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Record W4303985113 · doi:10.1051/0004-6361/202243659

Stellar population of the Rosette Nebula and NGC 2244

2022· article· en· W4303985113 on OpenAlexfundno aff
K. Mužić, V. Almendros-Abad, H. Bouy, Karolina Kubiak, Karla Peña Ramírez, A. Krone-Martins, A. Moitinho, Miguel Conceição

Bibliographic record

VenueAstronomy and Astrophysics · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Star Formation Studies
Canadian institutionsnot available
FundersPlanetary Science DivisionInstitut national des sciences de l'UniversFundação para a Ciência e a TecnologiaCanadian Space AgencyScience Mission DirectorateInstituto de Astrofísica de CanariasSmithsonian Astrophysical ObservatoryUniversity of EdinburghMax-Planck-Institut für AstronomieNvidiaAgencia Nacional de Investigación y DesarrolloNational Central UniversityCentre National de la Recherche ScientifiqueQueen's UniversityAgence Nationale de la RechercheSpace Telescope Science InstituteEötvös Loránd TudományegyetemCalifornia Institute of TechnologyEuropean CommissionLos Alamos National LaboratoryEuropean Space AgencyJohns Hopkins UniversityQueen's University BelfastNational Science FoundationNational Aeronautics and Space AdministrationDurham UniversitySmithsonian Institution
KeywordsNebulaPhysicsAstrophysicsProper motionPhotometry (optics)Context (archaeology)Open clusterStar clusterPopulationExtinction (optical mineralogy)RADIUSAstronomyStarsPaleontologyOpticsBiology

Abstract

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Context.Measurements of internal dynamics of young clusters and star-forming regions are crucial to fully understand the process of their formation. A basic prerequisite for this is a well-established and robust list of probable members. Aims.In this work, we study the 2.8° ×2.6° region in the emblematic Rosette Nebula, centred in the young cluster NGC 2244, with the aim of constructing the most reliable candidate member list to date. Using the obtained catalogue, we can determine various structural and kinematic parameters, which can help to draw conclusions about the past and the future of the region. Methods.We constructed a catalogue containing optical to mid-infrared photometry, as well as accurate positions and proper motions fromGaiaEDR3 for the sources in the field of the Rosette Nebula. We applied the probabilistic random forest algorithm to derive the membership probability for each source within our field of view. Based on the list of almost 3000 probable members, of which about a third are concentrated within the radius of 20′ from the centre of NGC 2244, we identified various clustered sources and stellar concentrations in the region, and estimated the average distance to the entire region at 1489 ± 37 pc, 1440 ± 32 pc to NGC 2244, and 1525 ± 36 pc to NGC 2237. The masses, extinction, and ages were derived by fitting the spectral energy distribution to the atmosphere and evolutionary models, and the internal dynamic was assessed via proper motions relative to the mean proper motion of NGC 2244. Results.NGC 2244 is showing a clear expansion pattern, with an expansion velocity that increases with radius. Its initial mass function (IMF) is well represented by two power laws (dN/dM ∝ M−α), with slopesα = 1.05 ± 0.02 for the mass range 0.2–1.5M⊙andα = 2.3 ± 0.3 for the mass range 1.5–20M⊙, and it is in agreement with slopes detected in other star-forming regions. The mean age of the region, derived from the HR diagram, is ∼2 Myr. We find evidence for the difference in ages between NGC 2244 and the region associated with the molecular cloud, which appears slightly younger. The velocity dispersion of NGC 2244 is well above the virial velocity dispersion derived from the total mass (1000 ± 70M⊙) and half-mass radius (3.4 ± 0.2 pc). From the comparison to other clusters and to numerical simulations, we conclude that NGC 2244 may be unbound and that it possibly may have even formed in a super-virial state.

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 score0.012
Threshold uncertainty score0.024

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 studies0.0000.000
Scholarly communication0.0000.000
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 head0.005
GPT teacher head0.193
Teacher spread0.188 · 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

Citations24
Published2022
Admission routes1
Has abstractyes

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