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Record W2958258857 · doi:10.3847/1538-4357/ab46b9

Analysis of Helium-rich White Dwarfs Polluted by Heavy Elements in the Gaia Era

2019· article· en· W2958258857 on OpenAlexaboutno aff

Bibliographic record

VenueThe Astrophysical Journal · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsnot available
Fundersnot available
KeywordsWhite dwarfStarsPhotometry (optics)SkyParallaxStellar classificationMain sequenceSpectral line

Abstract

fetched live from OpenAlex

Abstract We present an analysis of 1023 DBZ/DZ(A) and 319 DQ white dwarf stars taken from the Montreal White Dwarf Database. This represents a significant increase over the previous comprehensive studies on these types of objects. We use new trigonometric parallax measurements from the Gaia second data release, together with photometry from the Sloan Digital Sky Survey, Pan-STARRS, Gaia , or BVRI from the literature, which allow the determination of the mass for the majority of the objects in our sample. We use the photometric and spectroscopic techniques with our recently improved model atmospheres code, which include high-density effects, to accurately determine the effective temperature, surface gravity, and heavy-element abundances for each object. We study the abundance of hydrogen in DBZ/DZ white dwarfs and the properties of the accreted planetesimals. We explore the nature of the second sequence of DQ stars using proper motions from Gaia and highlight evidence of crystallization in massive DQ stars. We also present mass distributions for both spectral types. Finally, we discuss the implications of our findings in the context of the spectral evolution of white dwarfs and provide the atmospheric parameters for each star.

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)0.000
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 score0.534

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.007
GPT teacher head0.226
Teacher spread0.220 · 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

Citations128
Published2019
Admission routes1
Has abstractyes

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