MétaCan
Menu
Back to cohort
Record W2000005233 · doi:10.1049/ip-rsn:20020227

Numerical analysis of the response of HF radar to meteor backscatter detection

2002· article· en· W2000005233 on OpenAlex
T. Thayaparan

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

VenueIEE Proceedings - Radar Sonar and Navigation · 2002
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsDepartment of National Defence
Fundersnot available
KeywordsMeteor (satellite)MeteoroidRadarPulse repetition frequencyWavelengthRemote sensingBackscatter (email)RADIUSRadar cross-sectionPhysicsGeologyOpticsMeteorologyTelecommunicationsComputer scienceAstronomy

Abstract

fetched live from OpenAlex

The response of a high frequency radar system to echoes from underdense meteor trails is numerically calculated. The strengths and limitations of radar detection of meteors at different radar frequencies have been studied based on standard theory. The standard theory takes into account the initial trail radius, the finite meteor velocity, and the radial diffusion. The significance of the pulse repetition frequency and the data sampling interval has been investigated. Height distributions of underdense meteor echoes are predicted, based on standard theory, as a function of radar frequency. The study shows that radars operating at wavelengths of around 5–15 m are unable to detect high-altitude meteors owing to wavelength-dependent ceilings. Long-wavelength radars operating around 15–60 m are potentially able to detect many more underdense meteor echoes than radars operating around 5–15 m. However, there are many important factors influencing the observation of meteors at low radio frequencies and the advantages and drawbacks of radar detection of meteors at low frequency are specifically discussed.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.351
Threshold uncertainty score0.379

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.007
GPT teacher head0.215
Teacher spread0.208 · 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