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Record W2073808060 · doi:10.1051/0004-6361:20011782

(Sub)millimetre emission from NGC 1569: An abundance of very small grains

2002· article· en· W2073808060 on OpenAlexaff
U. Lisenfeld, F. P. Israel, J. M. Stil, A. Sievers

Bibliographic record

VenueAstronomy and Astrophysics · 2002
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Star Formation Studies
Canadian institutionsQueen's University
FundersNational Aeronautics and Space Administration
KeywordsAstrophysicsPhysicsGalaxyJames Clerk Maxwell TelescopeMillimeterInterstellar mediumMolecular cloudPopulationCosmic dustAstronomyStar formation

Abstract

fetched live from OpenAlex

We present new data of the dwarf galaxy NGC 1569 at 450 μm, 850 μm and 1200 μm taken with SCUBA at the JCMT and the bolometer array at the IRAM 30 m telescope. After including data from IRAS at 12, 25, 60 and 100 μm, we have successfully fitted the dust grain population model of Désert et al. (1990) to the observed midinfrared-to-millimetre spectrum. The fit requires a combination of both large and very small grains exposed to a strong radiation field as well as an enhancement of the number of very small grains relative to the number of large grains. We interpret this as the consequence of large grain destruction due to shocks in the turbulent interstellar medium of NGC 1569. The contribution of polyaromatic hydrocarbons (PAH's) is found to be negligible. Comparison of the dust emission maps with an HI map of similar resolution shows that both dust and molecular gas distributions peak close to the radio continuum maximum and at a minimum in the HI distribution. From a comparison of these three maps and assuming that the gas-to-dust mass ratio is the same everywhere, we estimate the ratio of molecular hydrogen column density to integrated CO intensity to be about 25–30 times the local Galactic value. The gas-to-dust ratio is 1500–2900, about an order of magnitude higher than in the Solar Neighbourhood.

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 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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.952
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.013
GPT teacher head0.206
Teacher spread0.192 · 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 teacher head, not a consensus.

Study designOther design
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

Citations96
Published2002
Admission routes1
Has abstractyes

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