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Record W2465025257 · doi:10.1093/mnras/stw1038

The hot γ Doradus and Maia stars

2016· article· en· W2465025257 on OpenAlexaff
L. A. Balona, C. A. Engelbrecht, Y. C. Joshi, S. C. Joshi, Kaushal Kumar Sharma, Е. А. Семенко, Gajendra Pandey, N. K. Chakradhari, D. E. Mkrtichian, B. P. Hema, J. M. Nemec

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsCamosun College
Fundersnot available
KeywordsPhysicsStarsInstability stripAstrophysicsHertzsprung–Russell diagramSpectral lineInstabilityAstronomyStellar evolution

Abstract

fetched live from OpenAlex

The hot γ Doradus stars have multiple low frequencies characteristic of γ Dor or SPB variables, but are located between the red edge of the SPB and the blue edge of the γ Dor instability strips where all low-frequency modes are stable in current models of these stars. Though δ Sct stars also have low frequencies, there is no sign of high frequencies in hot γ Dor stars. We obtained spectra to refine the locations of some of these stars in the H–R diagram and conclude that these are, indeed, anomalous pulsating stars. The Maia variables have multiple high frequencies characteristic of β Cep and δ Sct stars, but lie between the red edge of the β Cep and the blue edge of the δ Sct instability strips. We compile a list of all Maia candidates and obtain spectra of two of these stars. Again, it seems likely that these are anomalous pulsating stars which are currently not understood.

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)0.001
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 score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.194
Teacher spread0.187 · 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

Citations37
Published2016
Admission routes1
Has abstractyes

Explore more

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