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Record W1782612819

Comparison of Radar Simulator for Air Traffic Control

2014· article· sl· W1782612819 on OpenAlexaboutno aff
Juraj Vagner, Edina Pappová

Bibliographic record

VenueHrčak Portal of scientific journals of Croatia (University Computing Centre) · 2014
Typearticle
Languagesl
FieldEngineering
TopicAerospace Engineering and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsAir traffic controlAviationRadarSimulationWork (physics)Flight simulatorSecondary surveillance radarControl (management)EngineeringService (business)Transport engineeringAir traffic control radar beacon systemAeronauticsComputer scienceTelecommunications
DOInot available

Abstract

fetched live from OpenAlex

The main aim of this article is to compare different types of air traffic control simulators, which are produced by several manufacturers. These may come from various countries, such as Czech Republic, Great Britain, United States of America, Canada and France. At the beginning of this work, the simulator is defined as an aviation ground equipment, which has to prepare air traffic controllers for their work and position for real air traffic as this profession requires perfect and precise training. Simulators are characterized by technical parameters, configuration of the simulator, types of simulated events, simulation of emergency situations, construction, services which are offered by company, service and maintenance and by other facilities. The final part of the work provides a comparison of the simulators of which one is chosen as the best choice. Comparison of Radar Simulator for Air Traffic Control

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.015
GPT teacher head0.249
Teacher spread0.235 · 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 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

Citations11
Published2014
Admission routes1
Has abstractyes

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