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Record W2059210687 · doi:10.1086/508557

Self‐Correlation Analysis of the Photometric Variability of T Tauri Stars

2006· article· en· W2059210687 on OpenAlexaff
John R. Percy, Wojciech Gryc, Janice C.‐Y. Wong, W. Herbst

Bibliographic record

VenuePublications of the Astronomical Society of the Pacific · 2006
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstro and Planetary Science
Canadian institutionsCanadian Institute for Theoretical AstrophysicsUniversity of Toronto
Fundersnot available
KeywordsAstrophysicsT Tauri starPhysicsStarsVariable starAmplitudeSpurious relationshipAccretion (finance)Light curveRotation periodFourier analysisVariation (astronomy)AstronomyFourier transform

Abstract

fetched live from OpenAlex

T Tauri stars are variable stars that are in an early phase of evolution, in which accretion and contraction to the main sequence are still taking place. Their photometric variability is complex; it takes place on a variety of timescales, due to a variety of physical processes. Periodic variability occurs due to rotation and the presence of cool or hot spots on the star. It may also occur due to periodic obscuration of the star by inhomogeneities in the still present accretion disk. But the periodicity may be masked by other forms of variability, or by time variation in the cool or hot spots, or the obscuring inhomogeneities. For other types of variable stars, self‐correlation has proven to be a useful adjunct to Fourier analysis for studying semiregular variability; it determines the cycle‐to‐cycle behavior of the star, averaged over all the data. We have therefore used it to investigate the photometric variability of about 30 T Tauri stars using existing data. It has provided useful information about periods and their coherence, about the amplitude of the periodic variation, or its upper limit, and about the "profile" of the amplitude‐timescale behavior. In most cases, it has confirmed periods previously determined by Fourier analysis, but in some cases it has suggested that the previously determined period is spurious.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.247

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.006
GPT teacher head0.194
Teacher spread0.188 · 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 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

Citations19
Published2006
Admission routes1
Has abstractyes

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