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Record W2486771893 · doi:10.3847/1538-4357/834/2/116

PLANETARY ENGULFMENT AS A TRIGGER FOR WHITE DWARF POLLUTION

2017· article· en· W2486771893 on OpenAlexaff
Cristóbal Petrovich, Diego J. Muñoz

Bibliographic record

VenueThe Astrophysical Journal · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstro and Planetary Science
Canadian institutionsCanadian Institute for Theoretical AstrophysicsThe Scarborough HospitalUniversity of Toronto
Fundersnot available
KeywordsPlanetesimalWhite dwarfPhysicsPlanetAstrophysicsBlack dwarfAccretion (finance)AstronomyPlanetary systemMetallicityAstrobiologyStars

Abstract

fetched live from OpenAlex

ABSTRACT The presence of a planetary system can shield a planetesimal disk from the secular gravitational perturbations due to distant outer massive objects (planets or stellar companions). As the host star evolves off the main sequence to become a white dwarf, these planets can be engulfed during the giant phase, triggering secular instabilities and leading to the tidal disruptions of small rocky bodies. These disrupted bodies can feed the white dwarfs with rocky material and possibly explain the high-metallicity material in their atmospheres. We illustrate how this mechanism can operate when the gravitational perturbations are due to the KL mechanism from a stellar binary companion, a process that is activated only after the planet has been removed/engulfed. We show that this mechanism can explain the observed accretion rates if: (1) the planetary engulfment happens rapidly compared to the secular timescale, which is generally the case for wide binaries ( au) and planetary engulfment during the asymptotic giant branch; (2) the planetesimal disk has a total mass of . We show that this new mechanism can provide a steady supply of material throughout the entire life of the white dwarfs for all cooling ages and can account for a large fraction (up to nearly half) of the observed polluted white dwarfs.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.244
Teacher spread0.231 · 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

Citations88
Published2017
Admission routes1
Has abstractyes

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