MétaCan
Menu
Back to cohort
Record W3103567708

UNUSUAL DUST EMISSION FROM PLANETARY NEBULAE IN THE MAGELLANIC CLOUDS

2009· article· en· W3103567708 on OpenAlexaff
J. Bernard‐Salas, E. Peeters, S. Gutenkunst, M. Matsuura

Bibliographic record

VenueUCL Discovery (University College London) · 2009
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Star Formation Studies
Canadian institutionsWestern University
Fundersnot available
KeywordsPlanetary nebulaAstrophysicsPhysicsLarge Magellanic CloudSpectral lineEmission spectrumAstronomySmall Magellanic CloudGalaxyStars
DOInot available

Abstract

fetched live from OpenAlex

We present a Spitzer Space Telescope spectroscopic study of a sample of 25 planetary nebulae (PNe) in the Magellanic Clouds (MCs). The low-resolution modules are used to analyze the dust features present in the infrared spectra. This study complements a previous work by the same authors where the same sample was analyzed in terms of neon and sulfur abundances. Over half of the objects (14) show emission of polycyclic aromatic hydrocarbons, typical of carbon-rich dust environments. We compare the hydrocarbon emission in our objects to those of Galactic H II regions and PNe, and Large Magellanic Cloud/Small Magellanic Cloud H II regions. Amorphous silicates are seen in just two objects, enforcing the now well known fact that oxygen-rich dust is less common at low metallicities. Besides these common features, some PNe show very unusual dust. Nine objects show a strong silicon carbide feature at 11 mu m and 12 of them show magnesium sulfide emission starting at 25 mu m. The high percentage of spectra with silicon carbide in the MCs is not common. Two objects show a broadband which may be attributed to hydrogenated amorphous carbon and weak low-excitation atomic lines. It is likely that these nebulae are very young. The spectra of the remaining eight nebulae are dominated by the emission of fine-structure lines with a weak continuum due to thermal emission of dust, although in a few cases the signal-to-noise ratio in the spectra is low, and weak dust features may not have been detected.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.626
Threshold uncertainty score0.575

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 communication0.0000.001
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 head0.007
GPT teacher head0.189
Teacher spread0.182 · 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.

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

Citations46
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueUCL Discovery (University College London)Same topicAstrophysics and Star Formation StudiesFrench-language works237,207