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Record W2797708215 · doi:10.1093/mnras/sty930

Limits on radio emission from meteors using the MWA

2018· article· en· W2797708215 on OpenAlexaff
X. Zhang, P. J. Hancock, Hadrien A. R. Devillepoix, R. B. Wayth, Adam P. Beardsley, B. Crosse, D. Emrich, T. M. O. Franzen, B. M. Gaensler, L. Horsley, M. Johnston‐Hollitt, D. L. Kaplan, D. Kenney, M. F. Morales, D. Pallot, Kim Steele, S. J. Tingay, Cathryn M. Trott, M. Walker, A. Williams, C. Wu, Jianghui Ji, Yuehua Ma

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRadio Astronomy Observations and Technology
Canadian institutionsCanadian Institute for Theoretical AstrophysicsUniversity of Toronto
FundersChina Scholarship CouncilNational Natural Science Foundation of China
KeywordsPhysicsMeteoroidAstronomyAstrophysics

Abstract

fetched live from OpenAlex

Recently, low-frequency, broad-band radio emission has been observed accompanying bright meteors by the Long Wavelength Array (LWA). The broad-band spectra between 20 and 60 MHz were captured for several events, while the spectral index (dependence of flux density on frequency, with Sν ∝ να) was estimated to be −4 ± 1 during the peak of meteor afterglows. Here we present a survey of meteor emission and other transient events using the Murchison Wide Field Array (MWA) at 72–103 MHz. In our 322 h survey, down to a 5σ detection threshold of 3.5 Jy beam−1, no transient candidates were identified as intrinsic emission from meteors. We derived an upper limit of −3.7 (95 per cent confidence limit) on the spectral index in our frequency range. We also report detections of other transient events, such as reflected FM broadcast signals from small satellites, conclusively demonstrating the ability of the MWA to detect and track space debris on scales as small as 0.1 m in low Earth orbits.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.016
GPT teacher head0.229
Teacher spread0.213 · 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

Citations21
Published2018
Admission routes1
Has abstractyes

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