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Record W2907931015 · doi:10.1051/0004-6361/201834092

A Sino-German <i>λ</i>6 cm polarisation survey of the Galactic plane

2019· article· en· W2907931015 on OpenAlexaboutno aff

Bibliographic record

VenueAstronomy and Astrophysics · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsnot available
FundersYouth Innovation Promotion AssociationSpace Telescope Science InstituteNederlandse Organisatie voor Wetenschappelijk OnderzoekChinese Academy of SciencesCalifornia Institute of TechnologyNational Aeronautics and Space AdministrationJet Propulsion LaboratoryNational Astronomical Observatories, Chinese Academy of SciencesUniversity of California, Los AngelesMax-Planck-GesellschaftNational Natural Science Foundation of ChinaNational Geographic SocietyYouth Innovation Promotion Association of the Chinese Academy of SciencesNational Science Foundation
KeywordsGalactic planeAngular resolution (graph drawing)SkySpectral indexConfusionInfraredAngular diameterQuasarFlux (metallurgy)

Abstract

fetched live from OpenAlex

Context. Large-scale radio continuum surveys provide data to get insights into the physical properties of radio sources. H II regions are prominent radio sources produced by thermal emission of ionised gas around young massive stars. Aims. We identify and analyse H II regions in the Sino-German λ6 cm polarisation survey of the Galactic plane. Methods. Objects with flat radio continuum spectra together with infrared and/or Hα emission were identified as H II regions. For H II regions with small apparent sizes, we cross-matched the λ6 cm small-diameter source catalogue with the radio H II region catalogue compiled by Paladini and the infrared H II region catalogue based on the WISE data. Effelsberg λ21 cm and λ11 cm continuum survey data were used to determine source spectra. High angular resolution data from the Canadian Galactic Plane Survey and the NRAO VLA Sky Survey were used to solve the confusion when low angular resolution observations were not sufficient. Extended H II regions were identified by eye by overlaying the Paladini and the WISE H II regions onto the λ6 cm survey images for coincidences. The TT-plot method was employed for spectral index verification. Results. A total of 401 H II regions were identified and their flux densities were determined with the Sino-German λ6 cm survey data. In the surveyed area, 76 pairs of sources are found to be duplicated in the Paladini H II region catalogue, mainly due to the non-distinction of previous observations with different angular resolutions and 78 objects in their catalogue are misclassified as H II regions, being actually planetary nebulae, supernova remnants, or extragalactic sources that have steep spectra. More than 30 H II regions and H II region candidates from our λ6 cm survey data, especially extended ones, do not have counterparts in the WISE H II region catalogue, of which 9 are identified for the first time. Our results imply that some more Galactic H II regions still await to be discovered and the combination of multi-domain observations is important for H II region identification. Based on the newly derived radio continuum spectra and the evidence of infrared emission, the previously identified SNRs G11.1−1.0, G20.4+0.1 and G16.4−0.5 are believed to be H II regions.

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 score0.019
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.006
GPT teacher head0.196
Teacher spread0.189 · 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

Citations13
Published2019
Admission routes1
Has abstractyes

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