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Record W4307633617 · doi:10.3847/1538-3881/ac959a

Evidence of Long-term Period Variations in the Exoplanet Transit Database (ETD)

2022· article· en· W4307633617 on OpenAlexafffund
Simone R. Hagey, Billy Edwards, Aaron C. Boley

Bibliographic record

VenueThe Astronomical Journal · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsExoplanetPhysicsHot JupiterTransit (satellite)Orbital periodPlanetPeriod (music)Gas giantAstronomyJupiter (rocket family)DatabaseAstrophysicsStarsComputer science

Abstract

fetched live from OpenAlex

Abstract We analyze a large number of citizen science data and identify eight hot Jupiter systems that show evidence for deviations from a constant orbital period: HAT-P-19 b, HAT-P-32 b, TrES-1 b, TrES-2 b, TrES-5 b, WASP-4 b, WASP-10 b, and WASP-12 b. The latter system is already well known to exhibit strong evidence for tidal orbital decay and serves as an important control for this study. Several other systems we identify have disputed period drifts in the literature, allowing the results here to serve as an independent analysis. The citizen science data are from the Exoplanet Transit Database (ETD), which is a global project established in 2008 by the Variable Star and Exoplanet Section of the Czech Astronomical Society. With over 400 planets and 12,000 contributed observations spanning 15 yr, the ETD is brimming with potential for studying the long-term orbital evolution of close-in hot Jupiters. We use our results to discuss prioritization of targets for follow-up investigations, which will be necessary to confirm the period drifts and their causes.

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)0.002
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.007
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.032
GPT teacher head0.258
Teacher spread0.227 · 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 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

Citations21
Published2022
Admission routes2
Has abstractyes

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