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Record W2025016837 · doi:10.1086/341115

<i>r</i>‐Modes in the Ocean of a Magnetic Neutron Star

2002· article· en· W2025016837 on OpenAlexaff
Vahid Rezania

Bibliographic record

VenueThe Astrophysical Journal · 2002
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPulsars and Gravitational Waves Research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPhysicsMagnetic fieldMagnetohydrodynamic driveL-shellShell (structure)MagnetohydrodynamicsMechanicsClassical mechanicsEarth's magnetic fieldQuantum mechanics

Abstract

fetched live from OpenAlex

We study the dynamics of r -modes in the ocean of a magnetic neutron star. We model the star's ocean with a spherical rotating thin shell and assume that the magnetic field symmetry axis is not aligned to the shell's spin axis. In the magnetohydrodynamic approximation, we calculate the frequency of l = m r -modes in the shell of an incompressible fluid. Different r -modes with l and l ± 2 are coupled by the inclined magnetic field. Kinematical secular effects for the motion of a fluid element in the shell undergoing the l = m = 2 r -mode are studied. The magnetic-corrected drift velocity of a given fluid element undergoing the l = m r -mode oscillations is obtained. The magnetic field increases the magnitude of the fluid drift produced by the r -mode oscillations. The drift velocity is strongly modulated by the inclined magnetic field. We show that the magnetic field is distorted by the high- l magnetic r -modes more strongly than by the low- l modes. Furthermore, because of the shear produced by the r -mode drift velocity, the high- l modes in the ocean fluid will damp faster than the low- l ones.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.015
GPT teacher head0.280
Teacher spread0.266 · 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 designSimulation or modeling
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

Citations6
Published2002
Admission routes1
Has abstractyes

Explore more

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