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Record W1500339488 · doi:10.22323/1.010.0054

Neutrino Oscillations, Fluctuations and Solar Magneto-gravity Waves

2003· article· en· W1500339488 on OpenAlexafffund
C. P. Burgess, N. S. Dzhalilov, Michele Maltoni, T. I. Rashba, V. B. Semikoz, M. Tórtola, J. W. F. Valle

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNeutrino Physics Research
Canadian institutionsMcGill University
FundersUniversitat de ValènciaRussian Foundation for Basic ResearchEuropean Science FoundationNatural Sciences and Engineering Research Council of CanadaEuropean CommissionMcGill University
KeywordsPhysicsHelioseismologyNeutrino oscillationNeutrinoOscillation (cell signaling)Radiative transferGravitational waveRadiation zoneComputational physicsSolar neutrinoMagnetic fieldAstrophysicsConvection zoneOpticsParticle physicsStars

Abstract

fetched live from OpenAlex

This review has two parts.The first part summarizes the current observational constraints on fluctuations in the solar medium deep within the solar Radiative Zone, and shows how the KamLAND and SNO-salt data combine to make the experimental determination of the neutrino oscillation parameters largely insensitive to prior assumptions about the nature of these oscillations.As part of a search for plausible sources of solar fluctuations to which neutrinos could be sensitive, the second part of the talk summarizes a preliminary analysis of the influence of magnetic fields on helioseismic waves.Using simplifying assumptions which should apply to modes in the solar radiative zone, we find a resonance between Alfvén waves and helioseismic g-modes which potentially modifies the solar density profile fairly significantly over comparatively short distance scales, too narrow to be ruled out by present-day analyses of p-wave helioseismic spectra.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.016
GPT teacher head0.277
Teacher spread0.261 · 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 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

Citations0
Published2003
Admission routes2
Has abstractyes

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