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Record W2141677995 · doi:10.1109/plans.1996.509075

Preoperational testing of data link-based air traffic management systems in Magadan, Far East Russia

2002· article· en· W2141677995 on OpenAlexaboutno aff
Alexander P Shuvaev, R.T. Oishi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAir Traffic Management and Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsGlobal Positioning SystemAir traffic controlRadarSecondary surveillance radarPosition (finance)AeronauticsAir traffic control radar beacon systemAutomatic dependent surveillance-broadcastReliability (semiconductor)Data linkEngineeringTransport engineeringComputer scienceTelecommunicationsAerospace engineeringRadar engineering detailsRadar imagingBusiness

Abstract

fetched live from OpenAlex

The Global Positioning System (GPS) has been used in many different applications. This paper discusses one such application: the surveillance of commercial aircraft in a developing airspace environment. GPS provides system users with the ability to determine their own position with an accuracy, reliability and cost that is unprecedented. Voice procedures augmented by radar have been the primary tools for air traffic surveillance since the end of World War II. But for some countries the equipage of aircraft with GPS and a data link capable of carrying position reports to the ATC authorities is providing a viable alternative to long-range secondary radar systems. In 1995, ARINC installed and demonstrated equipment in Magadan, Russia, which permits air traffic controllers of MAGADANAEROCONTROL to monitor GPS position reports generated by aircraft as far away as Canada and the South Pacific. The position reports were displayed against maps and flight tracks. This equipment has clearly demonstrated an alternative technology for the upgrading of the ATC system in Siberia and other remote areas.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.918
Threshold uncertainty score0.482

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 science0.0000.000
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 head0.041
GPT teacher head0.210
Teacher spread0.169 · 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 designSimulation or modeling
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

Citations1
Published2002
Admission routes1
Has abstractyes

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