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Record W2098061942 · doi:10.1109/tvcg.2014.18

Dynamic Affordances in Embodied Interactive Systems: The Role of Display and Mode of Locomotion

2014· article· en· W2098061942 on OpenAlex

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

VenueIEEE Transactions on Visualization and Computer Graphics · 2014
Typearticle
Languageen
FieldComputer Science
TopicVirtual Reality Applications and Impacts
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsAffordanceHuman–computer interactionEmbodied cognitionJoystickVirtual realityComputer sciencePerceptionMode (computer interface)Action (physics)Task (project management)SimulationArtificial intelligencePsychologyEngineering

Abstract

fetched live from OpenAlex

We investigated how the properties of interactive virtual reality systems affect user behavior in full-body embodied interactions. Our experiment compared four interactive virtual reality systems using different display types (CAVE vs. HMD) and modes of locomotion (walking vs. joystick). Participants performed a perceptual-motor coordination task, in which they had to choose among a series of opportunities to pass through a gate that cycled open and closed and then board a moving train. Mode of locomotion, but not type of display, affected how participants chose opportunities for action. Both mode of locomotion and display affected performance when participants acted on their choices. We conclude that technological properties of virtual reality system (both display and mode of locomotion) significantly affected opportunities for action available in the environment (affordances) and discuss implications for design and practical applications of immersive interactive systems.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.985
Threshold uncertainty score0.305

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 head0.008
GPT teacher head0.271
Teacher spread0.263 · 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