Frequency‐and‐angular HF sounding and ISR diagnostics of TIDs
Bibliographic record
Abstract
A single digisonde, used as a receiver for ionospheric high frequency signals from broadcast stations, was able to determine the wave characteristics of traveling ionospheric disturbances (TIDs) using frequency shift and arrival angle measurements. During a measurement campaign, aimed at recovering large‐scale wave‐like processes in the upper atmosphere, in March 2001 at the MIT Haystack Observatory (Millstone Hill, MA), a Digisonde Portable Sounder (DPS) made simultaneous observations with the incoherent scatter radar (ISR). The DPS was upgraded to include the frequency and angular sounding (FAS) technique previously developed at the Institute of Radio Astronomy in Kharkov, Ukraine, for TID diagnostics. The DPS with four spaced receive antennas received the radio signals at 3.33 MHz and 7.335 MHz from Radio CHU of the Canadian Time Service (Ottawa, Ontario). The FAS technique recovered the basic parameters of TIDs, i.e., amplitude, speed, and the direction of the propagation vector by modeling the ionosphere as a perfectly reflecting surface. For three days during the campaign the Millstone Hill ISR monitored the ionospheric midpoint using a triangulation mode to identify the direction of motion and speed of the wave‐like ionospheric disturbances. Comparison of the results from the two diagnostic techniques showed good agreement. The wave directions were within 10 to 15 degrees, and speed and wavelength were within 10 to 12%.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".