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Record W4229446670 · doi:10.3389/fspas.2022.893061

Planetary Nebulae as Sources of Chemical Enrichment of the Galaxy

2022· article· en· W4229446670 on OpenAlexafffund
Sun Kwok

Bibliographic record

VenueFrontiers in Astronomy and Space Sciences · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Star Formation Studies
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPlanetary nebulaPhysicsAsymptotic giant branchCircumstellar envelopeAstrochemistryAstrophysicsInterstellar mediumGalaxyAstrobiologyAstronomyPhotosphereSolar SystemStarsFormation and evolution of the Solar SystemSpectral line

Abstract

fetched live from OpenAlex

During the late asymptotic giant branch (AGB) phase of stellar evolution, the element carbon is created through the triple- α nuclear reaction. This is followed by the synthesis of other heavy elements via neutron capture in the core and the dredge-up of these elements to the surface by convection. Simple molecules and solid-state minerals begin to form in the upper photosphere. These molecules and solids are ejected into the interstellar medium by a strong stellar wind. During the subsequent post-AGB evolution, complex organics with aromatic and aliphatic structures are synthesized in the circumstellar envelope. Planetary nebulae, formed by swept-up circumstellar material, are found to show strong spectral signatures of ions, atoms, molecules, and inorganic and organic solids. These ejected materials of planetary nebulae serve as primordial ingredients of formation of new stars and planetary systems. Stellar synthesized organic solids may survive their journeys through the interstellar medium and evidence for remnants of such organics can be found in our own Solar System. In this paper, we summarize the recent observations of circumstellar synthesis of molecules and solids and discuss the implications of these ejected circumstellar materials on the chemical enrichment of the Galaxy and planetary systems.

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 score0.616
Threshold uncertainty score0.227

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 head0.005
GPT teacher head0.200
Teacher spread0.194 · 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

Citations6
Published2022
Admission routes2
Has abstractyes

Explore more

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