Low-latitude equinoctial spread-F occurrence at different longitude sectors under low solar activity
Bibliographic record
Abstract
Abstract. We present the results of a comparative study of spread-F signatures over five low-latitude sites: Chiangmai (CGM; 18.8° N, 98.9° E, mag. Lat. 8.8° N), Thailand; Tanjungsari (TNJ; 6.9° S, 107.6° E, mag. Lat. 16.9° S), Indonesia; Palmas (PAL; 10.2° S, 311.8° E, mag. Lat. 0.9° S) and São José Dos Campos (SJC; 23.2° S, 314.1° E, mag. Lat. 14.0° S), Brazil; and Tucumán (TUC; 26.9° S, 294.6° E, mag. Lat. 16.8° S), Argentina. The investigation was based on simultaneous ionograms recorded by an FMCW (frequency-modulated continuous-wave) at CGM, an IPS-71 (digital ionosonde from KEL aerospace) at TNJ, a CADI (Canadian Advanced Digital Ionosonde) at PAL and SJC, and an AIS-INGV (Advanced Ionospheric Sounder – Istituto Nazionale di Geofisica e Vulcanologia) at TUC, during the equinoctial periods March–April (R12 = 2.0 and R12 = 2.2) and September–October (R12 = 6.1 and R12 = 7.0) 2009, for very low solar activity. Spread-F signatures were categorized into two types: the range spread-F (RSF) and the frequency spread-F (FSF). The study confirms that the dynamics and the physical processes responsible for these phenomena are actually complicated. In fact, the features that arise from the investigation are different, depending on both the longitude sector and on the hemisphere. For instance, TUC, under the southern crest of the ionospheric equatorial ionization anomaly (EIA), shows a predominance of RSF signatures, while both SJC, under the southern crest of EIA but in a different longitude sector, and CGM, under the northern crest of EIA, show a predominance of FSF signatures. Moreover, the spread-F occurrence over the longitude sector that includes CGM and TNJ is significantly lower than the spread-F occurrence over the longitude sector of PAL, SJC, and TUC.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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; both teacher heads agree on what is shown here.
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".