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Record W2808618292 · doi:10.3847/1538-4357/aaccfc

Spiral Arms in Disks: Planets or Gravitational Instability?

2018· article· en· W2808618292 on OpenAlexaff
Ruobing Dong, Joan Najita, S. Brittain

Bibliographic record

VenueThe Astrophysical Journal · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Star Formation Studies
Canadian institutionsUniversity of Victoria
FundersNational Aeronautics and Space AdministrationNational Science Foundation
KeywordsPhysicsPlanetAstrophysicsStarsAstronomySpiral galaxyAccretion (finance)Gravitational instabilityPlanetary systemProtoplanetary diskGiant planetGalaxy

Abstract

fetched live from OpenAlex

Abstract Spiral arm structures seen in scattered-light observations of protoplanetary disks can potentially serve as signposts of planetary companions. They can also lend unique insights into disk masses, which are critical in setting the mass budget for planet formation but are difficult to determine directly. A surprisingly high fraction of disks that have been well studied in scattered light have spiral arms of some kind (8/29), as do a high fraction (6/11) of well-studied Herbig intermediate-mass stars (i.e., Herbig stars >1.5 M ⊙ ). Here we explore the origin of spiral arms in Herbig systems by studying their occurrence rates, disk properties, and stellar accretion rates. We find that two-arm spirals are more common in disks surrounding Herbig intermediate-mass stars than are directly imaged giant planet companions to mature A and B stars. If two-arm spirals are produced by such giant planets, this discrepancy suggests that giant planets are much fainter than predicted by hot-start models. In addition, the high stellar accretion rates of Herbig stars, if sustained over a reasonable fraction of their lifetimes, suggest that disk masses are much larger than inferred from their submillimeter continuum emission. As a result, gravitational instability is a possible explanation for multiarm spirals. Future observations can lend insights into the issues raised here.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.591
Threshold uncertainty score0.401

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 head0.017
GPT teacher head0.271
Teacher spread0.254 · 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 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

Citations83
Published2018
Admission routes1
Has abstractyes

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