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Record W2340009919 · doi:10.3847/2041-8205/822/2/l27

DISCOVERY OF THREE PULSATING, MIXED-ATMOSPHERE, EXTREMELY LOW-MASS WHITE DWARF PRECURSORS*

2016· article· en· W2340009919 on OpenAlexaff
A. Gianninas, Brandon Curd, G. Fontaine, Warren R. Brown, Mukremin Kilic

Bibliographic record

VenueThe Astrophysical Journal Letters · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsAtmosphere (unit)White dwarfAstrobiologyWhite (mutation)PhysicsAstrophysicsAstronomyEnvironmental scienceChemistryMeteorologyStars

Abstract

fetched live from OpenAlex

ABSTRACT We report the discovery of pulsations in three mixed-atmosphere, extremely low-mass white dwarf (ELM WD, M ≤ 0.3 M ⊙) precursors. Following the recent discoveries of pulsations in both ELM and pre-ELM WDs, we targeted pre-ELM WDs with mixed H/He atmospheres with high-speed photometry. We find significant optical variability in all three observed targets with periods in the range 320–590 s, consistent in timescale with theoretical predictions of p-mode pulsations in mixed-atmosphere ≈0.18 M ⊙ He-core pre-ELM WDs. This represents the first empirical evidence that pulsations in pre-ELM WDs can only occur if a significant amount of He is present in the atmosphere. Future, more extensive, timeseries photometry of the brightest of the three new pulsators offers an excellent opportunity to constrain the thickness of the surface H layer, which regulates the cooling timescales for ELM WDs.

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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.204
Teacher spread0.194 · 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

Citations36
Published2016
Admission routes1
Has abstractyes

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