MétaCan
Menu
Back to cohort
Record W4386980120 · doi:10.1093/mnras/stad2867

Planetesimals at DZ stars – I. Chondritic compositions and a massive accretion event

2023· article· en· W4386980120 on OpenAlexaff
Andrew Swan, Jay Farihi, Carl Melis, P. Dufour, Steven J. Desch, D. Koester, Jincheng Guo

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstro and Planetary Science
Canadian institutionsUniversité de Montréal
FundersUppsala UniversitetUniversität WienScience and Technology Facilities CouncilEuropean CommissionNational Natural Science Foundation of ChinaH2020 European Research CouncilNational Aeronautics and Space AdministrationCalifornia Institute of TechnologyW. M. Keck Foundation
KeywordsPhysicsPlanetesimalWhite dwarfAstrophysicsAstronomyAccretion (finance)StarsAsteroidDebris diskSolar SystemChondriteYoung stellar objectAstrobiologyPlanetary systemStar formationMeteorite

Abstract

fetched live from OpenAlex

ABSTRACT There is a wealth of evidence to suggest that planetary systems can survive beyond the main sequence. Most commonly, white dwarfs are found to be accreting material from tidally disrupted asteroids, whose bulk compositions are reflected by the metals polluting the stellar photospheres. While many examples are known, most lack the deep, high-resolution data required to detect multiple elements, and thus characterize the planetesimals that orbit them. Here, spectra of seven DZ white dwarfs observed with Keck High Resolution Echelle Spectrometer (HIRES) are analysed, where up to nine metals are measured per star. Their compositions are compared against those of Solar system objects, working in a Bayesian framework to infer or marginalize over the accretion history. All of the stars have been accreting primitive material, similar to chondrites, with hints of a Mercury-like composition at one star. The most polluted star is observed several Myr after its last major accretion episode, in which a Moon-sized object met its demise.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.295
Threshold uncertainty score0.428

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 head0.007
GPT teacher head0.206
Teacher spread0.199 · 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 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

Citations22
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueMonthly Notices of the Royal Astronomical SocietySame topicAstro and Planetary ScienceFrench-language works237,207