MétaCan
Menu
Back to cohort
Record W4401121162 · doi:10.1093/mnras/stae1831

Two distinct molecular cloud populations detected in massive galaxies

2024· article· en· W4401121162 on OpenAlexafffund
Tom Rose, B. R. McNamara, F. Combes, A. C. Edge, Michael McDonald, Ewan O’Sullivan, H. R. Russell, A. C. Fabian, G. J. Ferland, P. Salomé, G. Tremblay

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2024
Typearticle
Languageen
FieldChemistry
TopicFullerene Chemistry and Applications
Canadian institutionsUniversity of Waterloo
FundersScience and Technology Facilities CouncilNational Astronomical Observatory of JapanCentre National de la Recherche ScientifiqueCanadian Space AgencyMax-Planck-GesellschaftNational Science FoundationKorea Astronomy and Space Science InstituteNational Institutes of Natural SciencesAgence Nationale de la Recherche
KeywordsPhysicsGalaxyAstrophysicsMolecular cloudAstronomyStars

Abstract

fetched live from OpenAlex

ABSTRACT We present new ALMA observations of CO, CN, CS, HCN, and HCO$^{+}$ absorption seen against the bright and compact radio continuum sources of eight galaxies. Combined with archival observations, they reveal two distinct populations of molecular clouds, which we identify by combining CO emission and absorption profiles to unambiguously reveal each cloud’s direction of motion and likely location. In galaxy discs, we see clouds with low velocity dispersions, low line-of-sight velocities, and a lack of any systemic inflow or outflow. In galactic cores, we find high velocity dispersion clouds inflowing at up to 550 km s−1. This provides observational evidence in favour of cold accretion on to galactic centres, which likely contributes to the fuelling of active galactic nuclei. We also see a wide range in the CO(2-1)/CO(1-0) ratios of the absorption lines. This is likely the combined effect of hierarchical substructure within the molecular clouds and continuum sources which vary in size with frequency.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.194
Threshold uncertainty score0.543

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 head0.010
GPT teacher head0.231
Teacher spread0.222 · 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 designSimulation or modeling
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

Citations10
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueMonthly Notices of the Royal Astronomical SocietySame topicFullerene Chemistry and ApplicationsFrench-language works237,207