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Record W4403898289 · doi:10.1093/mnras/stae2427

Viewing the PLATO LOPS2 field through the lenses of <i>TESS</i>

2024· article· en· W4403898289 on OpenAlexaff
Yoshi Nike Emilia Eschen, Daniel Bayliss, T. G. Wilson, Michelle Kunimoto, Ingrid Pelisoli, Toby Rodel

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstronomy and Astrophysical Research
Canadian institutionsUniversity of British Columbia
FundersMitutoyo Association for Science and TechnologyNational Aeronautics and Space Administration
KeywordsPhysicsAstronomyExoplanetField (mathematics)AstrophysicsTheoretical physicsClassical mechanicsStarsPure mathematics

Abstract

fetched live from OpenAlex

ABSTRACT PLATO will begin observing stars in its Southern Field (LOPS2) after its launch in late 2026. By this time, TESS will have observed the stars in LOPS2 for at least four years. We find that by 2025, on average each star in the PLATO field will have been monitored for 330 d by TESS, with a subset of stars in the TESS continuous viewing zone having over 1000 d of monitoring. There are currently 101 known transiting exoplanets in the LOPS2 field, with 36 of these residing in multiplanet systems. The LOPS2 field also contains more than 500 TESS planet candidate systems, 64 exoplanets discovered by radial velocity only, over 1000 bright (V&amp;lt;13) eclipsing binary systems, 7 transiting brown dwarf systems, and 2 bright white dwarfs (G&amp;lt;13). We calculate TESS and PLATO sensitivities to detecting transits for the bright FGK stars that make up the PLATO LOPS2 P1 sample. We find that TESS should have discovered almost all transiting giant planets out to approximately 30 d within the LOPS2 field, and out to approximately 100 d for the regions of the LOPS2 field within the TESS CVZ ($\sim 20$ per cent of the LOPS2 field). However, we find that for smaller radius planets in the range 1 – 4 R$_{\oplus }$PLATO will have significantly better sensitivity, and these are likely to make up the bulk of new PLATO discoveries.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.149
Threshold uncertainty score0.433

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.013
GPT teacher head0.251
Teacher spread0.238 · 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 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

Citations12
Published2024
Admission routes1
Has abstractyes

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