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Record W4381162273 · doi:10.1093/mnras/stad1752

Milliarcsecond structure and variability of methanol maser emission in three high-mass protostars

2023· article· en· W4381162273 on OpenAlexfundno aff
Artis Aberfelds, A. Bartkiewicz, M. Szymczak, Jānis Šteinbergs, G. Surcis, Agnieszka Kobak, M. Durjasz, I. Shmeld

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Star Formation Studies
Canadian institutionsnot available
FundersEuropean Regional Development FundHorizon 2020 Framework ProgrammeNarodowym Centrum NaukiInstitut sur la Nutrition et les Aliments FonctionnelsNarodowe Centrum NaukiEuropean Commission
KeywordsMaserVery-long-baseline interferometryPhysicsProtostarAstrophysicsSkyStar formationInterferometryAstronomyStars

Abstract

fetched live from OpenAlex

ABSTRACT The variability study of 6.7 GHz methanol masers has become a useful way to improve our understanding of the physical conditions in high-mass star-forming regions. Based on the single-dish monitoring using the Irbene telescopes, we selected three sources with close sky positions. We imaged them using the European very long baseline interferometry (VLBI) Network and searched available data on VLBI archives to follow detailed changes in their structures and single maser spot variability. All three targets show a few groups of maser cloudlets of a typical size of 3.5 mas and the majority of them show linear or arched structures with velocity gradients of order 0.22 km s−1 mas−1. The cloudlets and overall source morphologies are remarkably stable on time-scales of 7–15 yr, supporting a scenario of variability due to changes in the maser pumping rate.

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 score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.007
GPT teacher head0.212
Teacher spread0.205 · 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
Published2023
Admission routes1
Has abstractyes

Explore more

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