Three‐way validation of the Rankin Inlet PolarDARN radar velocity measurements
Bibliographic record
Abstract
The newly installed Rankin Inlet HF radar is very similar to other SuperDARN radars but uses a new type of antennae with its back lobe overlooking the auroral zone where ionospheric irregularities occur very frequently. Despite the fact that a special screen has been installed, there is a chance to receive echoes from the back/side lobe, which can affect the observed velocities. In this study, Rankin Inlet HF radar (RKN) velocities are compared with measurements from three independent instruments: the HF radar in Saskatoon, the CADI ionosonde at Resolute Bay, and drift meters on board DMSP satellites passing the RKN field of view. Although data spread and the degree of agreement vary from one comparison to another, the overall conclusion is that even if echoes are received from the back/side lobe, their effect is statistically insignificant. RKN velocities were found to be comparable to those inferred from other instrument outputs; the slope of the best fit line and the correlation coefficient can be as high as 0.7 and 0.8, respectively. The majority of inconsistencies are related to the difference in the spatial and temporal resolutions of the instruments involved in the comparison.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".