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Record W2773749868 · doi:10.3847/1538-4357/aa9e89

A Radio Continuum and Polarization Study of SNR G57.2+0.8 Associated with Magnetar SGR 1935+2154

2018· article· en· W2773749868 on OpenAlexaff

Bibliographic record

VenueThe Astrophysical Journal · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Cosmic Phenomena
Canadian institutionsCanadian Institute for Theoretical AstrophysicsDominion Astrophysical ObservatoryUniversity of TorontoHerzberg Institute of Astrophysics
Fundersnot available
KeywordsMagnetarPulsarSupernova remnantSpectral indexPulsar wind nebulaMilky WayPolarization (electrochemistry)Magnetic fieldLinear polarization

Abstract

fetched live from OpenAlex

Abstract We present a radio continuum and linear polarization study of the Galactic supernova remnant (SNR) G57.2+0.8, which may host the recently discovered magnetar SGR 1935+2154. The radio SNR shows the typical radio continuum spectrum of a mature supernova remnant with a spectral index of and moderate polarized intensity. Magnetic field vectors indicate a tangential magnetic field, expected for an evolved SNR, in one part of the SNR, and a radial magnetic field in the other. The latter can be explained by an overlapping arc-like feature, perhaps a pulsar wind nebula, emanating from the magnetar. The presence of a pulsar wind nebula is supported by the low average braking index of 1.2, which we extrapolated for the magnetar, and the detection of diffuse X-ray emission around it. We found a distance of 12.5 kpc for the SNR, which identifies G57.2+0.8 as a resident of the Outer spiral arm of the Milky Way. The SNR has a radius of about 20 pc and could be as old as 41,000 yr. The SNR has already entered the radiative or pressure-driven snowplow phase of its evolution. We compare independently determined characteristics like age and distance for both the SNR and the soft gamma repeater SGR 1935+2154, and conclude that they are physically related.

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 score0.583
Threshold uncertainty score0.522

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 head0.005
GPT teacher head0.199
Teacher spread0.193 · 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

Citations72
Published2018
Admission routes1
Has abstractyes

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