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Record W2943962698 · doi:10.3847/1538-3881/ab25f6

CHANG-ES. XX. High-resolution Radio Continuum Images of Edge-on Galaxies and Their AGNs: Data Release 3

2019· article· en· W2943962698 on OpenAlexaff

Bibliographic record

VenueThe Astronomical Journal · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsArthur B. McDonald-Canadian Astroparticle Physics Research InstituteUniversity of ManitobaQueen's University
Fundersnot available
KeywordsSpectral indexActive galactic nucleusGalaxyRadio galaxySpiral galaxySpectral lineLuminous infrared galaxyDisc galaxy

Abstract

fetched live from OpenAlex

Abstract The CHANG-ES galaxy sample consists of 35 nearby edge-on galaxies that have been observed using the VLA at 1.6 and 6.0 GHz. Here we present the third data release of our sample, namely, the B configuration 1.6 GHz sample. In addition, we make available the band-to-band spectral index maps between 1.6 and 6.0 GHz, the latter taken in the matching resolution C configuration. The images can be downloaded from https://www.queensu.ca/changes . These are our highest-resolution images (≈3″), and we examine the possible presence of low-luminosity active galactic nuclei (AGNs) in the sample, as well as some in-disk structure. New features can be seen in the spectral index maps that are masked in the total intensity emission, including hidden spiral arms in NGC 3448 and two previously unknown radio lobes on either side of the nucleus of NGC 3628. Our AGN detection rate, using only radio criteria, is 55%, which we take as a lower limit because some weaker embedded AGNs are likely present that could be revealed at higher resolution. Archival XMM-Newton data were used to search for further fingerprints of the AGNs in the studied sample. In galaxy disks, discrete regions of flat spectral index are seen, likely due to a thermal emission fraction that is higher than the global average.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.584

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.010
GPT teacher head0.208
Teacher spread0.198 · 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

Citations33
Published2019
Admission routes1
Has abstractyes

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