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Record W2911391557 · doi:10.3847/1538-4357/ab02fe

Source Structure and Molecular Gas Properties from High-resolution CO Imaging of SPT-selected Dusty Star-forming Galaxies

2019· article· en· W2911391557 on OpenAlexaff
Chenxing Dong, Justin Spilker, Anthony H. Gonzalez, Y. Apostolovski, Manuel Aravena, M. Béthermin, S. C. Chapman, Chian-Chou Chen, Christopher C. Hayward, Yashar Hezaveh, Katrina C. Litke, Jingzhe Ma, Daniel P. Marrone, Warren R. Morningstar, Kedar A. Phadke, C. Reuter, Sreevani Jarugula, A. A. Stark, J. D. Vieira, A. Weiß

Bibliographic record

VenueThe Astrophysical Journal · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Star Formation Studies
Canadian institutionsDalhousie University
Fundersnot available
KeywordsPhysicsAstrophysicsGalaxyRedshiftSubmillimeter ArrayMillimeterAstronomyStar formationLine (geometry)Dust laneLuminous infrared galaxyInterstellar mediumGeometry

Abstract

fetched live from OpenAlex

Abstract We present Atacama Large Millimeter/submillimeter Array (ALMA) observations of high-J CO lines (J up = 6, 7, 8) and associated dust continuum toward five strongly lensed, dusty, star-forming galaxies at redshift z = 2.7–5.7. These galaxies, discovered in the South Pole Telescope survey, are observed at 0.″2–0.″4 resolution with ALMA. Our high-resolution imaging coupled with the lensing magnification provides a measurement of the structure and kinematics of molecular gas in the background galaxies with spatial resolutions down to kiloparsec scales. We derive visibility-based lens models for each galaxy, accurately reproducing observations of four of the galaxies. Of these four targets, three show clear velocity gradients, of which two are likely rotating disks. We find that the reconstructed region of CO emission is less concentrated than the region emitting dust continuum even for the moderate-excitation CO lines, similar to what has been seen in the literature for lower-excitation transitions. We find that the lensing magnification of a given source can vary by 20%–50% across the line profile, between the continuum and line, and between different CO transitions. We apply Large Velocity Gradient modeling using apparent and intrinsic line ratios between lower-J and high-J CO lines. Ignoring these magnification variations can bias the estimate of physical properties of interstellar medium of the galaxies. The magnitude of the bias varies from galaxy to galaxy and is not necessarily predictable without high-resolution 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)0.001
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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.192
Teacher spread0.187 · 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

Explore more

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