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Record W2016051508 · doi:10.1177/154193120905300117

Proposed Techniques for Extending Ecological Interface Design to Tactile Displays: Using Tactile Cues to Enhance UAV Interface Design

2009· article· en· W2016051508 on OpenAlexaff
G. Robert Arrabito, Geoffrey Ho, Heidi Au, Jocelyn Keillor, Mark Rutley, Annie Lambert, Ming Hou

Bibliographic record

VenueProceedings of the Human Factors and Ergonomics Society Annual Meeting · 2009
Typearticle
Languageen
FieldPsychology
TopicHuman-Automation Interaction and Safety
Canadian institutionsDefence Research and Development Canada
Fundersnot available
KeywordsInterface (matter)SAFERHuman–computer interactionComputer scienceRelation (database)Interface design

Abstract

fetched live from OpenAlex

There is little guidance for designers on how to map information requirements to tactile displays. In this paper, we propose new directions for carrying out the mapping of tactile displays based on semantic mapping techniques used in auditory and visual displays. We discuss these techniques in relation to the design of a multimodal ground control station (GCS) for unmanned aerial vehicles to improve the visually-dominated GCS interface. We hope that this approach will encourage the design of better, safer, and more intuitive UAV GCS interfaces to reduce the frequency of mishaps related to human error.

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)0.007
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.045
GPT teacher head0.368
Teacher spread0.323 · 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
Published2009
Admission routes1
Has abstractyes

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