Study of Radial Differential Coronal Rotation using Solar Radio flux for period (1980-1986)
Bibliographic record
Abstract
The unpredictable solar activity cycle is ancient problem in solar physics.It affects the entire space weather activity, which in turn can have trivial public impact.Solar activities are stoutly interrelated with the solar rotation.Spatial and temporal variation in inner and outer solar coronal rotation may be a remarkable issue to investigate which is one of the bases of most of solar activities.Present work investigates radial differential rotation of solar corona by using radio emission at different frequencies emitted from various layers of the solar corona during the time period 1980-1986 (Half Schwabe Cycle).Tracking of tracers on the surface of the sun, spectroscopic measurement and Flux modulation; are the different techniques to study solar rotation.The flux modulation method is used here in present work.Solar radio flux emerging at different heights in the solar atmosphere is recorded at different Radio Astronomical Observatories; as solar flux emission at frequencies 430 and 810 MHz recorded at Jagiellonian University Radio Astronomical observatory, Cracow, Poland; at 1415 and 2695 MHz recorded at Sagamore Hill Radio Observatory Massachusetts, USA and 2800 MHz recorded at Dominion Radio Astrophysical Observatory, Pentincton, Canada. .Annual time series is formed from daily recorded solar flux data.Periodic component present in such time series are estimated by statistical tool Lomb Scargle Periodogram (LSP).The estimated rotation period for different layers of solar corona are correlated with the annually averaged sun spot numbers (SSN) and solar flare index (SFI) for study period.The interrelation of variation in solar coronal rotation with solar activity through which possible space weather prediction will be covered as a full paper for publication in proceedings of (URSI-RCRS2024).Detail outcome of work would also be presented in the conference.
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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 | 0.001 | 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".