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Record W3098896129 · doi:10.3847/0004-637x/817/2/107

ATMOSPHERES OF LOW-MASS PLANETS: THE “BOIL-OFF”

2016· article· en· W3098896129 on OpenAlexaff
James E. Owen, Yanqin Wu

Bibliographic record

VenueThe Astrophysical Journal · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPlanetPhotoevaporationPhysicsAstrophysicsPlanetary massRADIUSGas giantAstronomyAtmosphere (unit)ExoplanetProtoplanetary diskMeteorology

Abstract

fetched live from OpenAlex

ABSTRACT We show that, for a low-mass planet that orbits its host star within a few tenths of an AU (like the majority of the Kepler planets), the atmosphere it was able to accumulate while embedded in the protoplanetary disk may not survive unscathed after the disk disperses. This gas envelope, if more massive than a few percent of the core (with a mass below ), has a cooling time that is much longer than the timescale on which the planet exits the disk. As such, it could not have contracted significantly from its original size, of the order of the Bondi radius. So a newly exposed protoplanet would be losing mass via a Parker wind that is catalyzed by the stellar continuum radiation. This represents an intermediate stage of mass-loss, occurring soon after the disk has dispersed, but before the EUV/X-ray driven photoevaporation becomes relevant. The surface mass-loss induces a mass movement within the envelope that advects internal heat outward. As a result, the planet atmosphere rapidly cools down and contracts, until it has reached a radius of the order of 0.1 Bondi radius, at which time the mass-loss effectively shuts down. Within a million years after the disk disperses, we find a planet that has only about 10% of its original envelope, and a Kelvin–Helmholtz time that is much longer than its actual age. We suggest that this “boil-off” process may be partially responsible for the lack of planets above a radius of in the Kepler data, provided planet formation results in initial envelope masses of tens of percent.

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 score0.263
Threshold uncertainty score0.597

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)0.0010.000

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 head0.007
GPT teacher head0.207
Teacher spread0.200 · 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

Citations229
Published2016
Admission routes1
Has abstractyes

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