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Record W3213082769 · doi:10.3847/1538-4357/ac382b

Accretion Flows or Outflow Cavities? Uncovering the Gas Dynamics around Lupus 3-MMS

2022· article· en· W3213082769 on OpenAlexaff
Travis J. Thieme, S. Lai, Sheng-Jun Lin, Pou-Ieng Cheong, Chin‐Fei Lee, Hsi-Wei Yen, Zhi‐Yun Li, Ka Ho Lam, Bo Zhao

Bibliographic record

VenueThe Astrophysical Journal · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Star Formation Studies
Canadian institutionsMcMaster University
FundersMinistry of Science and Technology, Taiwan
KeywordsPhysicsOutflowProtostarAccretion (finance)AstrophysicsAstronomyStar formationStars

Abstract

fetched live from OpenAlex

Abstract Understanding how material accretes onto the rotationally supported disk from the surrounding envelope of gas and dust in the youngest protostellar systems is important for describing how disks are formed. Magnetohydrodynamic simulations of magnetized, turbulent disk formation usually show spiral-like streams of material (accretion flows) connecting the envelope to the disk. However, accretion flows in these early stages of protostellar formation still remain poorly characterized, due to their low intensity, and possibly some extended structures are disregarded as being part of the outflow cavity. We use ALMA archival data of a young Class 0 protostar, Lupus 3-MMS, to uncover four extended accretion flow–like structures in C 18 O that follow the edges of the outflows. We make various types of position–velocity cuts to compare with the outflows and find the extended structures are not consistent with the outflow emission, but rather more consistent with a simple infall model. We then use a dendrogram algorithm to isolate five substructures in position–position–velocity space. Four out of the five substructures fit well (>95%) with our simple infall model, with specific angular momenta between 2.7–6.9 × 10 −4 km s −1 pc and mass-infall rates of 0.5–1.1 × 10 −6 M ⊙ yr −1 . Better characterization of the physical structure in the supposed “outflow cavities” is important to disentangle the true outflow cavities and accretion flows.

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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.011
GPT teacher head0.232
Teacher spread0.221 · 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

Citations42
Published2022
Admission routes1
Has abstractyes

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