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Record W6910759470 · doi:10.48620/84769

Antenna Design for the Arctic Weather Satellite Microwave Sounder

2023· article· en· W6910759470 on OpenAlexaff

Bibliographic record

VenueOpen Access CRIS of the University of Bern · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil Moisture and Remote Sensing
Canadian institutionsApollo Microwaves (Canada)
Fundersnot available
KeywordsRadiometerMicrowaveAntenna (radio)SatelliteCalibrationArcticMicrowave radiometerParabolic antennaFocus (optics)

Abstract

fetched live from OpenAlex

The Arctic Weather Satellite (AWS) is a prototype mission for an operational constellation of microwave sounders, complimenting existing meteorological sounders. The AWS is a microsatellite with a single cross-track scanning radiometer operating in the 54, 89, 183 and 325 GHz bands. Due to the small platform size, the core design focus of the radiometer’s quasi-optics is less complexity and a more compact setup than comparable spaceborne microwave sounders. To achieve this, the instrument utilises a splitblock feedarray which directly illuminates the off-axis parabolic scanning reflector. A secondary parabolic reflector is used to couple into a wedge-shaped load which is used for calibration in combination with cold sky measurements. The main challenge for instrument performance is that only one of the four horns can be located in the focus of the scanning reflector. Consequently, scan angle dependent spillover variations and beam asymmetries can occur. This paper details the simulation and optimisation efforts of the quasi-optics to minimise the aforementioned effects.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.648
Threshold uncertainty score0.926

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 science0.0020.001
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 head0.059
GPT teacher head0.285
Teacher spread0.226 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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