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Record W2611613970 · doi:10.1093/mnras/stx2190

The first optical spectra of Wolf–Rayet stars in M101 revealed with Gemini/GMOS

2017· article· en· W2611613970 on OpenAlexaff
J. L. Pledger, Michael M. Shara, Matthew C. Wilde, P. A. Crowther, K. S. Long, David Zurek, A. F. J. Moffat

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGamma-ray bursts and supernovae
Canadian institutionsUniversité de Montréal
FundersScience and Technology Facilities CouncilNational Aeronautics and Space Administration
KeywordsPhysicsStarsWolf–Rayet starAstrophysicsSpiral galaxySupernovaAstronomyGalaxy

Abstract

fetched live from OpenAlex

Deep narrow-band HST imaging of the iconic spiral galaxy M101 has revealed over a thousand new Wolf Rayet (WR) candidates. We report spectrographic confirmation of 10 HeII emission line sources hosting 15 WR stars. We find WR stars present at both sub- and super-solar metalicities with WC stars favouring more metal-rich regions compared to WN stars. We investigate the association of WR stars with HII regions using archival HST imaging and conclude that the majority of WR stars are in or associated with HII regions. Of the 10 emission lines sources, only one appears to be unassociated with a star-forming region. Our spectroscopic survey provides confidence that our narrow-band photometric candidates are in fact bonafide WR stars, which will allow us to characterise the progenitors of any core-collapse supernovae that erupt in the future in M101.

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)0.000
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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.008
GPT teacher head0.208
Teacher spread0.200 · 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

Citations4
Published2017
Admission routes1
Has abstractyes

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