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Record W2900962508 · doi:10.3847/1538-4357/aaf057

Spatially Resolved [C ii] Emission in SPT0346-52: A Hyper-starburst Galaxy Merger at z ∼ 5.7

2019· article· en· W2900962508 on OpenAlexaff

Bibliographic record

VenueThe Astrophysical Journal · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsDalhousie University
FundersNational Institutes of Natural SciencesNational Astronomical Observatory of JapanFlatiron HealthGordon and Betty Moore FoundationNational Science FoundationKorea Astronomy and Space Science InstituteNational Radio Astronomy Observatory
KeywordsGalaxyGalaxy mergerLine (geometry)Star formationEmission spectrumLine-of-sight

Abstract

fetched live from OpenAlex

Abstract SPT0346-52 is one of the most most luminous and intensely star-forming galaxies in the universe, with and . In this paper, we present ALMA observations of the 158 μm emission line in this z = 5.7 dusty star-forming galaxy. We use a pixellated lensing reconstruction code to spatially and kinematically resolve the source-plane and rest-frame 158 μm dust continuum structure at ∼700 pc (∼0.″12) resolution. We discuss the deficit with a pixellated study of the L [C ii]/L FIR ratio in the source plane. We find that individual pixels within the galaxy follow the same trend found using unresolved observations of other galaxies, indicating that the deficit arises on scales ≲700 pc. The lensing reconstruction reveals two spatially and kinematically separated components (∼1 kpc and ∼500 km s−1 apart) connected by a bridge of gas. Both components are found to be globally unstable, with Toomre Q instability parameters everywhere. We argue that SPT0346-52 is undergoing a major merger, which is likely driving the intense and compact star formation.

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 score0.007
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.007
GPT teacher head0.205
Teacher spread0.199 · 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

Citations59
Published2019
Admission routes1
Has abstractyes

Explore more

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