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Record W4292190216 · doi:10.3847/2041-8213/ac84d3

Multiple Channels for the Onset of Magnetism in Isolated White Dwarfs

2022· article· en· W4292190216 on OpenAlexafffund
S. Bagnulo, J. D. Landstreet

Bibliographic record

VenueThe Astrophysical Journal Letters · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsWhite (mutation)White dwarfMagnetismPsychologyAstrophysicsPhysicsGeneticsBiologyCondensed matter physicsStars

Abstract

fetched live from OpenAlex

Abstract The presence of a strong magnetic field is a feature common to a significant fraction of degenerate stars, yet little is understood about the field’s origin and evolution. New observational constraints from volume-limited surveys point to a more complex situation than a single mechanism valid for all stars. We show that in high-mass white dwarfs, which are probably the results of mergers, magnetic fields are extremely common and very strong and appear immediately in the cooling phase. These fields may have been generated by a dynamo active during the merging. Lower-mass white dwarfs, which are often the product of single-star evolution, are rarely detectably magnetic at birth, but fields appear very slowly, and very weakly, in about a quarter of them. What we may see is an internal field produced in an earlier evolutionary stage that gradually relaxes to the surface from the interior. The frequency and strength of magnetic fields continue to increase to eventually rival those of highly massive stars, particularly after the stars cool past the start of core crystallization, an effect that could be responsible for a dynamo mechanism similar to the one that is active in Earth’s interior.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.157
Threshold uncertainty score0.351

Codex and Gemma teacher scores by category

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

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 head0.010
GPT teacher head0.211
Teacher spread0.201 · 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 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

Citations64
Published2022
Admission routes2
Has abstractyes

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