MétaCan
Menu
Back to cohort
Record W2072390915 · doi:10.1086/503795

Giant Planet Accretion and Migration: Surviving the Type I Regime

2006· article· en· W2072390915 on OpenAlexaff
Edward W. Thommes, Norman Murray

Bibliographic record

VenueThe Astrophysical Journal · 2006
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Star Formation Studies
Canadian institutionsCanadian Institute for Theoretical AstrophysicsUniversity of Toronto
Fundersnot available
KeywordsGas giantPhysicsPlanetAccretion (finance)Giant planetAstrophysicsJovianAstronomyPlanetary migrationGravitational collapseProtoplanetary diskAstrobiologyExoplanetPlanetary system

Abstract

fetched live from OpenAlex

In the standard model of gas giant planet formation, a large solid core (~10 times the Earth's mass) forms first, then accretes its massive envelope (100 or more Earth masses) of gas. However, inward planet migration due to gravitational interaction with the protostellar gas disk poses a difficulty in this model. Core-sized bodies undergo rapid "type I" migration; for typical parameters their migration timescale is much shorter than their accretion timescale. How, then, do growing cores avoid spiraling into the central star before they ever get the chance to become gas giants? Here, we present a simple model of core formation in a gas disk that is viscously evolving. As the disk dissipates, accretion and migration timescales eventually become comparable. If this happens while there is still enough gas left in the disk to supply a Jovian atmosphere, then a window of opportunity for gas giant formation opens. We examine under what circumstances this happens, and thus, what predictions our model makes about the link between protostellar disk properties and the likelihood of forming giant planets.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0010.002
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 head0.008
GPT teacher head0.216
Teacher spread0.207 · 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

Citations45
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueThe Astrophysical JournalSame topicAstrophysics and Star Formation StudiesFrench-language works237,207