MétaCan
Menu
Back to cohort
Record W2117987166 · doi:10.1177/154193120004403318

Dynamic Tethering for Enhanced Remote Control and Navigation

2000· article· en· W2117987166 on OpenAlexaff
Herman W. Colquhoun, Paul Milgram

Bibliographic record

VenueProceedings of the Human Factors and Ergonomics Society Annual Meeting · 2000
Typearticle
Languageen
FieldComputer Science
TopicVirtual Reality Applications and Impacts
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEndocentric and exocentricComputer scienceTask (project management)Situation awarenessTetheringOffset (computer science)Operator (biology)Human–computer interactionSimulationComputer visionArtificial intelligenceEngineering

Abstract

fetched live from OpenAlex

Misalignments between display and control reference frames complicate execution of many remote control tasks by loading the operator's attentional resources with mental transformations. It is thus important to maintain alignment between an operator's controls and her view of the controlled object or task space. Maximising the operator's situational awareness within this task space by providing an optimal frame of reference also simplifies task execution. Traditional rigid tethering integrates desirable egocentric and exocentric aspects of a display by connecting an exocentric view of the task space to the system being controlled. This paper introduces the concept of dynamic tethering (a superset of rigid tethering) which also preserves the principle of the moving part while maintaining control-display motion compatibility. Two experiments are presented, which show that compliance with these principles decreases the frequency of control reversals, improves reaction times, and decreases the RMS error associated with tracking performance.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.604
Threshold uncertainty score0.358

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 head0.010
GPT teacher head0.244
Teacher spread0.233 · 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 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

Citations11
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the Human Factors and Ergonomics Society Annual MeetingSame topicVirtual Reality Applications and ImpactsFrench-language works237,207