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Record W4385394865 · doi:10.1093/mnrasl/slad105

The ubiquity of carbon dredge-up in hydrogen-deficient white dwarfs as revealed by <i>GALEX</i>

2023· article· en· W4385394865 on OpenAlexafffund
Simon Blouin, Mukremin Kilic, Antoine Bédard, Pier-Emmanuel Tremblay

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society Letters · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsUniversity of Victoria
FundersKavli Institute for Theoretical Physics, University of California, Santa BarbaraNatural Sciences and Engineering Research Council of CanadaEuropean CommissionHorizon 2020 Framework ProgrammeNuclear Safety and Security CommissionH2020 European Research CouncilEuropean Space AgencyNational Aeronautics and Space AdministrationNational Science Foundation
KeywordsPhysicsAstrophysicsWhite dwarfCarbon fibersHydrogenAstronomyStars

Abstract

fetched live from OpenAlex

ABSTRACT The convective dredge-up of carbon from the interiors of hydrogen-deficient white dwarfs has long been invoked to explain the presence of carbon absorption features in the spectra of cool DQ stars ($T_{\rm eff} \lt 10\,000\,$K). It has been hypothesized that this transport process is not limited to DQ white dwarfs and also operates, albeit less efficiently, in non-DQ hydrogen-deficient white dwarfs within the same temperature range. This non-DQ population is predominantly composed of DC white dwarfs, which exhibit featureless optical spectra. However, no direct observational evidence of ubiquitous carbon pollution in DC stars has thus far been uncovered. In this Letter, we analyse data from the Galaxy Evolution Explorer to reveal the photometric signature of ultraviolet carbon lines in most DC white dwarfs in the $8500\, {\rm K} \le T_{\rm eff} \le 10\,500\,$K temperature range. Our results show that the vast majority of hydrogen-deficient white dwarfs experience carbon dredge-up at some point in their evolution.

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)0.000
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.006
GPT teacher head0.200
Teacher spread0.193 · 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

Citations13
Published2023
Admission routes2
Has abstractyes

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