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Record W3106202617 · doi:10.5167/uzh-154504

Simulations of gaseous disc-embedded planet interaction

2004· article· en· W3106202617 on OpenAlexaff
Graeme Lufkin, Thomas Quinn, James Wadsley, Joachim Stadel, Fabio Governato

Bibliographic record

VenueZurich Open Repository and Archive (University of Zurich) · 2004
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Star Formation Studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPlanetPhysicsAccretion (finance)GravitationGas giantInstabilityGravitational instabilitySmoothed-particle hydrodynamicsAstrophysicsJupiter massTerrestrial planetExoplanetAstronomyPlanetary massMechanics

Abstract

fetched live from OpenAlex

We present global three-dimensional self-gravitating smoothed particle hydrodynamics (SPH) simulations of an isothermal gaseous disc interacting with an embedded planet. Discs of varying stability are simulated with planets ranging from 10 Earth masses to 2 Jupiter masses. The SPH technique provides the large dynamic range needed to accurately capture the large-scale behaviour of the disc and the small-scale interaction of the planet with surrounding material. Most runs used 105 gas particles, giving us the spatial resolution required to observe the formation of planets. We find four regions in parameter space: low-mass planets undergo type I migration; higher-mass planets can form a gap; the gravitational instability mode of planet formation in marginally stable discs can be triggered by embedded planets; discs that are completely unstable can fragment to form many planets. The disc stability is the most important factor in determining which interaction a system will exhibit. For the stable disc cases, our migration and accretion time-scales are shorter and scale differently from previously suggested

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.009
GPT teacher head0.218
Teacher spread0.209 · 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 designSimulation or modeling
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

Citations19
Published2004
Admission routes1
Has abstractyes

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