MétaCan
Menu
Back to cohort
Record W1968846983 · doi:10.1093/mnras/stu1684

Magnetically controlled mass-loss from extrasolar planets in close orbits

2014· article· en· W1968846983 on OpenAlexaff
James E. Owen, Fred C. Adams

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsCanadian Institute for Theoretical Astrophysics
Fundersnot available
KeywordsPhysicsExoplanetAstrophysicsPlanetHot JupiterMagnetic fieldPlanetary massField strengthOutflowFlux (metallurgy)Planetary systemField lineAstronomy

Abstract

fetched live from OpenAlex

We consider the role magnetic fields play in guiding and controlling mass-loss via evaporative outflows from exoplanets that experience UV irradiation. First, we present analytic results that account for planetary and stellar magnetic fields, along with mass-loss from both the star and planet. We then conduct series of numerical simulations for gas giant planets, and vary the planetary field strength, background stellar field strength, UV heating flux, and planet mass. These simulations show that the flow is magnetically controlled for moderate field strengths and even the highest UV fluxes, i.e. planetary surface fields BP ≳ 0.3 G and fluxes FUV ∼ 106 erg s−1. We thus conclude that outflows from all hot Jupiters with moderate surface fields are magnetically controlled. The inclusion of magnetic fields highly suppresses outflow from the night side of the planet. Only the magnetic field lines near the pole are open and allow outflow to occur. The fraction of open field lines depends sensitively on the strength (and geometry) of the background magnetic field from the star, along with the UV heating rate. The net effect of the magnetic field is to suppress the mass-loss rate by (approximately) an order of magnitude. Finally, some open field lines do not allow the flow to pass smoothly through the sonic point; flow along these streamlines does not reach a steady state, resulting in time-variable mass-loss.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.110
Threshold uncertainty score0.827

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.005
GPT teacher head0.190
Teacher spread0.185 · 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

Citations139
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueMonthly Notices of the Royal Astronomical SocietySame topicStellar, planetary, and galactic studiesFrench-language works237,207