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A low-cost satellite terminal for measuring Ka-band propagation to low earth orbit using the CASSIOPE satellite

2015· article· en· W1900038067 on OpenAlexaff
David G. Michelson, Hyun-Chang Jang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicPrecipitation Measurement and Analysis
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsGeostationary orbitKa bandSatelliteRemote sensingFadingCommunications satelliteLow earth orbitMedium Earth orbitBeaconFadeGeocentric orbitComputer scienceOrbit (dynamics)Geosynchronous orbitTelecommunicationsAerospace engineeringGeologyEngineering

Abstract

fetched live from OpenAlex

Although Ka-band links to communication satellites in geostationary orbit (GEO) have been used for many years, their use in communicating with communication and remote sensing satellites in low earth orbit (LEO) is still emerging. Of particular interest to designers is characterization of the rate of fading, i.e., the so-called fade slope, which is accentuated on links to satellites to LEO by the rapid manner in which the Earth-space path sweeps though rain cells in the vicinity of the Earth station as the satellite passes across the sky. Fade slopes steepen as the orbital altitude of the satellite decreases and as the intensity of individual rain cells increases. The result has important implications for the design of the power control loops and other mitigation strategies used to mitigate rain fading on such links. Only a few satellites in LEO carry Ka-band propagation beacons or receivers suitable for use in propagation studies and, for various reasons, relatively little measurement data to support design of such links is available.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.003

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 head0.103
GPT teacher head0.271
Teacher spread0.168 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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
Published2015
Admission routes1
Has abstractyes

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