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Record W2011527499 · doi:10.1088/0004-6256/143/4/92

THE THIRD SIGNATURE OF GRANULATION IN BRIGHT-GIANT AND SUPERGIANT STARS

2012· article· en· W2011527499 on OpenAlexaff
David F. Gray, Teznie Pugh

Bibliographic record

VenueThe Astronomical Journal · 2012
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsWestern University
Fundersnot available
KeywordsPhysicsAstrophysicsSupergiantStarsGiant starRed supergiantLuminosityGranulationAstronomyBlue supergiantPhotosphereSpectral lineGalaxy

Abstract

fetched live from OpenAlex

We investigated third-signature granulation plots for 18 bright giants and supergiants and one giant of spectral classes G0 to M3. These plots reveal the net granulation velocities, averaged over the stellar disk, as a function of depth. Supergiants show significant differences from the "standard" shape seen for lower-luminosity stars. Most notable is a striking reversal of slope seen for three of the nine supergiants, i.e., stronger lines are more blueshifted than weaker lines, opposite the solar case. Changes in the third-signature plot of α Sco (M1.5 Iab) with time imply granulation cells that penetrate only the lower portion of the photosphere. For those stars showing the standard shape, we derive scaling factors relative to the Sun that serve as a first-order measure of the strength of the granulation relative to the Sun. For G-type stars, the third-signature scale of the bright giants and supergiants is approximately 1.5 times as strong as in dwarfs, but for K stars, there in no discernible difference between higher-luminosity stars and dwarfs. Classical macroturbulence, a measure of the velocity dispersion of the granulation, increases with the third-signature-plot scale factors, but at different rates for different luminosity classes.

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 score0.009
Threshold uncertainty score0.195

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 head0.008
GPT teacher head0.212
Teacher spread0.204 · 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

Citations23
Published2012
Admission routes1
Has abstractyes

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