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Record W2061683826 · doi:10.1088/0004-637x/799/1/33

STATISTICAL ANALYSIS OF INTERFEROMETRIC MEASUREMENTS OF AXIS RATIOS FOR CLASSICAL Be STARS

2015· article· en· W2061683826 on OpenAlexafffund
R. P. Cyr, C. E. Jones, C. Tycner

Bibliographic record

VenueThe Astrophysical Journal · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhysicsMonte Carlo methodAstrophysicsStarsInterferometryLine (geometry)Star (game theory)Thin diskOpticsComputational physicsStatisticsMathematicsGeometry

Abstract

fetched live from OpenAlex

This work presents a novel method to estimate the effective opening angle of CBe star disks from projected axis ratio measurements, obtained by interferometry using a statistical approach. A Monte Carlo scheme was used to generate a large set of theoretical axis ratios from disk models using different distributions of disk densities and opening angles. These theoretical samples were then compared to observational samples, using a two-sample Kolmogorov–Smirnov test, to determine which theoretical distribution best reproduces the observations. The results suggest that the observed ratio distributions in the K , H , and N band can best be explained by the presence of thin disks, with opening half-angles of the order of 0 15–4 0. Results for measurements over the Hα line point toward slightly thicker disks, 3 7–14°, which is consistent with a flaring disk predicted by the viscous disk model.

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)0.004
metaresearch head score (Gemma)0.016
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 score0.004
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.063
GPT teacher head0.291
Teacher spread0.228 · 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

Citations9
Published2015
Admission routes2
Has abstractyes

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