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Record W4214937809 · doi:10.3847/1538-4357/ac474f

The Gas–Star Formation Cycle in Nearby Star-forming Galaxies. II. Resolved Distributions of CO and Hα Emission for 49 PHANGS Galaxies

2022· article· en· W4214937809 on OpenAlexafffund
Hsi-An Pan, Eva Schinnerer, Annie Hughes, Adam K. Leroy, Brent Groves, Ashley T. Barnes, Francesco Belfiore, Frank Bigiel, Guillermo A. Blanc, Yixian Cao, Mélanie Chevance, Enrico Congiu, Daniel A. Dale, Cosima Eibensteiner, Éric Emsellem, Christopher M. Faesi, Simon C. O. Glover, Kathryn Grasha, Cinthya N. Herrera, I-Ting Ho, Ralf S. Klessen, J. M. Diederik Kruijssen, P. Lang, Daizhong Liu, Rebecca McElroy, Sharon E. Meidt, E. J. Murphy, J. Pety, Miguel Querejeta, Alessandro Razza, Erik Rosolowsky, Toshiki Saito, Francesco Santoro, Andreas Schruba, Jiayi Sun, Neven Tomičić, A. Usero, Dyas Utomo, Thomas G. Williams

Bibliographic record

VenueThe Astrophysical Journal · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsUniversity of Alberta
FundersInstitut National de Physique Nucléaire et de Physique des ParticulesNational Institutes of Natural SciencesNatural Sciences and Engineering Research Council of CanadaAgencia Nacional de Investigación y DesarrolloMinisterio de Ciencia e InnovaciónCentre National de la Recherche ScientifiqueCentre National d’Etudes SpatialesNational Astronomical Observatory of JapanEuropean CommissionMax-Planck-GesellschaftDeutsche ForschungsgemeinschaftMinisterio de Ciencia, Innovación y UniversidadesAgencia Estatal de InvestigaciónNational Radio Astronomy ObservatoryKorea Astronomy and Space Science InstituteNational Science Foundation
KeywordsPhysicsAstrophysicsStar formationGalaxyAstronomy

Abstract

fetched live from OpenAlex

Abstract The relative distribution of molecular gas and star formation in galaxies gives insight into the physical processes and timescales of the cycle between gas and stars. In this work, we track the relative spatial configuration of CO and Hα emission at high resolution in each of our galaxy targets and use these measurements to quantify the distributions of regions in different evolutionary stages of star formation: from molecular gas without star formation traced by Hα to star-forming gas, and to H ii regions. The large sample, drawn from the Physics at High Angular resolution in Nearby GalaxieS ALMA and narrowband Hα (PHANGS-ALMA and PHANGS-Hα) surveys, spans a wide range of stellar masses and morphological types, allowing us to investigate the dependencies of the gas‒star formation cycle on global galaxy properties. At a resolution of 150 pc, the incidence of regions in different stages shows a dependence on stellar mass and Hubble type of galaxies over the radial range probed. Massive and/or earlier-type galaxies in our sample exhibit a significant reservoir of molecular gas without star formation traced by Hα, while lower-mass galaxies harbor substantial H ii regions that may have dispersed their birth clouds or formed from low-mass, more isolated clouds. Galactic structures add a further layer of complexity to the relative distribution of CO and Hα emission. Trends between galaxy properties and distributions of gas traced by CO and Hα are visible only when the observed spatial scale is ≪500 pc, reflecting the critical resolution requirement to distinguish stages of the star formation process.

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 score0.010
Threshold uncertainty score0.020

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 studies0.0000.000
Scholarly communication0.0000.000
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 head0.008
GPT teacher head0.227
Teacher spread0.219 · 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

Citations34
Published2022
Admission routes2
Has abstractyes

Explore more

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