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Record W577104397

WAAS IN CANADA : AUGMENTED GLOBAL POSITIONING SATELLITE SIGNALS PROMISE IMPROVED NAVIGATION IN CANADA

2004· article· en· W577104397 on OpenAlexaboutno aff
C McCormick

Bibliographic record

VenueAirports international · 2004
Typearticle
Languageen
FieldEngineering
TopicAir Traffic Management and Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsRunwayGlobal Positioning SystemAviationAir traffic controlSatelliteAeronauticsComputer scienceReal-time computingEngineeringTelecommunicationsGeographyAerospace engineering
DOInot available

Abstract

fetched live from OpenAlex

NAV Canada and the Federal Aviation Administration (FAA) announced in September of 2004 that NAV Canada will host and maintain four ground monitoring stations, which will enable the airspace to have access to Wide Area Augmentation System (WAAS) signals, improved Global Positioning System (GPS) navigational devices and improved runway approach systems. WAAS offers positioning accuracy to within about two meters throughout a flight, its most publicized capability is on the approach, where positional accuracy is critical. Aircraft using GPS/WAAS signals will be able to be located vertically and laterally within two meter, with very high reliability. By contrast, GPS approaches rely on on-board equipment for vertical location and so are considered non-precision. The FAA calls this new level of service, lateral precision, vertical guidance (LPV). It is also close to the CAT-1 minimums for approaches. WAAS approaches can be tailored to any runway, but justification needs to be made for the design of one. Increased usability is a generally accepted benchmark. Future developments in WAAS depend on how and if the system is supported by additional operators, including the International Air Transport Association. Supporters expect it to eventually catch on, just as GPS supported approaches did starting in 1994.

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: Empirical
Teacher disagreement score0.182
Threshold uncertainty score0.997

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 head0.003
GPT teacher head0.170
Teacher spread0.167 · 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

Citations0
Published2004
Admission routes1
Has abstractyes

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