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Record W2064846308 · doi:10.1086/592764

Lithium Depletion of Nearby Young Stellar Associations

2008· article· en· W2064846308 on OpenAlexaff
Erin Mentuch Cooper, A. Brandeker, M. H. van Kerkwijk, Ray Jayawardhana, P. H. Hauschildt

Bibliographic record

VenueThe Astrophysical Journal · 2008
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsmyrAstrophysicsPhysicsStarsSurface gravityCluster (spacecraft)Open clusterLithium (medication)Spectral lineAbundance (ecology)Effective temperatureStar clusterAstronomyChemistryBiologyEcology

Abstract

fetched live from OpenAlex

We estimate cluster ages from lithium depletion in five pre-main-sequence groups found within 100 pc of the Sun: TW Hydrae Association, Eta Chamaeleontis Cluster, Beta Pictoris Moving Group, Tucanae-Horologium Association and AB Doradus Moving Group. We determine surface gravities, effective temperatures and lithium abundances for over 900 spectra through least squares fitting to model-atmosphere spectra. For each group, we compare the dependence of lithium abundance on temperature with isochrones from pre-main-sequence evolutionary tracks to obtain model dependent ages. We find that the Eta Chamaelontis Cluster and the TW Hydrae Association are the youngest, with ages of 12+/-6 Myr and 12+/-8 Myr, respectively, followed by the Beta Pictoris Moving Group at 21+/-9 Myr, the Tucanae-Horologium Association at 27+/-11 Myr, and the AB Doradus Moving Group at an age of at least 45 Myr (where we can only set a lower limit since the models -- unlike real stars -- do not show much lithium depletion beyond this age). Here, the ordering is robust, but the precise ages depend on our choice of both atmospheric and evolutionary models. As a result, while our ages are consistent with estimates based on Hertzsprung-Russell isochrone fitting and dynamical expansion, they are not yet more precise. Our observations do show that with improved models, much stronger constraints should be feasible: the intrinsic uncertainties, as measured from the scatter between measurements from different spectra of the same star, are very low: around 10 K in effective temperature, 0.05 dex in surface gravity, and 0.03 dex in lithium abundance.

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 score0.018
Threshold uncertainty score0.366

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 head0.014
GPT teacher head0.224
Teacher spread0.209 · 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

Citations161
Published2008
Admission routes1
Has abstractyes

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