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Record W2131616569 · doi:10.1051/0004-6361:200810529

Discovery of eclipsing binary central stars in the planetary nebulae M 3-16, H 2-29, and M 2-19

2008· article· en· W2131616569 on OpenAlexafffund
B. Miszalski, A. Acker, A. F. J. Moffat, Q. A. Parker, A. Udalski

Bibliographic record

VenueAstronomy and Astrophysics · 2008
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsUniversité de Montréal
FundersNatural Sciences and Engineering Research Council of CanadaMinisterstwo Edukacji i NaukiFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsPhysicsAstrophysicsBulgeLight curvePlanetary nebulaStarsAstronomyBinary numberBinary starRadial velocitySpectroscopyEclipse

Abstract

fetched live from OpenAlex

Progress in understanding the formation and evolution of planetary nebulae (PN) has been restricted by a paucity of well-determined central star masses. To address this deficiency we aim to (i) increase significantly the number of known eclipsing binary central stars of PN (CSPN); and subsequently (ii) measure directly their masses and absolute dimensions by combining their light curve parameters with planned radial velocity data. Using photometric data from the third phase of the Optical Gravitational Lensing Experiment (OGLE), we searched for periodic variability in a large sample of PN towards the Galactic Bulge using Fourier and phase-dispersion minimisation techniques. Among some dozen periodically variable CSPN found, we report on three new eclipsing binaries: M 3-16, H 2-29 and M 2-19. We present images, confirmatory spectroscopy and light curves of the systems.

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
Bibliometrics0.0010.001
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 head0.011
GPT teacher head0.198
Teacher spread0.187 · 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

Citations22
Published2008
Admission routes2
Has abstractyes

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