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Record W2528810434 · doi:10.1175/jtech-d-16-0143.1

The Imperfect Phase Pattern of Real Parabolic Radar Antenna and Data Quality

2016· article· en· W2528810434 on OpenAlexafffundabout
Ya-Chien Feng, Frédéric Fabry

Bibliographic record

VenueJournal of Atmospheric and Oceanic Technology · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicPrecipitation Measurement and Analysis
Canadian institutionsMcGill University
FundersEnvironment and Climate Change CanadaNatural Sciences and Engineering Research Council of CanadaMcGill University
KeywordsRadarRemote sensingAntenna (radio)Radar imagingPhase (matter)AzimuthComputer scienceGeologyEnvironmental scienceOpticsPhysicsTelecommunications

Abstract

fetched live from OpenAlex

Abstract Although antennas have well-known power patterns that are commonly used to understand the quality of measurements, they also have phase patterns that are difficult to obtain and are seldom discussed in the radar meteorological community. This study presents the characteristics of the antenna phase pattern of the McGill S-band radar. Phase variations in azimuth and elevation with respect to the main beam axis are obtained using high-resolution scans of an isolated ground target and of an emission source. The two-way phase pattern is relatively constant within the radar main beam, but it changes rapidly at the power minima between the main beam and the first sidelobe. The effects of this phase pattern on ground and weather targets were evaluated and were found to be much more pronounced for point targets than for distributed targets. Nevertheless, proper knowledge of the phase pattern of the radar antenna would enhance the ability to better select ground targets for radar refractivity retrieval and to estimate the quality of radar data.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.591
Threshold uncertainty score0.148

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.026
GPT teacher head0.284
Teacher spread0.258 · 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 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

Citations4
Published2016
Admission routes3
Has abstractyes

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