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Record W4393095066 · doi:10.1093/mnras/stae831

Quantifying the bulk density of southern delta aquariid meteoroids: insights from the Canadian automated meteor observatory

2024· article· en· W4393095066 on OpenAlexaffabout
Arazi Pinhas, Z. Krzeminski, Denis Vida, Peter Brown

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstro and Planetary Science
Canadian institutionsWestern University
FundersMarshall Space Flight CenterNuclear Safety and Security CommissionNational Aeronautics and Space Administration
KeywordsMeteoroidPhysicsMeteor (satellite)ObservatoryMeteor showerAstrophysicsAstronomy

Abstract

fetched live from OpenAlex

ABSTRACT Physical properties of ten millimetre-sized meteoroids from the Southern Delta Aquariids (SDA) shower are derived using optical observations from the Canadian Automated Meteor Observatory between 2020 and 2023. The meteors are found to ablate in two distinct erosion stages, the second stage showing a single, bright leading fragment. Our modelling interprets these observations as evidence for equal masses of compact grains embedded in a porous, low density matrix. The average bulk density of SDA meteors is found to be 1420 ± 100 $\rm {kg \ m^{-3}}$, with the compact component having a density of 2310 ± 160 $\rm {kg \ m^{-3}}$ and the porous component a density of 700 ± 110 $\rm {kg \ m^{-3}}$. The high bulk density of SDA meteors is comparable to densities found for the Quadrantid and Geminid showers, both of which also have low perihelion distances. This suggests that thermal desorption may play a significant role in the processing of meteoroids.

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 score0.154
Threshold uncertainty score0.310

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.017
GPT teacher head0.212
Teacher spread0.195 · 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

Citations2
Published2024
Admission routes2
Has abstractyes

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