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Record W3081618648 · doi:10.1002/sat.1375

Non‐geostationary satellite orbit communications satellite constellations history

2020· article· en· W3081618648 on OpenAlexaff
Tom Butash, P. Garland, B.G. Evans

Bibliographic record

VenueInternational Journal of Satellite Communications and Networking · 2020
Typearticle
Languageen
FieldEngineering
TopicSatellite Communication Systems
Canadian institutionsValacta (Canada)Ste. Anne's Hospital
Fundersnot available
KeywordsGeostationary orbitConstellationComputer scienceSatelliteTelecommunicationsSatellite constellationCommunications satelliteBroadbandRemote sensingAstronomyGeologyPhysics

Abstract

fetched live from OpenAlex

Summary This special issue of the journal on ‘constellations’ comes at a critical time in their development as a second wave of such non‐geostationary satellite orbit (NGSO) systems is being planned and deployed. These mega‐constellations as they have become known are, with a few exceptions, very much larger than those in the first wave and are focused on broadband and 5G applications rather than speech and narrow band data as those deployed in the first wave during the 1990s. However, as we explain in this editorial, there are many similarities in the design and business plans to the first wave and, perhaps, many similar lessons to be learned.

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)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0010.001
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0130.005

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 head0.073
GPT teacher head0.267
Teacher spread0.194 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations33
Published2020
Admission routes1
Has abstractyes

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