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Record W1966969008 · doi:10.1145/1228175.1228196

Interface design for an aircraft thrust and braking indicator/advisor

2006· article· en· W1966969008 on OpenAlexafffund
Shane D. Pinder, D. N. Bristow, T. Claire Davies

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPsychology
TopicHuman-Automation Interaction and Safety
Canadian institutionsUniversity of Waterloo
FundersCanadian Institutes of Health ResearchUniversity of WaterlooUniversity of AucklandAuckland University of Technology, New Zealand
KeywordsCockpitInterface (matter)TakeoffThrustComputer scienceProcess (computing)Human–computer interactionUser interfaceTakeoff and landingWork (physics)Domain (mathematical analysis)AeronauticsSystems engineeringSimulationEngineeringAutomotive engineeringAerospace engineeringOperating systemMechanical engineering

Abstract

fetched live from OpenAlex

Recent advances in the development of aircraft landing and takeoff performance monitoring systems (Pinder, 2003) have shown the feasibility of a cockpit instrument that could aid significantly in the decision making process during the most critical phases of flight, provided that the information can be effectively visualized. The design of a cockpit interface to communicate the information in a timely and efficient manner has now been completed. Here we describe the ecological interface design resulting from a work domain analysis conducted in consultation with industrial partners, and the results of user testing conducted on the prototype bimodal interface. The resulting Thrust and Braking Indicator/Advisor (TABI/A) integrates a visual display with audible advice.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.002

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 head0.054
GPT teacher head0.388
Teacher spread0.334 · 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 designBench or experimental
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

Citations5
Published2006
Admission routes2
Has abstractyes

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