MétaCan
Menu
Back to cohort
Record W1492753264 · doi:10.3233/scc-2002-271

Ka‐band rain attenuation estimation using weather radar

2002· article· en· W1492753264 on OpenAlex

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

VenueSpace Communications · 2002
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicPrecipitation Measurement and Analysis
Canadian institutionsLockheed Martin (Canada)
Fundersnot available
KeywordsRadarWeather radarAttenuationRemote sensingIce crystalsRadar horizonEnvironmental scienceMeteorologyOpticsPulse-Doppler radarGeologyPhysicsRadar imagingComputer scienceTelecommunications

Abstract

fetched live from OpenAlex

Weather radars have been routinely used for investigating propagation phenomena which affect satellite communication links. Weather radar returns can be used to estimate both attenuation and depolarization produced by hydrometeors. Some of the early radar measurements resulted in the discovery of high altitude ice particles as a potential source for depolarization and the development of models for the melting layer or the radar bright band. The radar return from precipitation particles is proportional to the number density of particles in the radar pulse volume. The reflectivity can be converted to an equivalent rain rate or signal attenuation through appropriate assumptions on the particle size distribution. If the radar is capable of measuring reflectivity in two orthogonal polarizations, the difference between the two reflectivity measurements is a direct estimate of the anisotropy of the particulate medium. Differential reflectivity can be used to detect regions containing highly non‐spherical particles such as the melting layer and high altitude ice particles. Results of an experiment involving a dual polarized radar to estimate Ka‐band path attenuation at a tropical location are presented.

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 categoriesInsufficient payload (model declined to judge)
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 score0.880
Threshold uncertainty score0.998

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)0.0030.001

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 head0.098
GPT teacher head0.280
Teacher spread0.181 · 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