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Record W3092140441 · doi:10.3847/1538-3881/abbe20

Searching for ZZ Ceti White Dwarfs in the Gaia Survey

2020· article· en· W3092140441 on OpenAlexafffund

Bibliographic record

VenueThe Astronomical Journal · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsCentre for Research in Astrophysics of Québec
FundersNatural Sciences and Engineering Research Council of CanadaCentre National de la Recherche ScientifiqueNational Aeronautics and Space AdministrationEuropean Space AgencyCalifornia Institute of TechnologyJet Propulsion Laboratory
KeywordsWhite dwarfInstability stripParallaxVariable starStarsAmplitudeInstabilitySouthern Hemisphere

Abstract

fetched live from OpenAlex

Abstract The Gaia satellite recently released parallax measurements for ∼260,000 high-confidence white dwarf candidates, allowing for precise measurements of their physical parameters. By combining these parallaxes with Pan-STARRS and u -band photometry, we measured the effective temperature and stellar mass for all white dwarfs in the Northern Hemisphere within 100 pc of the Sun, and identified a sample of ZZ Ceti white dwarf candidates within the so-called instability strip. We acquired high-speed photometric observations for 90 candidates using the PESTO camera attached to the 1.6 m telescope at the Mont-Mégantic Observatory. We report the discovery of 38 new ZZ Ceti stars, including two very rare ultramassive pulsators. We also identified five possibly variable stars within the strip, in addition to 47 objects that do not appear to show any photometric variability. However, several of those could be variable with an amplitude below our detection threshold, or could be located outside the instability strip due to errors in their photometric parameters. In the light of our results, we explore the trends of the dominant period and amplitude in the M – plane, and briefly discuss the question of the purity of the ZZ Ceti instability strip (i.e., a region devoid of non-variable 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 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 score0.023
Threshold uncertainty score0.296

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.047
GPT teacher head0.270
Teacher spread0.223 · 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

Citations34
Published2020
Admission routes2
Has abstractyes

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