Ionospheric providing of HF propagation in high latitudinal regions
Bibliographic record
Abstract
For HF propagation providing, it is necessary to have the information on an ionospheric condition. The paper purpose was the estimation of possibility to use the IRI model in a high-latitude zone according to vertical and oblique sounding. It is shown that the new version IRI2016 of the model provides conformity of the modeling values of foF2 with experimental medians at level of middle-latitude values. Calculations of oblique ionograms were performed by a ray tracing method for two days 26.01.2016 (UT = 11:20) and 25.02.2016 (UT = 10:20) to which data were available. The greatest number of paths (17) was 25.02. The following results are obtained for these paths. For the initial IRI model, relative deviations of MUF from observational values MOF were 14.53% and 15.75% for one and two hops. Adaptation of the IRI model to data of current diagnostics has provided 7.93% and 6.68%. As foF2, SPIDR database was used, at absence - data of TEC. These estimates lay in limits for middle-latitude zones. Thus, in this case (quiet geomagnetic conditions) the initial IRI model provides acceptable results. Its adaptation to data of current diagnostics of vertical sounding and measurements of TEC allows increasing accuracy of MUF determination in 2 times.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".