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Record W2148205276 · doi:10.1088/0004-637x/732/1/54

PREDICTING THE DETECTABILITY OF OSCILLATIONS IN SOLAR-TYPE STARS OBSERVED BY<i>KEPLER</i>

2011· article· en· W2148205276 on OpenAlexaff
W. J. Chaplin, H. Kjeldsen, T. R. Bedding, J. Christensen‐Dalsgaard, Ronald L. Gilliland, S. D. Kawaler, T. Appourchaux, Y. Elsworth, R. A. García, G. Houdek, C. Karoff, Τ. S. Metcalfe, J. Molenda‐Żakowicz, M. J. P. F. G. Monteiro, M. J. Thompson, G. A. Verner, Natalie M. Batalha, W. J. Borucki, Timothy M. Brown, Stephen T. Bryson, Jessie L. Christiansen, Bruce Clarke, Jon M. Jenkins, Todd C. Klaus, D. Koch, Deokkeun An, J. Ballot, Sarbani Basu, O. Benomar, A. Bonanno, A.-M. Broomhall, T. L. Campante, E. Corsaro, O. L. Creevey, Lisa Esch, Ning Gai, P. Gaulme, Steven J. Hale, R. Handberg, S. Hekker, Daniel Huber, S. Mathur, B. Mosser, R. New, Marc H. Pinsonneault, D. Pricopi, Pierre-Olivier Quirion, C. Régulo, I. W. Roxburgh, D. Salabert, Dennis Stello, M. D. Suran

Bibliographic record

VenueThe Astrophysical Journal · 2011
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsCanadian Space Agency
FundersScience and Technology Facilities Council
KeywordsAsteroseismologyPhysicsKeplerExoplanetStarsAstronomyAstrophysicsRADIUSPlanetMagnitude (astronomy)

Abstract

fetched live from OpenAlex

Asteroseismology of solar-type stars has an important part to play in the exoplanet program of the NASA Kepler Mission . Precise and accurate inferences on the stellar properties that are made possible by the seismic data allow very tight constraints to be placed on the exoplanetary systems. Here, we outline how to make an estimate of the detectability of solar-like oscillations in any given Kepler target, using rough estimates of the temperature and radius, and the Kepler apparent magnitude.

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)0.001
metaresearch head score (Gemma)0.007
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 score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0000.001
Research integrity0.0010.001
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 head0.223
Teacher spread0.191 · 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

Citations151
Published2011
Admission routes1
Has abstractyes

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