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Record W2073451155 · doi:10.1086/508144

Model Atmosphere Analysis of the Weakly Magnetic DZ White Dwarf G165‐7

2006· article· en· W2073451155 on OpenAlexaff

Bibliographic record

VenueThe Astrophysical Journal · 2006
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsWhite dwarfZeeman effectSpectral linePolarization (electrochemistry)SkyMagnetic fieldStellar atmosphereFlux (metallurgy)Absorption spectroscopy

Abstract

fetched live from OpenAlex

A reanalysis of the strongly metal-blanketed DZ white dwarf G165-7 is presented. An improved grid of model atmospheres and synthetic spectra is used to analyze BVRI , JHK , and ugriz photometric observations as well as a high-quality Sloan Digital Sky Survey spectrum covering the energy distribution from 3600 to 9000 Å. The detection of splitting in several lines of Ca, Na, and Fe, suggesting a magnetic field of B s ~ 650 kG, is confirmed by spectropolarimetric observations that reveal as much as ±7.5% circular polarization in many of the absorption lines, most notably Na, Mg, and Fe. Our combined photometric and spectroscopic fit yields T eff = 6440 K, log g = 7.99, log(H/He) = -3.0, and log(Ca/He) = -8.1. The other heavy elements have solar ratios with respect to Ca, with the exception of Na and Cr, which had to be reduced by a factor of 2 and 3, respectively. A crude polarization model based on the observed local spectral flux gradient yields a longitudinal field of 165 kG, consistent with the mean surface field inferred from the Zeeman splitting. The inclusion of this weak magnetic field in our synthetic spectrum calculations, even in an approximate fashion, is shown to improve our fit significantly.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score0.157

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.201
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 designSimulation or modeling
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

Citations35
Published2006
Admission routes1
Has abstractyes

Explore more

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