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Record W3217286902 · doi:10.3847/1538-4357/ac3ed6

Kepler-167e as a Probe of the Formation Histories of Cold Giants with Inner Super-Earths

2022· article· en· W3217286902 on OpenAlexaff
Yayaati Chachan, Paul A. Dalba, Heather A. Knutson, Benjamin J. Fulton, Daniel Thorngren, Charles Beichman, David R. Ciardi, Andrew W. Howard, Judah Van Zandt

Bibliographic record

VenueThe Astrophysical Journal · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsPhysicsAstronomyKeplerAstrobiologyAstrophysicsPlanet

Abstract

fetched live from OpenAlex

Abstract The observed correlation between outer giant planets and inner super-Earths is emerging as an important constraint on planet formation theories. In this study, we focus on Kepler-167, which is currently the only system known to contain both inner transiting super-Earths and a confirmed outer transiting gas giant companion beyond 1 au. Using long-term radial velocity monitoring, we measure the mass of the gas giant Kepler-167e ( P = 1071 days) to be 1.01 − 0.15 + 0.16 M J , thus confirming it as a Jupiter analog. We refit the Kepler photometry to obtain updated radii for all four planets. Using a planetary structure model, we estimate that Kepler-167e contains 66 ± 19 M ⊕ of solids and is significantly enriched in metals relative to its solar-metallicity host star. We use these new constraints to explore the broader question of how systems like Kepler-167 form in the pebble accretion framework for giant planet core formation. We utilize simple disk evolution models to demonstrate that more massive and metal-rich disks, which are the most favorable sites for giant planet formation, can also deliver enough solids to the inner disk to form systems of super-Earths. We use these same models to constrain the nature of Kepler-167's protoplanetary disk and find that it likely contained ≳300 M ⊕ of dust and was ≳40 au in size. These values overlap with the upper end of the observed dust mass and size distributions of Class 0 and I disks and are also consistent with the observed occurrence rate of Jupiter analogs around Sun-like stars.

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)0.001
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.193
Teacher spread0.186 · 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

Citations25
Published2022
Admission routes1
Has abstractyes

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