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Wolf-Rayet stars in M33 - I. Optical spectroscopy using CFHT-MOS

2004· article· en· W2126497509 on OpenAlexafffundabout
Jay B. Abbott, P. A. Crowther, Laurent Drissen, Luc Dessart, Pierre Martin, Guillaume Boivin

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2004
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaCentre National de la Recherche ScientifiqueRoyal SocietyNational Science Foundation
KeywordsPhysicsWolf–Rayet starAstrophysicsStarsMilky WayMetallicityGalaxyAstronomySpectroscopyStellar classificationWilliam Herschel TelescopeO-type starSpectrographSpectral line

Abstract

fetched live from OpenAlex

We have obtained spectroscopy of a large sample of Wolf–Rayet stars in M33 with the Canada–France–Hawaii Telescope Multi-Object Spectrograph (CFHT-MOS), including 26 WC stars, 15 WN stars and a WN/C star. In general, spectral types are merely refined, although the spectral type of X9 from Massey & Johnson is revised from WNL?+abs to WC4+abs, whilst their G1 and C21 candidates are not confirmed as Wolf–Rayet stars. We also re-examine the metallicity gradient of M33 from H ii regions and identify the present sample, lying in the inner disc, with 8.6 ≤ log(O/H) ≤ 8.9. Spectral types are in accord with similar regions in the Milky Way. Our large sample has allowed us to examine the claimed anticorrelation between WC linewidths and galactocentric distance by Schild et al. We find a much larger scatter, though there remains an absence of broad-line WC stars in the inner disc and narrow-line WC stars in the outer galaxy.

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 score0.021
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.223
Teacher spread0.213 · 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

Citations20
Published2004
Admission routes3
Has abstractyes

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