A Characterization of Periodicity in the Voltage Time Series of a Riometer
Bibliographic record
Abstract
Abstract This paper reveals unprecedented periodicity in the voltage series of relative ionospheric opacity meters (riometers) of the Canadian Riometer Array (CRA). In quiet times, the riometer voltage series is accurately modeled by a stochastic process whose components include both a six term expansion in harmonic functions and some amplitude modulated modes of lower signal to noise ratio (SNR). In units of cycles per sidereal day (cpsd), the frequencies of the six harmonic functions lie within 0.01 cpsd of an integer. Earth's rotation induces a splitting of the low SNR components, resulting in the appearance of nine multiplets in standardized power spectrum estimates of the considered CRA voltage series. A second feature of these spectrum estimates is a 6 min periodic element appearing in both the CRA voltage series and the proton mass density series of the Advanced Composition Explorer (ACE). Spectral peak frequencies have been detected, which lie near established solar mode frequency estimates. In addition, some of these peak frequency estimates are coincident with peak frequency estimates of the standardized power spectra for the time series of proton mass density and interplanetary magnetic field strength (IMF) at ACE.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 | 0.000 |
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".