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Record W306130932 · doi:10.1017/s0252921100016651

Frequency Analysis of a Subset of Fundamental Mode RR Lyrae Stars from the MACHO Project Large Magellanic Cloud Database

2002· article· en· W306130932 on OpenAlexaff
D. L. Welch, G. Kovács, K. H. Cook, C. Alcock, R. A. Allsman, D. R. Alves, T. S. Axelrod, A. C. Becker, D. P. Bennett, A. J. Drake, K. C. Freeman, Marla Geha, K. Griest, M. J. Lehner, S. Marshall, D. Minniti, C. Nelson, B. A. Peterson, Piotr Popowski, M. R. Pratt, Peter J. Quinn, A. W. Rodgers, C. W. Stubbs, William J. Sutherland, T. Vandehei

Bibliographic record

VenueInternational Astronomical Union Colloquium · 2002
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsMcMaster University
FundersNational Nuclear Security AdministrationHungarian Scientific Research FundLawrence Livermore National LaboratoryU.S. Department of Energy
KeywordsRR Lyrae variablePhysicsLarge Magellanic CloudAstrophysicsStarsVariable starPhotometry (optics)Globular clusterPopulationAstronomySpectral lineOvertoneMedicine

Abstract

fetched live from OpenAlex

Abstract We present the preliminary results of a frequency analysis of 1457 fundamental mode RR Lyrae (RR0) stars in the Large Magellanic Cloud (LMC) from MACHO Project photometry. We find the same classes of pulsational behavior as were found in our earlier survey of first overtone RR Lyrae (RR1) stars. Variables whose prewhitened power spectra contain one or two peaks close to the main frequency component in the original power spectra are commonly known as Blazhko-type variables. The present analysis shows the overall frequency of Blazhko-type stars in the total RR0 population analysed to date to be ≈ 10%. This is lower than the often cited Galactic field/globular rate of 20-30% (Szeidl, 1988). The incidence rate of Blazhko-type variability in the LMC appears to be about three times higher in RR0 stars than in RR1 stars. This puts important constraints on possible models of the Blazhko effect.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.998

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)0.0030.000

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 head0.019
GPT teacher head0.258
Teacher spread0.239 · 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.

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

Citations0
Published2002
Admission routes1
Has abstractyes

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