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Meteor radiant activity mapping using single-station radar observations

2006· article· en· W2127341285 on OpenAlexaffabout
J. Jones, W. Linwood Jones

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2006
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstro and Planetary Science
Canadian institutionsWestern University
Fundersnot available
KeywordsMeteor (satellite)PhysicsMeteor showerRemote sensingRadarSensitivity (control systems)GeodesyMeteorologyAstronomyGeologyComputer scienceTelecommunications

Abstract

fetched live from OpenAlex

We describe a method for producing high-resolution maps of the radiant distribution of meteor activity over the celestial sphere using single-station radio-meteor observations. The method uses a convolution technique and we show how a suitable convolution function can be chosen to enhance the apparent activity of meteor shower radiants. We apply this method to data produced by the Canadian Meteor Orbit Radar system near London, Ontario and show that the daily motion of the radiant can be measured within a fraction of a degree per day. The system has detected a number of weak showers that have not been previously catalogued. We show how the sensitivity of the system can be improved by combining observations from several days.

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 score0.251
Threshold uncertainty score0.801

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 science0.0000.000
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 head0.024
GPT teacher head0.203
Teacher spread0.179 · 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

Citations44
Published2006
Admission routes2
Has abstractyes

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