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Record W3092264961

Probing the Photosphere/Wind Connection in Hot Stars with a Long-Exposure Chandra Observation of Zeta Puppis: X-Ray and Optical Variability

2020· article· en· W3092264961 on OpenAlexaff
N. A. Miller, Joy S. Nichols, Yaël Nazé, David P. Huenemoerder, A. F. J. Moffat, J. Lauer, Richard Ignace, W. L. Waldron, K. G. Gayley, W.‐R. Hamann, L. M. Oskinova, Tahina Ramiaramanantsoa, Noel D. Richardson

Bibliographic record

VenueOpen Repository and Bibliography (University of Liège) · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsPhysicsStarsAstrophysicsPhotosphereAstronomyX-rayOpticsSpectral line
DOInot available

Abstract

fetched live from OpenAlex

Many previous studies of ζ Puppis (O4I(n)fp) at a variety of wave bands have reported periodic variability for this star. These studies found periods ranging from less than a day up to approximately 5 days, with much recent interest centered on the variability with a period of 1.78 days. We are using time-resolved data for Zeta Puppis from the High Energy Transmission Grating/ACIS-S instrument on the Chandra spacecraft to investigate the variability of this star in the X-ray band. The X-ray data was obtained during the following three intervals: July/August 2018 (464.0 ks), January/February 2010 (74.7 ks), and July/August 2019 (274.4 ks), for a total of 813.1 ks. In this study we concentrate on the temporal behavior of broad-band X-ray spectral regions. These bands are chosen to be wide enough to achieve adequate count rates in the short time intervals required to investigate periodic signals on the time scales described above. We compare this X-ray data with nearly contemporaneous high precision optical space photometric monitoring performed by the BRITE optical satellite array (including some corroborative data from TESS) to explore connections between the star's photosphere and its strong outflowing wind.

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 score0.387

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
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 head0.016
GPT teacher head0.193
Teacher spread0.176 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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