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Record W2609771036 · doi:10.3847/1538-4357/aa88c0

The EDGE–CALIFA Survey: Variations in the Molecular Gas Depletion Time in Local Galaxies

2017· article· en· W2609771036 on OpenAlexaff

Bibliographic record

VenueThe Astrophysical Journal · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsGalaxyStarsGravitational potentialDrop (telecommunication)Luminous infrared galaxyStar formationEnhanced Data Rates for GSM EvolutionGravitation

Abstract

fetched live from OpenAlex

Abstract We present results from the EDGE survey, a spatially resolved CO(1−0) follow-up to CALIFA, an optical Integral Field Unit survey of local galaxies. By combining the data products of EDGE and CALIFA, we study the variation in molecular gas depletion time ( τ dep ) on kiloparsec scales in 52 galaxies. We divide each galaxy into two parts: the center, defined as the region within , and the disk, defined as the region between 0.1 and . We find that 14 galaxies show a shorter τ dep (∼1 Gyr) in the center relative to that in the disk ( τ dep ∼ 2.4 Gyr), which means the central region in those galaxies is more efficient at forming stars per unit molecular gas mass. This finding implies that the centers with shorter τ dep resemble the intermediate regime between galactic disks and starburst galaxies. Furthermore, the central drop in τ dep is correlated with a central increase in the stellar surface density, suggesting that a shorter τ dep is associated with molecular gas compression by the stellar gravitational potential. We argue that varying the CO-to-H 2 conversion factor only exaggerates the central drop of τ dep .

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 score0.061
Threshold uncertainty score0.122

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.225
Teacher spread0.217 · 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

Citations75
Published2017
Admission routes1
Has abstractyes

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