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Record W3201249706 · doi:10.1093/mnras/stab2557

Meteor shower radiant dispersions in Global Meteor Network data

2021· article· en· W3201249706 on OpenAlexafffund
Althea V. Moorhead, Tiffany D. Clements, Denis Vida

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstro and Planetary Science
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of CanadaNational Aeronautics and Space Administration
KeywordsMeteor showerMeteoroidMeteor (satellite)ShowerPhysicsEnvironmental scienceMeteorologyAstronomy

Abstract

fetched live from OpenAlex

ABSTRACT Meteor showers occur when streams of meteoroids originating from a common source intersect the Earth. There will be small dissimilarities between the direction of motion of different meteoroids within a stream, and these small differences will act to broaden the radiant, or apparent point of origin, of the shower. This dispersion in meteor radiant can be particularly important when considering the effect of the Earth’s gravity on the stream, as it limits the degree of enhancement of the stream’s flux due to gravitational focusing. In this paper, we present measurements of the radiant dispersion of 12 showers using observations from the Global Meteor Network. We find that the median offset of individual meteors from the shower radiant ranges from 0.32○ for the eta Aquariids to 1.41○ for the Southern Taurids. We also find that there is a small but statistically significant drift in Sun-centred ecliptic radiant and/or geocentric speed over time for most showers. Finally, we compare radiant dispersion with shower duration and find that, in contrast with previous results, the two quantities are not correlated in our data.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.683

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 science0.0010.001
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 head0.013
GPT teacher head0.222
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 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

Citations10
Published2021
Admission routes2
Has abstractyes

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