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Record W2288211038 · doi:10.1002/2015sw001314

Solar modulation of the deep space galactic cosmic ray lineal energy spectrum measured by CRaTER, 2009–2014

2016· article· en· W2288211038 on OpenAlexaff
C. Zeitlin, A. W. Case, N. A. Schwadron, H. E. Spence, Joanna Mazur, C. J. Joyce, M. D. Looper, A. P. Jordan, R. R. Rios, Lawrence W. Townsend, J. C. Kasper, J. B. Blake, Sonya Smith, J. K. Wilson, Y. Iwata

Bibliographic record

VenueSpace Weather · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSolar and Space Plasma Dynamics
Canadian institutionsLockheed Martin (Canada)
FundersSouthwest Research InstituteNational Aeronautics and Space Administration
KeywordsCosmic rayHeliospherePhysicsSolar minimumSolar cycleImpact craterAstrophysicsSolar maximumAstronomyCoronal mass ejectionSolar cycle 22Solar windNuclear physicsPlasma

Abstract

fetched live from OpenAlex

Abstract The Cosmic Ray Telescope for the Effects of Radiation (CRaTER) is an energetic particle detector flying aboard the Lunar Reconnaissance Orbiter. Since arriving at the Moon in 2009, CRaTER has observed the deep solar minimum of solar cycle 23, the ascending phase of cycle 24, the very weak maximum of cycle 24, and in recent months, what appears to be the start of the descending phase of cycle 24. In earlier work, we presented lineal energy spectra of galactic cosmic rays (GCRs) at solar minimum for different shielding depths. The long period of CRaTER observations allows us to study the evolution of these spectra as a function of solar modulation. As solar modulation increases, the total flux of GCRs decreases, and lower‐energy ions are preferentially removed from the spectrum of ions that arrive in the inner heliosphere. These effects lead to modest variations in the lineal energy spectrum as a function of time. GCR fluxes at the 2009/2010 solar minimum were high by historical standards and at solar maximum remained high compared to earlier maxima.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.004
GPT teacher head0.191
Teacher spread0.187 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations8
Published2016
Admission routes1
Has abstractyes

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