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Record W3105975015 · doi:10.1051/0004-6361/201526263

Galactic cold cores. VII. Filament formation and evolution: Methods and observational constraints

2016· preprint· en· W3105975015 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCaltechAUTHORS (California Institute of Technology) · 2016
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Star Formation Studies
Canadian institutionsCanadian Institute for Theoretical AstrophysicsUniversity of Toronto
FundersNational Astronomical Observatories, Chinese Academy of SciencesMax-Planck-Institut für AstronomieScience and Technology Facilities CouncilCentre National d’Etudes SpatialesBundesministerium für Verkehr, Innovation und TechnologieKU LeuvenCentre National de la Recherche ScientifiqueHungarian Scientific Research FundNational Aeronautics and Space AdministrationCalifornia Institute of TechnologyImperial College LondonUK Space Agency
KeywordsPhysicsProtein filamentAstrophysicsAstronomyObservational studyStellar evolutionGalactic nucleiGalaxyStarsMedicine

Abstract

fetched live from OpenAlex

Context. The association of filaments with protostellar objects has made these structures a priority target in star formation studies. However, little is known about the link between filament properties and their local environment. 
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\nAims. The datasets from the Herschel Galactic Cold cores key programme allow for a statistical study of filaments with a wide range of intrinsic and environmental characteristics. Characterisation of this sample can therefore be used to identify key physical parameters and quantify the role of the environment in the formation of supercritical filaments. These results are necessary to constrain theoretical models of filament formation and evolution. 
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\nMethods. Filaments were extracted from fields at distance D< 500 pc with the getfilaments algorithm and characterised according to their column density profiles and intrinsic properties. Each profile was fitted with a beam-convolved Plummer-like function, and the filament structure was quantified based on the relative contributions from the filament “core”, represented by a Gaussian, and “wing” component, dominated by the power-law behaviour of the Plummer-like function. These filament parameters were examined for populations associated with different background levels. 
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\nResults. Filaments increase their core (M_(line,core)) and wing (M_(line,wing)) contributions while increasing their total linear mass density (M_(line,tot)). Both components appear to be linked to the local environment, with filaments in higher backgrounds having systematically more massive M_(line,core) and M_(line,wing). This dependence on the environment supports an accretion-based model of filament evolution in the local neighbourhood (D ≤ 500 pc). Structures located in the highest backgrounds develop the highest central A_V, M_(line,core), and M_(line,wing) as M_(line,tot) increases with time, favoured by the local availability of material and the enhanced gravitational potential. Our results indicate that filaments acquiring a significantly massive central region with M_(line,core) ≳ M_(crit)/2 may become supercritical and form stars. This translates into a need for filaments to become at least moderately self-gravitating to undergo localised star formation or become star-forming filaments.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.760
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.032
GPT teacher head0.307
Teacher spread0.275 · 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