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Record W4403411660 · doi:10.5539/apr.v16n2p87

Statistical Study of the Occurrence of Coronal Holes in the Solar Corona During Solar Cycle 24

2024· article· en· W4403411660 on OpenAlexvenueno aff
Salfo Kaboré, Guibula Karim, Gyebre Aristide Marie Frederic, Ouattara Frédéric

Bibliographic record

VenueApplied Physics Research · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSolar and Space Plasma Dynamics
Canadian institutionsnot available
FundersNational Aeronautics and Space Administration
KeywordsCorona (planetary geology)NanoflaresCoronal mass ejectionCoronal loopSolar cycle 22PhysicsSolar windAstrobiologyPlasma

Abstract

fetched live from OpenAlex

In this article we look at: (a) the occurrence of coronal holes as a function of the different phases of solar cycle 24, (b) the variability of the annual number of coronal holes from 2009 to 2019, (c) the distribution of polar and non-polar coronal holes, irrespective of the phase but also as a function of the different phases of the cycle. From the phase minimum to the descending phase of solar cycle 24, the occurrences of coronal holes observed on the solar disc are 38%, 24%, 9% and 29% respectively. The annual number of coronal holes observed on the solar disc does not always follow the expected evolution of the two components of the solar magnetic field and the annual number of sunspots. Regardless of the phase of the solar cycle, the majority of coronal holes, around 65%, are located in the polar regions. During the early and late phases of the solar cycle, polar coronal holes predominate, whereas during the ascending phase and phase maximum, non-polar coronal holes predominate. The number of polar coronal holes is highest during the minimum phase of the solar cycle and lowest during the maximum phase. During the phases of the solar cycle, coronal hole activity appears to be in phase opposition with sunspot activity. There is a fairly good correlation between variations in the number of polar coronal holes and the expected evolution of the poloidal component of the solar magnetic field.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.383
Threshold uncertainty score0.371

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.041
GPT teacher head0.347
Teacher spread0.306 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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