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Record W2328405779 · doi:10.1093/mnras/stu2327

A 13-year radar study of the η-Aquariid meteor shower

2014· article· en· W2328405779 on OpenAlexafffundabout
M. Campbell‐Brown, Peter Brown

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstro and Planetary Science
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsNational Aeronautics and Space Administration
KeywordsMeteoroidMeteor showerPhysicsMeteor (satellite)AstrophysicsShowerFlux (metallurgy)Orbit (dynamics)GeodesyMeteorologyAstronomyGeology

Abstract

fetched live from OpenAlex

We measure the activity and orbital characteristics of the η-Aquariid meteor shower appropriate to meteoroids of 200 μm size (mass ≈ 5–10 μg) based on ∼4 × 104 stream orbits measured by the Canadian Meteor Orbit Radar during the years 2002–2014. Significant activity from the stream is found to last from April 25–May 21 (λ⊙ = 35°–60°) with the shower detectable approximately one week on either side of these dates just above the median background. The radiant at peak activity (λ⊙ = 45|$_{.}^{\circ}$|5) is located at αg = 337|$_{.}^{\circ}$|8, δg = −0|$_{.}^{\circ}$|6 and shows a consistent drift of Δαg = +0|$_{.}^{\circ}$|69, Δδg = +0|$_{.}^{\circ}$|60. The velocity of the stream throughout its active period remains within ≈1 km s−1 of Vg = 64.3 km s−1 found at the peak; however, there are indications this is an underestimate due to undercorrection for stream meteoroids having larger than average deceleration. The activity profile shows no mass dependence between μg to mg sizes, but a clear asymmetry with the slope of the ascending branch having B+ = 0.135 ± 0.003 and the descending branch B− = 0.078 ± 0.003. The average yearly equivalent radar-measured peak Zenithal Hourly Rate (ZHR) is 50–80 from 2002–2014, with outbursts in 2004 and 2013 exceeding ZHRs of 100. The mass index shows a minimum at the time of the flux maximum with 1.8 ≤ s ≤ 1.9.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.157
Threshold uncertainty score0.400

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 science0.0010.000
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 head0.006
GPT teacher head0.188
Teacher spread0.182 · 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 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

Citations16
Published2014
Admission routes3
Has abstractyes

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