MétaCan
Menu
← Back to cohort
Record W4402741296 · doi:10.1051/0004-6361/202451708

The impact of third dredge-up on the mass loss of Mira variables

2024· article· en· W4402741296 on OpenAlexfundno aff
S. Uttenthaler, S. Shetye, A. Nanni, B. Aringer, Iain McDonald, D. Gobrecht, S. Höfner, U. Wolter, S. Cristallo, Klaus Bernhard

Bibliographic record

VenueAstronomy and Astrophysics · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysics and Gravity Measurements
Canadian institutionsnot available
FundersInstitut sur la Nutrition et les Aliments FonctionnelsUniversity of California, Los AngelesJet Propulsion LaboratoryKnut och Alice Wallenbergs StiftelseNational Aeronautics and Space AdministrationFonds Wetenschappelijk OnderzoekUppsala Multidisciplinary Center for Advanced Computational ScienceInstituto de Astrofísica de CanariasEuropean Research CouncilVlaamse regeringNarodowe Centrum NaukiCalifornia Institute of TechnologyEuropean CommissionNational Science FoundationEuropean Space AgencyVetenskapsrådet
KeywordsPhysicsAstrophysicsAstronomy

Abstract

fetched live from OpenAlex

Context. The details of the mass-loss process in the late stages of low- and intermediate-mass stellar evolution are not well understood, in particular its dependence on stellar parameters. Mira variables are highly suitable targets for studying this mass-loss process. Aims. Here, we follow up on our earlier finding that a near-to-mid-infrared (NIR-MIR) colour versus pulsation period diagram shows two sequences of Miras that can be distinguished by the third dredge-up (3DUP) indicator technetium in those stars. While IR colours are good indicators of the dust mass-loss rate (MLR) from Miras, no corresponding sequences have been found using the gas MLR. However, investigations of the gas MLR have been hampered by data limitations. We aim to alleviate these limitations with new observational data. Methods. We present new optical spectra of a well-selected sample of Miras. We searched these spectra for absorption lines of Tc and other 3DUP indicators, and combine our findings with gas MLRs and expansion velocities from the literature. Furthermore, we extend the analysis of the MIR emission to WISE data and compare the broadband spectral energy distributions (SEDs) of Miras with and without Tc. Results. We find no systematic difference in gas MLRs between Miras with and without Tc. However, the gas envelopes of Tc-poor Miras appear to have a higher terminal expansion velocity than those of Miras with Tc. Furthermore, our analysis of the IR photometry strongly corroborates the earlier finding that Tc-poor Miras have a higher MIR emission than Tc-rich ones, by as much as a factor of two. We model the IR colours with DARWIN and stationary wind models and conclude that Miras with and without Tc have different dust content or dust properties. Conclusions. We discuss several hypotheses and interpretations of the observations and conclude that the reduction of free oxygen by 3DUP of carbon and iron-depleted dust grains in Tc-rich stars are the most convincing explanations for our observations.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.210
Teacher spread0.197 · 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 designSimulation or modeling
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
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueAstronomy and Astrophysics→Same topicGeophysics and Gravity Measurements→French-language works237,207→