Interferometric calibration and the first elevation observations at EKB ISTP SB RAS radar at 10–12 MHz
Bibliographic record
Abstract
The method for calibrating elevation measurements at EKB ISTP SB RAS radar obtained for the period 20/09/2019–18/11/2019 is presented. The calibration method is a modernization of the method for calibrating radar by meteor trails. The main difference of the method is the use of not a statistically processed FitACF data, but the full waveform of the signals scattered on the meteor trails. Using the full waveform makes it possible to more reliably distinguish meteor scattering from other possible scattered signal sources, and to determine meteor heights from the trail lifetime using the NRLMSIS-00 model. A comparison of the results with the results of E-layer calibration method shows a good agreement. The first examples of regular elevation observations at the EKB ISTP SB RAS radar are presented, and their preliminary interpretation is given.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.001 | 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".