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Record W2990947568 · doi:10.1017/pasa.2019.33

Candidate radio supernova remnants observed by the GLEAM survey over 345° &lt;<i>l</i>&lt; 60° and 180° &lt;<i>l</i>&lt; 240°

2019· article· en· W2990947568 on OpenAlexaff
N. Hurley‐Walker, B. M. Gaensler, D. A. Leahy, M. D. Filipović, P. J. Hancock, T. M. O. Franzen, A. R. Offringa, J. R. Callingham, L. Hindson, Chengqing Wu, M. E. Bell, Bi‐Qing For, M. Johnston‐Hollitt, A. D. Kapińska, John Morgan, Tara Murphy, B. McKinley, P. Procopio, L. Staveley‐Smith, R. B. Wayth, Q. Zheng

Bibliographic record

VenuePublications of the Astronomical Society of Australia · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Cosmic Phenomena
Canadian institutionsUniversity of CalgaryCanadian Institute for Theoretical AstrophysicsUniversity of Toronto
FundersUniversity of California, Los AngelesJet Propulsion LaboratoryAustralian GovernmentCommonwealth Scientific and Industrial Research OrganisationCurtin University of TechnologyAstronomy Australia LimitedCalifornia Institute of TechnologyNational Aeronautics and Space Administration
KeywordsSupernovaGalactic planePhysicsAstrophysicsSkyAstronomySupernova remnantGalaxy

Abstract

fetched live from OpenAlex

Abstract We examined the latest data release from the GaLactic and Extragalactic All-sky Murchison Widefield Array (GLEAM) survey covering 345° &lt; l &lt; 60° and 180° &lt; l &lt; 240°, using these data and that of the Widefield Infrared Survey Explorer to follow up proposed candidate Supernova Remnant (SNR) from other sources. Of the 101 candidates proposed in the region, we are able to definitively confirm ten as SNRs, tentatively confirm two as SNRs, and reclassify five as H ii regions. A further two are detectable in our images but difficult to classify; the remaining 82 are undetectable in these data. We also investigated the 18 unclassified Multi-Array Galactic Plane Imaging Survey (MAGPIS) candidate SNRs, newly confirming three as SNRs, reclassifying two as H ii regions, and exploring the unusual spectra and morphology of two others.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.140
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.025
GPT teacher head0.243
Teacher spread0.218 · 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.

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

Citations35
Published2019
Admission routes1
Has abstractyes

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