ionospheric clutter using ionosondes in mid-latitude and arctic regions aimed at feasibility assessment of the high-frequency surface-wave radar surveillance
Bibliographic record
Abstract
This paper studies ionospheric clutter conditions and compares ionosonde measurements in the mid-latitude and arctic regions to determine the most favourable conditions for HFSWR surveillance for surface vessels and low-altitude air targets. The best time to perform HFSWR surveillance is between approximately 06:00-15:00 UT and 20:00-00:00 UT. During these hours, the number of days that sporadic-E interference occurs in a month and the range of frequencies reflected is minimized compared to other times of the day. Of the sites considered, Resolute Bay is the most favourable site for HFSWR surveillance in the summer since sporadic-E interference occurs least often, resulting in reduced signal interference. Similarly, Eureka is the preferred site during the winter months. In addition, the ionosphere at Eureka generally reflects the lowest range of maximum frequencies (~4 - 8 MHz), again resulting in less clutter interference. In all the observations, polar cap sites Eureka and Resolute Bay yield results that are less prone to sporadic-E interference than the mid-latitude site Cambridge Bay.
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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 | 0.000 | 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 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".