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MOST photometry of the RRd Lyrae variable AQ Leo: two radial modes, 32 combination frequencies and beyond

2007· article· en· W2021377149 on OpenAlexaff
M. Gruberbauer, K. Kolenberg, Jason F. Rowe, Daniel Huber, J. M. Matthews, P. Reegen, Robert Kuschnig, C. Cameron, T. Kallinger, W. W. Weiß, D. B. Guenther, A. F. J. Moffat, S. M. Ruciński, Dimitar Sasselov, G. A. H. Walker

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2007
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsUniversity of TorontoUniversité de MontréalSaint Mary's UniversitySt. Mary's UniversityUniversity of British Columbia
Fundersnot available
KeywordsPhysicsRR Lyrae variablePhotometry (optics)AstrophysicsOvertoneAstronomyAmplitudeVariable starStarsHarmonicsSpectral lineOptics

Abstract

fetched live from OpenAlex

Highly precise and nearly uninterrupted optical photometry of the RR Lyrae star AQ Leo was obtained with the MOST (Microvariability and Oscillations of Stars) satellite over 34.4 d in 2005 February–March. AQ Leo was the first known double-mode RR Lyrae pulsator (RRd star). Three decades after its discovery, MOST observations have revealed that AQ Leo oscillates with at least 42 frequencies, of which 32 are linear combinations (up to the sixth order) of the radial fundamental mode and its first overtone. Evidence for period changes of these modes is found in the data. The other intrinsic frequencies may represent an additional non-radial pulsation mode and its harmonics (plus linear combinations) which warrant theoretical modelling. The unprecedented number of frequencies detected with amplitudes down to mmag precision also presents an opportunity to test non-linear theories of mode growth and saturation in RRd 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)0.000
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.007
GPT teacher head0.206
Teacher spread0.199 · 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

Citations68
Published2007
Admission routes1
Has abstractyes

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