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Record W4392588348 · doi:10.3847/2041-8213/ad28c5

Jupiter’s Metastable Companions

2024· article· en· W4392588348 on OpenAlexaff
Sarah Greenstreet, Brett Gladman, Mario Jurić

Bibliographic record

VenueThe Astrophysical Journal Letters · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstro and Planetary Science
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsJovianPhysicsAstronomyJupiter (rocket family)TrojanPlanetAsteroidPopulationAstrophysicsGas giantAstrobiologySaturnExoplanet

Abstract

fetched live from OpenAlex

Abstract Jovian co-orbitals share Jupiter’s orbit and exhibit 1:1 mean-motion resonance with the planet. This includes >10,000 so-called Trojan asteroids surrounding the leading (L4) and trailing (L5) Lagrange points, viewed as stable groups dating back to planet formation. A small number of extremely transient horseshoe and quasi-satellite co-orbitals have been identified, which only briefly (<1,000 yr) exhibit co-orbital motions. Via an extensive numerical study, we identify for the first time some Trojans that are certainly only “metastable”; instead of being primordial, they are recent captures from heliocentric orbits into moderately long-lived (10 kyr–100 Myr) metastable states that will escape back to the scattering regime. We have also identified (1) the first two Jovian horseshoe co-orbitals that exist for many resonant libration periods and (2) eight Jovian quasi-satellites with metastable lifetimes of 4–130 kyr. Our perspective on the Trojan population is thus now more complex as Jupiter joins the other giant planets in having known metastable co-orbitals that are in steady-state equilibrium with the planet-crossing Centaur and asteroid populations; the 27 identified here are in agreement with theoretical estimates.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.010
GPT teacher head0.222
Teacher spread0.212 · 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 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

Citations4
Published2024
Admission routes1
Has abstractyes

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