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Record W2122026050 · doi:10.48550/arxiv.0907.2463

Binary planetary nebulae nuclei towards the Galactic bulge. II. A penchant for bipolarity and low-ionisation structures

2009· article· en· W2122026050 on OpenAlexaff
B. Miszalski, A. Acker, Q. A. Parker, A. F. J. Moffat

Bibliographic record

VenuearXiv (Cornell University) · 2009
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsUniversité de MontréalCentre for Research in Astrophysics of Québec
Fundersnot available
KeywordsPlanetary nebulaPhysicsBulgeAstrophysicsStarsAstronomyBinary numberCommon envelopeIonizationDoubly ionized oxygenEnvelope (radar)Spectral lineEmission spectrumIon

Abstract

fetched live from OpenAlex

Considerable effort has been applied towards understanding the precise shaping mechanisms responsible for the diverse range of morphologies exhibited by planetary nebulae (PNe). A binary companion is increasingly gaining support as a dominant shaping mechanism, however morphological studies of the few PNe that we know for certain were shaped by binary evolution are scarce or biased. Newly discovered binary central stars (CSPN) from the OGLE-III photometric variability survey have significantly increased the sample of post common-envelope (CE) nebulae available for morphological analysis. We present Gemini South narrow-band images for most of the new sample to complement existing data in a qualitative morphological study of 30 post-CE nebulae. Nearly 30% of nebulae have canonical bipolar morphologies, however this rises to 60% once inclination effects are incorporated with the aid of geometric models. This is the strongest observational evidence yet linking CE evolution to bipolar morphologies. A higher than average proportion of the sample shows low-ionisation knots, filaments or jets suggestive of a binary origin. These features are also common around emission-line nuclei which may be explained by speculative binary formation scenarios for H-deficient CSPN.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score0.623

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 studies0.0010.000
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 head0.036
GPT teacher head0.182
Teacher spread0.146 · 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

Citations100
Published2009
Admission routes1
Has abstractyes

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