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Record W2126342463 · doi:10.1109/3dui.2008.4476590

Assessing the Effects of Orientation and Device on (Constrained) 3D Movement Techniques

2008· article· en· W2126342463 on OpenAlex
Robert J. Teather, Wolfgang Stuerzlinger

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInteractive and Immersive Displays
Canadian institutionsYork University
Fundersnot available
KeywordsMovement (music)Orientation (vector space)Computer scienceConsistency (knowledge bases)Object (grammar)Computer visionArtificial intelligenceTracking (education)Human–computer interactionSimulationMathematicsPsychologyGeometry

Abstract

fetched live from OpenAlex

We present two studies to assess which physical factors influence 3D object movement tasks with various input devices. Since past research has shown that a mouse with suitable mapping techniques can serve as a good input device for some 3D object movement tasks, we also evaluate which characteristics of the mouse sustain its success. Our first study evaluates the effect of a supporting surface across orientation of input device movement and display orientation. A 3D tracking device was used in all conditions for consistency. The results of this study are inconclusive; no significant differences were found between the factors examined. The results of a second study show that the mouse outperforms the tracker for speed in all instances. The presence of support also improved accuracy when tracker movement is limited to 2D operation. A 3DOF movement mode performed worst overall.

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.

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: Empirical
Teacher disagreement score0.404
Threshold uncertainty score0.127

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 head0.017
GPT teacher head0.303
Teacher spread0.287 · 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

Quick stats

Citations34
Published2008
Admission routes1
Has abstractyes

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