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Record W2531052858 · doi:10.3847/1538-4357/aa6d0c

A Near-infrared Counterpart of 2E1613.5–5053: The Central Source in Supernova Remnant RCW103

2017· article· en· W2531052858 on OpenAlexafffund

Bibliographic record

VenueThe Astrophysical Journal · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGamma-ray bursts and supernovae
Canadian institutionsHerzberg Institute of AstrophysicsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of LeicesterSpace Telescope Science InstituteNational Aeronautics and Space AdministrationCanada Research ChairsMcGill University
KeywordsSupernova remnantNeutron starNear-Earth supernovaH II regionBinary numberInfraredHubble space telescopeBinary star

Abstract

fetched live from OpenAlex

On 2016 June 22, 2E 1613.5−5053, the puzzling central compact object in supernova remnant RCW 103 emitted a magnetar-like burst. Using Director's Discretionary Time, we observed 2E 1613.5−5053 with the Hubble Space Telescope ( HST ) (WFC3/IR) and we report here on the detection of a previously unseen infrared counterpart. In observations taken on 2016 July 4 and August 11, we detect a new source ( AB mag and AB mag), at the Chandra position of 2E 1613.5−5053, that was not detected in HST /NICMOS images from 2002 August 15 and October 8, to a depth of 24.5 AB mag (F110W) and 25.5 AB mag (F160W). We show that these deep IR observations rule out the possibility of 2E 1613.5−5053 being an accreting binary with a high degree of confidence, but mimic IR emission properties of magnetars and isolated neutron stars. The presence or absence of a low-mass fallback disk cannot be confirmed from our observations.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.239
Teacher spread0.227 · 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

Citations19
Published2017
Admission routes2
Has abstractyes

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