MétaCan
Menu
Back to cohort
Record W7054819656

The ALMaQUEST Survey. XII. Dense Molecular Gas as Traced by HCN and HCO+ in Green Valley Galaxies

2023· article· en· W7054819656 on OpenAlexfundno aff

Bibliographic record

VenueApollo (University of Cambridge) · 2023
Typearticle
Languageen
FieldEngineering
TopicLaser Design and Applications
Canadian institutionsnot available
FundersLawrence Berkeley National LaboratoryDirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de MéxicoJapan Society for the Promotion of ScienceSmithsonian Astrophysical ObservatoryUniversity of Colorado BoulderInstituto de Astrofísica de CanariasOffice of ScienceMax-Planck-Institut für AstronomieNational Institutes of Natural SciencesMax-Planck-Institut für AstrophysikNational Science and Technology CouncilUniversidad Nacional Autónoma de MéxicoKorea Astronomy and Space Science InstituteMinistério da Ciência, Tecnologia e InovaçãoVanderbilt UniversityConsejo Nacional de Ciencia y TecnologíaUniversity of OxfordYork UniversityU.S. Department of EnergySmithsonian InstitutionNational Radio Astronomy ObservatoryNew Mexico State UniversityNational Astronomical Observatory of JapanLeibniz-GemeinschaftUniversity of Notre DameCarnegie Mellon UniversityAlfred P. Sloan FoundationUniversity of WashingtonJohns Hopkins UniversityCarnegie Institution of WashingtonUniversity of UtahOhio State UniversityNational Science FoundationUniversity of PortsmouthYale University
KeywordsGalaxyStar formationMass fractionGalaxy formation and evolutionIrregular galaxyStellar mass
DOInot available

Abstract

fetched live from OpenAlex

We present Atacama Large Millimeter/submillimeter Array (ALMA) observations of two dense gas tracers, HCN (1−0) and HCO+ (1-0) for three galaxies in the green valley and two galaxies on the star-forming main sequence with comparable molecular gas fractions as traced by the CO (1−0) emissions, selected from the ALMaQUEST survey. We investigate whether the deficit of molecular gas star formation efficiency (SFEmol) that leads to the low specific star formation rate (sSFR) in these green valley galaxies is due to a lack of dense gas (characterized by the dense gas fraction f dense) or the low star formation efficiency of dense gas (SFEdense). We find that SFEmol as traced by the CO emissions, when considering both star-forming and retired spaxels together, is tightly correlated with SFEdense and depends only weakly on f dense. The sSFR on kiloparsec scales is primarily driven by SFEmol and SFEdense, followed by the dependence on f mol, and is least correlated with f dense or the dense-gas-to-stellar mass ratio (R dense). When compared with other works in the literature, we find that our green valley sample shows lower global SFEmol and lower SFEdense while exhibiting similar dense gas fractions when compared to star-forming and starburst galaxies. We conclude that the star formation of the three green valley galaxies with a normal abundance of molecular gas is suppressed, mainly due to the reduced SFEdense rather than the lack of dense gas.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.834
Threshold uncertainty score0.782

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.008
GPT teacher head0.187
Teacher spread0.179 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueApollo (University of Cambridge)Same topicLaser Design and ApplicationsFrench-language works237,207