SAMEERDU—Digital Ionosonde: Brief System Description and Initial Results from a Low‐Latitude Location Dibrugarh
Bibliographic record
Abstract
Abstract A digital ionosonde was designed and built by Society for Applied Microwave Electronics Engineering and Research (SAMEER), Mumbai in collaboration with Dibrugarh University to suit the needs of equatorial‐ and low‐latitude regions of India. The design objectives were to obtain good signal‐to‐noise ratio to mitigate the heavy noise due to interference, obtain short duration ionograms, estimate vertical drifts, reconstruct vertical electron density profile, and make antenna size smaller. Transmission of maximum 1 kW power using modified delta antenna is used with dual channel magnetic loop receiver antenna. Pulse compression by 8‐ and 16‐bit biphase codes are employed to increase noise immunity and the height resolution. The preliminary results of the ionogram mode only are presented in this work. The basic ionogram recorded by this system called SAMEER‐Dibrugarh University Ionospheric Radar is compared with colocated Canadian Advanced Digital Ionosonde ionogram which is in operation in Dibrugarh since 2010. A reasonably clear trace of E and F layers is obtained even without coherent pulse integration and pulse coding. The performance of the coding schemes is investigated with and without coherent integration. Some sample ionospheric experiments conducted with SAMEER‐Dibrugarh University Ionospheric Radar, and interesting results like the detection of travelling ionospheric disturbances, Es layer substructures, ionospheric irregularities, and the generation of bottom‐side vertical electron density profile are presented to highlight the potential and capabilities of the system.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".