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Record W4413028788 · doi:10.1029/2025rs008305

Enhanced Meteoroid Trajectory and Speed Reconstruction Using a Forward Scatter Radio Network: Pre‐t0 ${t}_{0}$ Phase Technique and Uncertainty Analysis

2025· article· en· W4413028788 on OpenAlex
Joachim Balis, H. Lamy, Michel Anciaux, Emmanuël Jehin, Johan De Keyser, Daniel Kastinen, Peter Brown

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueRadio Science · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstro and Planetary Science
Canadian institutionsWestern University
FundersSolar-Terrestrial Centre of ExcellenceNuclear Safety and Security CommissionBelgian Federal Science Policy OfficeNational Aeronautics and Space Administration
KeywordsMeteoroidTrajectoryPhase (matter)PhysicsOpticsComputer scienceRemote sensingGeologyAstronomy

Abstract

fetched live from OpenAlex

Abstract This study presents an enhanced method for reconstructing meteoroid trajectories and speeds using the Belgian RAdio Meteor Stations forward scatter radio network. A novel extension of the pre‐ phase technique, originally developed for backscatter radars, has been adapted for forward scatter continuous wave systems. This method leverages phase data recorded before the meteoroid reaches the specular reflection point to improve speed estimations. Additionally, we combine this newly determined pre‐ speed information with time of flight measurements into the trajectory solver to reduce uncertainties in meteoroid path and speed reconstructions. A Markov Chain Monte Carlo method is employed to propagate measurement uncertainties to the trajectory parameters. The reconstructed trajectories and speeds are validated against optical data from the CAMS‐BeNeLux network. The results show significant improvements in the accuracy and robustness of speed and inclination determination.

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.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.767
Threshold uncertainty score0.641

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0000.001
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 head0.008
GPT teacher head0.265
Teacher spread0.257 · 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