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Record W2138755640 · doi:10.3847/1538-3881/aa76e0

The Solar Neighborhood. XXXIX. Parallax Results from the CTIOPI and NOFS Programs: 50 New Members of the 25 parsec White Dwarf Sample

2017· article· en· W2138755640 on OpenAlexaff
John P. Subasavage, Wei‐Chun Jao, Todd J. Henry, Hugh C. Harris, C. C. Dahn, P. Bergeron, Pierre Dufour, B. H. Dunlap, B. N. Barlow, P. A. Ianna, Sébastien Lépine, S. Margheim

Bibliographic record

VenueThe Astronomical Journal · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsParallaxWhite dwarfAstrometryPhysicsAstrophysicsObservatoryAstronomySolar SystemProper motionStars

Abstract

fetched live from OpenAlex

Abstract We present 114 trigonometric parallaxes for 107 nearby white dwarf (WD) systems from both the Cerro Tololo Inter-American Observatory Parallax Investigation (CTIOPI) and the U. S. Naval Observatory Flagstaff Station (NOFS) parallax programs. Of these, 76 parallaxes for 69 systems were measured by the CTIOPI program and 38 parallaxes for as many systems were measured by the NOFS program. A total of 50 systems are confirmed to be within the 25-pc horizon of interest. Coupled with a spectroscopic confirmation of a common proper-motion companion to a Hipparcos star within 25 pc as well as confirmation parallax determinations for two WD systems included in the recently released Tycho Gaia Astrometric Solution catalog, we add 53 new systems to the 25-pc WD sample—a 42% increase. Our sample presented here includes four strong candidate halo systems, a new metal-rich DAZ WD, a confirmation of a recently discovered nearby short-period ( P = 2.85 hr) double degenerate, a WD with a new astrometric perturbation (long period, unconstrained with our data), and a new triple system where the WD companion main-sequence star has an astrometric perturbation ( P ∼ 1.6 year).

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.021
GPT teacher head0.236
Teacher spread0.215 · 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.

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

Citations61
Published2017
Admission routes1
Has abstractyes

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