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Record W1984505858 · doi:10.1086/301297

New Faint Variable Stars in the Outer Regions of the Metal-rich Globular Cluster M71

2000· article· en· W1984505858 on OpenAlexaff
Nam‐Kyu Park, J. M. Nemec

Bibliographic record

VenueThe Astronomical Journal · 2000
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsDominion Astrophysical ObservatoryHerzberg Institute of Astrophysics
Fundersnot available
KeywordsPhysicsGlobular clusterVariable starStarsBlue stragglerPhotometry (optics)AstrophysicsAstronomyObservatory

Abstract

fetched live from OpenAlex

Sixteen photometric variable stars with mean V magnitudes between 15.2 and 20.3 have been discovered in a 16 7 × 16 7 field centered on the metal-rich globular cluster M71. The identifications are the result of a systematic time-series CCD imaging survey of the cluster using the Dominion Astrophysical Observatory 1.8 m telescope. Light curves and finding charts are presented for the newly identified stars (eight of which are definite variables, three probable, and five possible). These 16 stars, when combined with the seven faint variable stars discovered recently by Hodder et al. and Yan & Mateo, bring to 23 the number of faint variables now known in M71. The variable stars are of two basic types: W UMa– or Algol-like eclipsing binaries and SX Phoenicis radially pulsating variable blue straggler stars. Additional photometry is required to confirm the nature of the variability of several of the 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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
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 head0.010
GPT teacher head0.212
Teacher spread0.202 · 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

Citations12
Published2000
Admission routes1
Has abstractyes

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