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Record W2338956948 · doi:10.3847/0004-637x/823/2/160

AN ALMA SEARCH FOR SUBSTRUCTURE, FRAGMENTATION, AND HIDDEN PROTOSTARS IN STARLESS CORES IN CHAMAELEON I

2016· article· en· W2338956948 on OpenAlexaff
Michael M. Dunham, Stella S. R. Offner, J. E. Pineda, Tyler L. Bourke, John Tobin, Héctor G. Arce, Xuepeng Chen, James Di Francesco, Doug Johnstone, Katherine I. Lee, Philip C. Myers, Daniel J. Price, Sarah Sadavoy, Scott Schnee

Bibliographic record

VenueThe Astrophysical Journal · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Star Formation Studies
Canadian institutionsUniversity of VictoriaHerzberg Institute of Astrophysics
Fundersnot available
KeywordsProtostarAstrophysicsSubstructurePhysicsStar formationFragmentation (computing)PopulationMolecular cloudTurbulenceAstronomyStarsBiology

Abstract

fetched live from OpenAlex

ABSTRACT We present an Atacama Large Millimeter/submillimeter Array (ALMA) 106 GHz (Band 3) continuum survey of the complete population of dense cores in the Chamaeleon I molecular cloud. We detect a total of 24 continuum sources in 19 different target fields. All previously known Class 0 and Class I protostars in Chamaeleon I are detected, whereas all of the 56 starless cores in our sample are undetected. We show that the Spitzer+Herschel census of protostars in Chamaeleon I is complete, with the rate at which protostellar cores have been misclassified as starless cores calculated as <1/56, or <2%. We use synthetic observations to show that starless cores collapsing following the turbulent fragmentation scenario are detectable by our ALMA observations when their central densities exceed ∼108 cm−3, with the exact density dependent on the viewing geometry. Bonnor–Ebert spheres, on the other hand, remain undetected to central densities at least as high as 1010 cm−3. Our starless core non-detections are used to infer that either the star-formation rate is declining in Chamaeleon I and most of the starless cores are not collapsing, matching the findings of previous studies, or that the evolution of starless cores are more accurately described by models that develop less substructure than predicted by the turbulent fragmentation scenario, such as Bonnor–Ebert spheres. We outline future work necessary to distinguish between these two possibilities.

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 score0.015
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.280
Teacher spread0.266 · 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

Citations62
Published2016
Admission routes1
Has abstractyes

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