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Record W2050646895 · doi:10.1088/0004-637x/698/1/405

DISCOVERY OF THE WIDEST VERY LOW MASS FIELD BINARY

2009· article· en· W2050646895 on OpenAlexaff
Jacqueline Radigan, David Lafreniére, Ray Jayawardhana, René Doyon

Bibliographic record

VenueThe Astrophysical Journal · 2009
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsUniversité de MontréalUniversité du Québec à MontréalCanadian Institute for Theoretical AstrophysicsUniversity of Toronto
Fundersnot available
KeywordsSkyProper motionBinary numberStarsPhysicsMotion (physics)AstrophysicsLow MassComponent (thermodynamics)Field (mathematics)Spectral lineAstronomyMathematics

Abstract

fetched live from OpenAlex

We present the discovery of the widest (∼6700 AU) very low mass (VLM) field binary to date, found in a proper motion cross-match of the Sloan Digital Sky Survey and the Two Micron All Sky Survey. Our follow-up J -band imaging provides a 10 year baseline for measuring proper motions. Consequently, we are able to confirm the common proper motion of the pair to within 10 mas, implying a 99.5% probability of their physical association. Near-infrared spectra of the components indicate spectral types of M6 ± 1 and M7 ± 1. The system resides at a spectroscopic distance of 105 ± 13 pc and has an angular separation of 63 38 ± 0 05. We have used evolutionary models to infer component masses of 0.105 +0.029 −0.017 M ☉ and 0.091 +0.010 −0.007 M ☉ . The large separation and low binding energy of this system can provide constraints for formation models of VLM stars.

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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.007
GPT teacher head0.210
Teacher spread0.203 · 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

Citations43
Published2009
Admission routes1
Has abstractyes

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