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Record W2139336715 · doi:10.1088/0004-637x/791/1/47

PROBING THE CRUST OF THE NEUTRON STAR IN EXO 0748-676

2014· article· en· W2139336715 on OpenAlexafffund
N. Degenaar, Z. Medin, A. Cumming, R. Wijnands, M. T. Wolff, Edward M. Cackett, J. M. Mïller, P. G. Jonker, J. Homan, Edward F. Brown

Bibliographic record

VenueThe Astrophysical Journal · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysical Phenomena and Observations
Canadian institutionsMcGill University
FundersOffice of Naval ResearchNatural Sciences and Engineering Research Council of CanadaCanadian Institute for Advanced ResearchSmithsonian Astrophysical ObservatoryNational Aeronautics and Space AdministrationSpace Telescope Science InstituteSmithsonian Institution
KeywordsNeutron starAstrophysicsAccretion (finance)PhysicsCrustThermalSwiftThermal emissionAstronomyGeophysics

Abstract

fetched live from OpenAlex

X-ray observations of quiescent X-ray binaries have the potential to provide insight into the structure and the composition of neutron stars. EXO 0748–676 had been actively accreting for over 24 yr before its outburst ceased in late 2008. Subsequent X-ray monitoring revealed a gradual decay of the quiescent thermal emission that can be attributed to cooling of the accretion-heated neutron star crust. In this work, we report on new Chandra and Swift observations that extend the quiescent monitoring to ≃5 yr post-outburst. We find that the neutron star temperature remained at ≃117 eV between 2009 and 2011, but had decreased to ≃110 eV in 2013. This suggests that the crust has not fully cooled yet, which is supported by the lower temperature (≃95 eV) measured ≃4 yr prior to the accretion phase in 1980. Comparing the data to thermal evolution simulations reveals that the apparent lack of cooling between 2009 and 2011 could possibly be a signature of convection driven by phase separation of light and heavy nuclei in the outer layers of the neutron star.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.012
GPT teacher head0.217
Teacher spread0.205 · 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

Citations53
Published2014
Admission routes2
Has abstractyes

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