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Record W2100953905 · doi:10.1109/glocom.1990.116488

The Canadian Olympus propagation experiment

2002· article· en· W2100953905 on OpenAlexafffundabout
R.L. Olsen, Dimitrios Makrakis, D. V. Rogers, R.C. Berube, W. Lam, J. I. Strickland, Yahia M. M. Antar, Jacques Albert, Sze Ki Melanie Tam, See Liang Foo, L. E. Allen, A. Hendry

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSatellite Communication Systems
Canadian institutionsMcGill UniversityMPB Technologies & Communications (Canada)Royal Military College of CanadaCommunications Research Centre Canada
FundersCanadian Space AgencyMinistère de la Défense Nationale
KeywordsAttenuationRemote sensingRadarElectric beaconBeaconSatelliteCommunications satelliteRadio propagationComputer scienceGeologyMeteorologyTelecommunicationsPhysicsOpticsAstronomy

Abstract

fetched live from OpenAlex

The planning of commercial and military satellite communication systems using the upper SHF and lower EHF bands has resulted in a need for more propagation data and models for these bands. This is especially true for VSAT systems using small attenuation margins for which accurate data are particularly scarce and existing models inaccurate. The Canadian Olympus propagation experiment, designed to obtain such data, is described. The experiment includes simultaneous attenuation and depolarization measurements using the 12, 20, and 30 GHz Olympus satellite beacons, radiometric measurements of attenuation at 14, 20, and 30 GHz, and polarimetric radar measurements at 9.6 GHz. One novel feature of the experiment is the attempt to use the radar data to help separate the statistics of melting layer attenuation from beacon-measured total attenuation.>

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.056
Threshold uncertainty score0.168

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0070.002
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0210.004

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 head0.032
GPT teacher head0.213
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

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

Citations2
Published2002
Admission routes3
Has abstractyes

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