MétaCan
Menu
Back to cohort
Record W601988509

DRIVING IN HYPERSPACE : IMPROVING VEHICLE DRIVER SKILLS IS PART OF THE FAA'S RUNWAY INCURSION REDUCTION PLAN

2002· article· en· W601988509 on OpenAlexaboutno aff
C McCormick

Bibliographic record

VenueAirports international · 2002
Typearticle
Languageen
FieldEngineering
TopicAerospace and Aviation Technology
Canadian institutionsnot available
Fundersnot available
KeywordsWindshieldRunwayAeronauticsEngineeringPlan (archaeology)Transport engineeringTraining (meteorology)Automotive engineeringSimulationAerospace engineering
DOInot available

Abstract

fetched live from OpenAlex

Extending training for drivers of airside utility vehicles beyond classroom instruction can be done by means of computer simulation. But many airports have minimal training for airside drivers, and a large number don't have any training at all. A Canadian company has created the Evolution Driver Simulator (EDS), which creates a realistic 3-D airport environment, along with a steering wheel, accelerator, brakes and desktop monitor, which is the windshield. It would replace costly tutoring sessions on live equipment conducted by veteran employees. It also permits recording of electronic grades as the employee completes each section, so instructors can monitor progress. Still, there are no firm training requirements for ground crews, which means training is inconsistent between airports.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.178
Threshold uncertainty score0.370

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 head0.005
GPT teacher head0.181
Teacher spread0.176 · 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 designObservational
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
Published2002
Admission routes1
Has abstractyes

Explore more

Same venueAirports internationalSame topicAerospace and Aviation TechnologyFrench-language works237,207