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Record W2152221917 · doi:10.1109/vecims.2011.6053842

Comparison of 3D navigation interfaces

2011· article· en· W2152221917 on OpenAlexaff
Joshua McClymont, Dmitri Shuralyov, Wolfgang Stuerzlinger

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInteractive and Immersive Displays
Canadian institutionsYork University
Fundersnot available
KeywordsHuman–computer interactionComputer scienceInterface (matter)User interfaceStyle (visual arts)Post-WIMPNatural user interfaceUser interface designUser experience designOperating system

Abstract

fetched live from OpenAlex

This paper evaluates two different interfaces for navigation in a 3D environment. The first is a `Click-to-Move' style interface that involves using a mouse. The second is a gaming style interface that uses both mouse and keyboard (i.e. the `WASD' keys) for view direction and movement respectively. In the user study, participants were asked to navigate a supermarket environment and collect a specific subset of items. Results revealed significant differences only for some of the sub-measures. Yet, some revealing observations were made regarding user behavior and interaction with the user interface.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.643
Threshold uncertainty score0.154

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 head0.063
GPT teacher head0.332
Teacher spread0.270 · 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

Citations10
Published2011
Admission routes1
Has abstractyes

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