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Record W2997015600 · doi:10.1017/s1743921318005720

Extended Dust Emission from Nearby Evolved stars

2018· article· en· W2997015600 on OpenAlexaff
T. E. Dharmawardena, F. Kemper, Peter Scicluna, Jan G. A. Wouterloot, Alfonso Trejo, S. Srinivasan, Jan Cami, A. A. Zijlstra, J. P. Marshall

Bibliographic record

VenueProceedings of the International Astronomical Union · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Star Formation Studies
Canadian institutionsWestern University
Fundersnot available
KeywordsEmissivityPhysicsStarsAstrophysicsCircumstellar envelopeSurface brightnessFlux (metallurgy)BrightnessCircumstellar dustAstronomyOpticsGalaxyMaterials science

Abstract

fetched live from OpenAlex

Abstract We derive azimuthally-averaged surface-brightness profiles of 16 AGB stars in the far-IR and sub-mm with the aim of studying the resolved historic mass loss in the extended circumstellar envelope. The PSF-subtracted extended component fluxes were found to be ∼40% of the total source flux. By fitting SEDs at each radial point we derive the dust temperature, column density and spectral index of emissivity via Bayesian inference. The measured dust-to-gas ratios were somewhat consistent with canonical values however with a large scatter.

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
Bibliometrics0.0000.000
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 head0.009
GPT teacher head0.230
Teacher spread0.221 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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