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Record W3020752682 · doi:10.3847/1538-3881/abd73e

TESS Discovery of a Super-Earth and Three Sub-Neptunes Hosted by the Bright, Sun-like Star HD 108236

2021· article· en· W3020752682 on OpenAlexaff

Bibliographic record

VenueThe Astronomical Journal · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsCanadian Institute for Theoretical AstrophysicsUniversity of Toronto
Fundersnot available
KeywordsExoplanetPlanetTransit (satellite)Planetary systemRADIUSHot JupiterLight curveRadial velocity

Abstract

fetched live from OpenAlex

Abstract We report the discovery and validation of four extrasolar planets hosted by the nearby, bright, Sun-like (G3V) star HD 108236 using data from the Transiting Exoplanet Survey Satellite (TESS). We present transit photometry, reconnaissance, and precise Doppler spectroscopy, as well as high-resolution imaging, to validate the planetary nature of the objects transiting HD 108236, also known as the TESS Object of Interest (TOI) 1233. The innermost planet is a possibly rocky super-Earth with a period of days and has a radius of 1.586 ± 0.098 R ⊕ . The outer planets are sub-Neptunes, with potential gaseous envelopes, having radii of R ⊕ , 2.72 ± 0.11 R ⊕ , and R ⊕ and periods of days, days, and days, respectively. With V and K s magnitudes of 9.2 and 7.6, respectively, the bright host star makes the transiting planets favorable targets for mass measurements and, potentially, for atmospheric characterization via transmission spectroscopy. HD 108236 is the brightest Sun-like star in the visual ( V ) band known to host four or more transiting exoplanets. The discovered planets span a broad range of planetary radii and equilibrium temperatures and share a common history of insolation from a Sun-like star ( R ⋆ = 0.888 ± 0.017 R ⊙ , T eff = 5730 ± 50 K), making HD 108236 an exciting, opportune cosmic laboratory for testing models of planet formation and evolution.

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 score0.006
Threshold uncertainty score0.430

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)0.0000.000

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 head0.010
GPT teacher head0.202
Teacher spread0.192 · 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

Citations18
Published2021
Admission routes1
Has abstractyes

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